WO2024169259A1

WO2024169259A1 - Channel state information prediction

Info

Publication number: WO2024169259A1
Application number: PCT/CN2023/129768
Authority: WO
Inventors: Ruixiang MA; Yuantao Zhang; Hongmei Liu; Zhi YAN
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2023-11-03
Filing date: 2023-11-03
Publication date: 2024-08-22
Anticipated expiration: 2026-05-03

Abstract

Various aspects of the present disclosure relate to a user equipment (UE), a base station, apparatuses and methods for predicting channel state information. In an aspect, a UE determines at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter. The UE determines to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window. By implementing the embodiments of the present disclosure, a solution of how to predict CSI using different prediction models trained with different parameters and how to use different CSI-RSs in a measurement window can be provided, and thus the accuracy and efficiency of the prediction results can be improved.

Description

CHANNEL STATE INFORMATION PREDICTION

TECHNICAL FIELD

The present disclosure relates to wireless communications, and more specifically to a user equipment, a base station, apparatuses and methods for predicting channel state information (CSI) .

BACKGROUND

A wireless communications system may include one or multiple network communication devices, such as base stations, which may be otherwise known as an eNodeB (eNB) , a next-generation NodeB (gNB) , or other suitable terminology. Each network communication devices, such as a base station may support wireless communications for one or multiple user communication devices, which may be otherwise known as user equipment (UE) , or other suitable terminology. The wireless communications system may support wireless communications with one or multiple user communication devices by utilizing resources of the wireless communication system (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers) . Additionally, the wireless communications system may support wireless communications across various radio access technologies including third generation (3G) radio access technology, fourth generation (4G) radio access technology, fifth generation (5G) radio access technology, among other suitable radio access technologies beyond 5G (e.g., sixth generation (6G) ) .

A gNB may send CSI reference signals (RS) to a UE. The UE may measure the channel based on CSI-RS and report the quantity of the channel to the gNB in a CSI report. The quantity may be presented by a channel quality indicator (CQI) , rank indication (RI) , precoding matrix indicator (PMI) and so on. The resources used for transmitting the CSI-RSs may be periodic, semi-static, or aperiodic. The UE may perform some CSI-RS related data collection. A model (such as an artificial intelligence (AI) /machine learning (ML) model) may be trained by the UE or the gNB. The UE may predict the CSI report in the future based on the model. In this way, the gNB does not need to send CSI-RSs in the future, which can increase the system capacity.

SUMMARY

The present disclosure relates to a user equipment, a base station, apparatuses and methods for predicting channel state information. In a first aspect of the solution, a UE determines at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter. The UE determines to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window. By implementing the embodiments of the present disclosure, a solution of how to predict CSI using different prediction models trained with different parameters and how to use different CSI-RSs in a measurement window can be provided, and thus the accuracy and efficiency of the prediction results can be improved.

In some implementations of the method and apparatuses described herein, the at least one parameter may comprise one of the following: a number of CSI-RSs in a measurement window; an interval of CSI-RSs in a measurement window; a symbol for a CSI-RS being configured with an uplink (UL) subband or not; or a CSI-RS pattern in a measurement window, wherein the CSI-RS pattern indicates at least one of a CSI-RS position, at least one interval of CSI-RSs, or a number of CSI-RSs in the measurement window.

In some implementations of the method and apparatuses described herein, in the case of one or more CSI-RSs are cancelled in the measurement window, the at least one CSI-RS used for predicting the CSI report may comprise: at least one remaining CSI-RS in the measurement window; or the at least one remaining CSI-RS and at least one supplementary CSI-RS, wherein a supplementary CSI-RS is determined based on the remaining CSI-RS.

In some implementations of the method and apparatuses described herein, a CSI-RS among the one or more CSI-RSs may be cancelled in one of the following cases: the CSI-RS overlaps with UL symbols; the CSI-RS is in a symbol or slot not configured with UL subband, and a prediction model associated with symbol or slot configured with UL subband is used; or one or more CSI-RSs are in a symbol or slot configured with UL subband and a prediction model associated with symbol or slots not configured with UL subband is used.

In some implementations of the method and apparatuses described herein, each of the at least one prediction model is determined based on one of the following: a combination of CSI-RSs associated with symbols or slots configured with UL subband and CSI-RSs associated with symbols or slots not configured with UL subband; CSI-RSs associated with symbols or slots configured with UL subband; or CSI-RSs associated with symbols or slots not configured with UL subband.

In some implementations of the method and apparatuses described herein, in the case that all CSI-RSs are in the symbols or slots configured with UL subband in the measurement window, a prediction model of the at least one prediction model determined based on the CSI-RSs associated with symbols or slots configured with UL subband may be used for prediction; or in the case that all CSI-RSs are in symbols or slots not configured with UL subband in the measurement window, a prediction model of the at least one prediction model determined based on the CSI-RSs associated with symbols or slots not configured with UL subband may be used for prediction.

In some implementations of the method and apparatuses described herein, in the case that none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, the UE may prevent from predicting the CSI report; or in the case that a number of corresponding parameters of CSI-RSs in a measurement window with different parameters exceeds a threshold, the UE may prevent from predicting the CSI report.

In some implementations of the method and apparatuses described herein, the UE may cancel the CSI report for the prediction window; transmit, via the transceiver, the CSI report for the CSI-RSs in the measurement window; or detect, via the transceiver, scheduling information from a base station for scheduling the CSI report for the prediction window.

In some implementations of the method and apparatuses described herein, the UE may predict the CSI report based on a selected prediction model of the at least one prediction model in the following case: a number of CSI-RSs in the measurement window is the same with a number of CSI-RSs used for determining the selected prediction model; or a symbol or slot format of the CSI-RSs in the measurement window is the same with a slot format associated with the CSI-RSs used for determining the selected prediction model.

In some implementations of the method and apparatuses described herein, the UE may predict the CSI report based on a prediction model for symbols or slots configured with UL subband of the at least one prediction model in the following case: a number of CSI-RSs in symbols or slots configured with UL subband in the measurement window is greater than a number of CSI-RSs in symbols or slots not configured with UL subband in the measurement window; or first CSI-RS in symbols or slots configured with UL subband in the measurement window.

In some implementations of the method and apparatuses described herein, in the case that a number of CSI-RSs in symbols or slots configured with UL subband in the measurement window is the same with a number of CSI-RSs in symbols or slots not configured with UL subband in the measurement window, the UE may predict the CSI report based on a predefined or indicated prediction model.

In some implementations of the method and apparatuses described herein, a prediction model of the at least one prediction model may be determined based on CSI-RSs associated with parameters X and Y. X may be a minimum number of CSI-RS instances, and Y may be a maximum interval of the CSI-RS instances. In the case that X for a first prediction model is smaller than or equal to a number of CSI-RSs in the measurement window and/or in the case that Y for the first prediction model is greater than or equal to an interval of CSI-RSs in the measurement window, predict the CSI report based on the first prediction model, the UE may predict the CSI report based on the first prediction model.

In some implementations of the method and apparatuses described herein, the UE may select one of first prediction models to predict the CSI report, and the selected first prediction model may be associated with the same CSI-RS patterns as CSI-RS patterns in the measurement window; the same interval of CSI-RSs as an interval of CSI-RSs in the measurement window; or the same number of CSI-RSs as a number of CSI-RSs in the measurement window.

In some implementations of the method and apparatuses described herein, the UE may predict the CSI report based on a prediction model which is predefined, preconfigured or indicated by a base station.

In some implementations of the method and apparatuses described herein, the UE may predict a plurality of CSI reports based on a plurality of prediction models among the at least one prediction model, wherein the plurality of prediction models are determined based on at least one parameter which is the same as at least one parameter in a measurement window; or the UE may predict the plurality of CSI reports based on the at least one prediction model.

In some implementations of the method and apparatuses described herein, the UE may transmit, via the transceiver to a base station, the plurality of CSI reports; or transmit, via the transceiver to the base station, a CSI report determined based on an average of the plurality of CSI reports.

In some implementations of the method and apparatuses described herein, the UE may predict a first CSI report based on a prediction model associated with symbols or slots configured with UL subband; predict a second CSI report based on a prediction model associated with symbols or slots not configured with UL subband; and transmit, via the transceiver to the base station, the first CSI report and the second CSI report.

In some implementations of the method and apparatuses described herein, in the case that none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, the UE may determine an extended measurement window based on extending the measurement window by one or more time units, and the UE may determine to predict the CSI report based on the one or more prediction models until one or more parameters of CSI-RSs in the extended measurement window are the same as one or more parameters associated with one or more prediction models of the at least one prediction model.

In some implementations of the method and apparatuses described herein, the parameter associated with the at least one CSI-RS in the measurement window may be the same as parameters used for determining one or more prediction model among the at least one prediction model.

In a second aspect of the solution, a BS described herein may include a processor; and a transceiver coupled to the processor, wherein the processor may be configured to determine at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter; and receive, via the transceiver from a UE, one or more CSI reports for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.

In some implementations of the method and apparatuses described herein, the at least one parameter may comprise one of the following: a number of CSI-RSs in a measurement window; an interval of CSI-RSs in a measurement window; a symbol for a CSI-RS being configured with a UL subband or not; or a CSI-RS pattern in a measurement window, wherein the CSI-RS pattern indicates at least one of a CSI-RS position, at least one interval of CSI-RSs, or a number of CSI-RSs in the measurement window.

In some implementations of the method and apparatuses described herein, the BS may transmit, to the UE, an indication indicative of using which prediction models of the at least one prediction model to predict the CSI report.

In some implementations of the method and apparatuses described herein, in the case that none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, or in the case that a number of corresponding parameters of CSI-RSs in a measurement window with different parameters exceeds a threshold, the BS may prevent from receiving the CSI report; receive the CSI report for the CSI-RSs in the measurement window; or transmit scheduling information for scheduling the CSI report for the prediction window.

In some implementations of the method and apparatuses described herein, the BS may receive a plurality of CSI reports based on a plurality of prediction models among the at least one prediction model, wherein the plurality of prediction models are determined based on at least one parameter which is the same as at least one parameter in a measurement window; or receive a plurality of CSI reports based on the at least one prediction model.

In a third aspect of the solution, a processor for wireless communication may comprise: at least one memory; and a controller coupled with the at least one memory and configured to cause the controller to: determine at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter; and determine to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.

In a fourth aspect of the solution, a processor for wireless communication may comprise: at least one memory; and a controller coupled with the at least one memory and configured to cause the controller to: determine at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information CSI-RSs associated with at least one parameter; and receive, via the transceiver from a UE, one or more CSI reports for a prediction window at least one CSI-RS in a measurement window corresponding to the prediction window.

In a fifth aspect of the solution, a method performed by a UE described herein may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter; and determining to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.

In a sixth aspect of the solution, a method performed by a BS described herein may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information CSI-RSs associated with at least one parameter; and receiving, from a UE, one or more CSI reports for a prediction window at least one CSI-RS in a measurement window corresponding to the prediction window.

It is to be understood that the summary section is not intended to identify key or essential features of embodiments of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure. Other features of the present disclosure will become easily comprehensible through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates an example of a wireless communications system that supports a solution for predicting CSI in accordance with aspects of the present disclosure.

FIG. 1B illustrates an example of sub-band full duplex (SBFD) scheme.

FIG. 1C illustrates an example showing frequency domain resources of CSI-RS in SBFD slot.

FIG. 1D illustrates an example of an uplink (UL) /a downlink (DL) configuration by tdd-UL-DL-ConfigCommon.

FIG. 1E illustrates an example of procedures of UE-side training based CSI prediction.

FIG. 1F illustrates an example of procedures of network (NW) -side training based CSI prediction.

FIG. 1G illustrates an example of a model and its measurement window and prediction window.

FIG. 2 illustrates example signalling procedures for predicting CSI in accordance with aspects of the present disclosure.

FIGS. 3-9 illustrate examples showing that how to predict CSI using different prediction models trained with different parameters and how to use different CSI-RSs in a measurement window in accordance with aspects of the present disclosure.

FIGS. 10-11 illustrate examples of devices for predicting CSI in accordance with aspects of the present disclosure.

FIGS. 12-13 illustrate examples of processors for predicting CSI in accordance with aspects of the present disclosure.

FIGS. 14-15 illustrate flowcharts of methods for predicting CSI in accordance with aspects of the present disclosure.

DETAILED DESCRIPTION

Principles of the present disclosure will now be described with reference to some embodiments. It is to be understood that these embodiments are described for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. The disclosure described herein may be implemented in various manners other than the ones described below.

In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.

References in the present disclosure to “one embodiment, ” “an example embodiment, ” “an embodiment, ” “some embodiments, ” and the like indicate that the embodiment (s) described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment (s) . Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

It shall be understood that although the terms “first” and “second” or the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used to distinguish one element from another element. For example, a first element could also be termed as a second element, and similarly, a second element could also be termed as a first element, without departing from the scope of embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.

The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting of example embodiments. As used herein, the singular forms “a” , “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” , “comprising” , “has” , “having” , “includes” and/or “including” , when used herein, specify the presence of stated features, elements, and/or components etc., but do not preclude the presence or addition of one or more other features, elements, components and/or combinations thereof.

As used herein, the term “communication network” refers to a network following any suitable communication standards, such as, 5G NR, long term evolution (LTE) , LTE-advanced (LTE-A) , wideband code division multiple access (WCDMA) , high-speed packet access (HSPA) , narrow band internet of things (NB-IoT) , and so on. Further, the communications between a terminal device and a network device in the communication network may be performed according to any suitable generation communication protocols, including but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the fifth generation (5G) communication protocols, and/or any other protocols either currently known or to be developed in the future. Embodiments of the present disclosure may be applied in various communication systems. Given the rapid development in communications, there will also be future type communication technologies and systems in which the present disclosure may be embodied. It should not be seen as limiting the scope of the present disclosure to only the aforementioned systems.

As used herein, the term “network device” generally refers to a node in a communication network via which a terminal device can access the communication network and receive services therefrom. The network device may refer to a base station (BS) or an access point (AP) , for example, a node B (NodeB or NB) , a radio access network (RAN) node, an evolved NodeB (eNodeB or eNB) , a NR NB (also referred to as a gNB) , a remote radio unit (RRU) , a radio header (RH) , an infrastructure device for a V2X (vehicle-to-everything) communication, a transmission and reception point (TRP) , a reception point (RP) , a remote radio head (RRH) , a relay, an integrated access and backhaul (IAB) node, a low power node such as a femto BS, a pico BS, and so forth, depending on the applied terminology and technology.

As used herein, the term “terminal device” generally refers to any end device that may be capable of wireless communications. By way of example rather than a limitation, a terminal device may also be referred to as a communication device, a user equipment (UE) , an end user device, a subscriber station (SS) , an unmanned aerial vehicle (UAV) , a portable subscriber station, a mobile station (MS) , or an access terminal (AT) . The terminal device may include, but is not limited to, a mobile phone, a cellular phone, a smart phone, a voice over IP (VoIP) phone, a wireless local loop phone, a tablet, a wearable terminal device, a personal digital assistant (PDA) , a portable computer, a desktop computer, an image capture terminal device such as a digital camera, a gaming terminal device, a music storage and playback appliance, a vehicle-mounted wireless terminal device, a wireless endpoint, a mobile station, laptop-embedded equipment (LEE) , laptop-mounted equipment (LME) , a USB dongle, a smart device, wireless customer-premises equipment (CPE) , an internet of things (loT) device, a watch or other wearable, a head-mounted display (HMD) , a vehicle, a drone, a medical device (for example, a remote surgery device) , an industrial device (for example, a robot and/or other wireless devices operating in an industrial and/or an automated processing chain contexts) , a consumer electronics device, a device operating on commercial and/or industrial wireless networks, and the like. In the following description, the terms: “terminal device, ” “communication device, ” “terminal, ” “user equipment” and “UE, ” may be used interchangeably.

Aspects of the present disclosure are described in the context of a wireless communications system.

FIG. 1A illustrates an example of a wireless communications system 100A that supports a solution for predicting CSI in accordance with aspects of the present disclosure. The wireless communications system 100 may include one or more network entities 102 (also referred to as network equipment (NE) , or a base station (BS) 102) , one or more UEs 104, a core network 106, and a packet data network 108. The wireless communications system 100 may support various radio access technologies. In some implementations, the wireless communications system 100 may be a 4G network, such as an LTE network or an LTE-advanced (LTE-A) network. In some other implementations, the wireless communications system 100 may be a 5G network, such as an NR network. In other implementations, the wireless communications system 100 may be a combination of a 4G network and a 5G network, or other suitable radio access technology including institute of electrical and electronics engineers (IEEE) 802.11 (Wi-Fi) , IEEE 802.16 (WiMAX) , IEEE 802.20. The wireless communications system 100 may support radio access technologies beyond 5G. Additionally, the wireless communications system 100 may support technologies, such as time division multiple access (TDMA) , frequency division multiple access (FDMA) , or code division multiple access (CDMA) , etc.

The one or more network entities 102 may be dispersed throughout a geographic region to form the wireless communications system 100. One or more of the network entities 102 described herein may be or include or may be referred to as a network node, a base station, a network element, a radio access network (RAN) , a base transceiver station, an access point, a NodeB, an eNodeB (eNB) , a next-generation NodeB (gNB) , or other suitable terminology. A network entity 102 and a UE 104 may communicate via a communication link 110, which may be a wireless or wired connection. For example, a network entity 102 and a UE 104 may perform wireless communication (e.g., receive signaling, transmit signaling) over a Uu interface.

A network entity 102 may provide a geographic coverage area 112 for which the network entity 102 may support services (e.g., voice, video, packet data, messaging, broadcast, etc. ) for one or more UEs 104 within the geographic coverage area 112. For example, a network entity 102 and a UE 104 may support wireless communication of signals related to services (e.g., voice, video, packet data, messaging, broadcast, etc. ) according to one or multiple radio access technologies. In some implementations, a network entity 102 may be moveable, for example, a satellite associated with a non-terrestrial network. In some implementations, different geographic coverage areas 112 associated with the same or different radio access technologies may overlap, but the different geographic coverage areas 112 may be associated with different network entities 102. Information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

The one or more UEs 104 may be dispersed throughout a geographic region of the wireless communications system 100. A UE 104 may include or may be referred to as a mobile device, a wireless device, a remote device, a remote unit, a handheld device, or a subscriber device, or some other suitable terminology. In some implementations, the UE 104 may be referred to as a unit, a station, a terminal, or a client, among other examples. Additionally, or alternatively, the UE 104 may be referred to as an internet-of-things (IoT) device, an internet-of-everything (IoE) device, or machine-type communication (MTC) device, among other examples. In some implementations, a UE 104 may be stationary in the wireless communications system 100. In some other implementations, a UE 104 may be mobile in the wireless communications system 100.

The one or more UEs 104 may be devices in different forms or having different capabilities. Some examples of UEs 104 are illustrated in FIG. 1A. A UE 104 may be capable of communicating with various types of devices, such as the network entities 102, other UEs 104, or network equipment (e.g., the core network 106, the packet data network 108, a relay device, an integrated access and backhaul (IAB) node, or another network equipment) , as shown in FIG. 1. Additionally, or alternatively, a UE 104 may support communication with other network entities 102 or UEs 104, which may act as relays in the wireless communications system 100.

A UE 104 may also be able to support wireless communication directly with other UEs 104 over a communication link 114. For example, a UE 104 may support wireless communication directly with another UE 104 over a device-to-device (D2D) communication link. In some implementations, such as vehicle-to-vehicle (V2V) deployments, vehicle-to-everything (V2X) deployments, or cellular-V2X deployments, the communication link 114 may be referred to as a sidelink. For example, a UE 104 may support wireless communication directly with another UE 104 over a PC5 interface.

A network entity 102 may support communications with the core network 106, or with another network entity 102, or both. For example, a network entity 102 may interface with the core network 106 through one or more backhaul links 116 (e.g., via an S1, N2, N2, or another network interface) . The network entities 102 may communicate with each other over the backhaul links 116 (e.g., via an X2, Xn, or another network interface) . In some implementations, the network entities 102 may communicate with each other directly (e.g., between the network entities 102) . In some other implementations, the network entities 102 may communicate with each other or indirectly (e.g., via the core network 106) . In some implementations, one or more network entities 102 may include subcomponents, such as an access network entity, which may be an example of an access node controller (ANC) . An ANC may communicate with the one or more UEs 104 through one or more other access network transmission entities, which may be referred to as a radio heads, smart radio heads, or transmission-reception points (TRPs) .

In some implementations, a network entity 102 may be configured in a disaggregated architecture, which may be configured to utilize a protocol stack physically or logically distributed among two or more network entities 102, such as an integrated access backhaul (IAB) network, an open radio access network (O-RAN) (e.g., a network configuration sponsored by the O-RAN Alliance) , or a virtualized RAN (vRAN) (e.g., a cloud RAN (C-RAN) ) . For example, a network entity 102 may include one or more of a CU, a DU, a radio unit (RU) , a RAN intelligent controller (RIC) (e.g., a near-real time RIC (Near-RT RIC) , a non-real time RIC (Non-RT RIC) ) , a service management and orchestration (SMO) system, or any combination thereof.

An RU may also be referred to as a radio head, a smart radio head, a remote radio head (RRH) , a remote radio unit (RRU) , or a transmission reception point (TRP) . One or more components of the network entities 102 in a disaggregated RAN architecture may be co-located, or one or more components of the network entities 102 may be located in distributed locations (e.g., separate physical locations) . In some implementations, one or more network entities 102 of a disaggregated RAN architecture may be implemented as virtual units (e.g., a virtual CU (VCU) , a virtual DU (VDU) , a virtual RU (VRU) ) .

Split of functionality between a CU, a DU, and an RU may be flexible and may support different functionalities depending upon which functions (e.g., network layer functions, protocol layer functions, baseband functions, radio frequency functions, and any combinations thereof) are performed at a CU, a DU, or an RU. For example, a functional split of a protocol stack may be employed between a CU and a DU such that the CU may support one or more layers of the protocol stack and the DU may support one or more different layers of the protocol stack. In some implementations, the CU may host upper protocol layer (e.g., a layer 3 (L3) , a layer 2 (L2) ) functionality and signaling (e.g., radio resource control (RRC) , service data adaption protocol (SDAP) , packet data convergence protocol (PDCP) ) . The CU may be connected to one or more DUs or RUs, and the one or more DUs or RUs may host lower protocol layers, such as a layer 1 (L1) (e.g., physical (PHY) layer) or an L2 (e.g., radio link control (RLC) layer, medium access control (MAC) layer) functionality and signaling, and may each be at least partially controlled by the CU 160.

Additionally, or alternatively, a functional split of the protocol stack may be employed between a DU and an RU such that the DU may support one or more layers of the protocol stack and the RU may support one or more different layers of the protocol stack. The DU may support one or multiple different cells (e.g., via one or more RUs) . In some implementations, a functional split between a CU and a DU, or between a DU and an RU may be within a protocol layer (e.g., some functions for a protocol layer may be performed by one of a CU, a DU, or an RU, while other functions of the protocol layer are performed by a different one of the CU, the DU, or the RU) .

A CU may be functionally split further into CU control plane (CU-CP) and CU user plane (CU-UP) functions. A CU may be connected to one or more DUs via a midhaul communication link (e.g., F1, F1-c, F1-u) , and a DU may be connected to one or more RUs via a fronthaul communication link (e.g., open fronthaul (FH) interface) . In some implementations, a midhaul communication link or a fronthaul communication link may be implemented in accordance with an interface (e.g., a channel) between layers of a protocol stack supported by respective network entities 102 that are in communication via such communication links.

The core network 106 may support user authentication, access authorization, tracking, connectivity, and other access, routing, or mobility functions. The core network 106 may be an evolved packet core (EPC) , or a 5G core (5GC) , which may include a control plane entity that manages access and mobility (e.g., a mobility management entity (MME) , an access and mobility management functions (AMF) ) and a user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW) , a packet data network (PDN) gateway (P-GW) , or a user plane function (UPF) ) . In some implementations, the control plane entity may manage non-access stratum (NAS) functions, such as mobility, authentication, and bearer management (e.g., data bearers, signal bearers, etc. ) for the one or more UEs 104 served by the one or more network entities 102 associated with the core network 106.

The core network 106 may communicate with the packet data network 108 over one or more backhaul links 116 (e.g., via an S1, N2, N2, or another network interface) . The packet data network 108 may include an application server 118. In some implementations, one or more UEs 104 may communicate with the application server 118. A UE 104 may establish a session (e.g., a protocol data unit (PDU) session, or the like) with the core network 106 via a network entity 102. The core network 106 may route traffic (e.g., control information, data, and the like) between the UE 104 and the application server 118 using the established session (e.g., the established PDU session) . The PDU session may be an example of a logical connection between the UE 104 and the core network 106 (e.g., one or more network functions of the core network 106) .

In the wireless communications system 100A, the network entities 102 and the UEs 104 may use resources of the wireless communications system 100 (e.g., time resources (e.g., symbols, slots, subframes, frames, or the like) or frequency resources (e.g., subcarriers, carriers) ) to perform various operations (e.g., wireless communications) . In some implementations, the network entities 102 and the UEs 104 may support different resource structures. For example, the network entities 102 and the UEs 104 may support different frame structures. In some implementations, such as in 4G, the network entities 102 and the UEs 104 may support a single frame structure. In some other implementations, such as in 5G and among other suitable radio access technologies, the network entities 102 and the UEs 104 may support various frame structures (i.e., multiple frame structures) . The network entities 102 and the UEs 104 may support various frame structures based on one or more numerologies.

One or more numerologies may be supported in the wireless communications system 100A, and a numerology may include a subcarrier spacing and a cyclic prefix. A first numerology (e.g., μ=0) may be associated with a first subcarrier spacing (e.g., 15 kHz) and a normal cyclic prefix. In some implementations, the first numerology (e.g., μ=0) associated with the first subcarrier spacing (e.g., 15 kHz) may utilize one slot per subframe. A second numerology (e.g., μ=1) may be associated with a second subcarrier spacing (e.g., 30 kHz) and a normal cyclic prefix. A third numerology (e.g., μ=2) may be associated with a third subcarrier spacing (e.g., 60 kHz) and a normal cyclic prefix or an extended cyclic prefix. A fourth numerology (e.g., μ=3) may be associated with a fourth subcarrier spacing (e.g., 120 kHz) and a normal cyclic prefix. A fifth numerology (e.g., μ=4) may be associated with a fifth subcarrier spacing (e.g., 240 kHz) and a normal cyclic prefix.

A time interval of a resource (e.g., a communication resource) may be organized according to frames (also referred to as radio frames) . Each frame may have a duration, for example, a 10 millisecond (ms) duration. In some implementations, each frame may include multiple subframes. For example, each frame may include 10 subframes, and each subframe may have a duration, for example, a 1 ms duration. In some implementations, each frame may have the same duration. In some implementations, each subframe of a frame may have the same duration.

Additionally or alternatively, a time interval of a resource (e.g., a communication resource) may be organized according to slots. For example, a subframe may include a number (e.g., quantity) of slots. The number of slots in each subframe may also depend on the one or more numerologies supported in the wireless communications system 100. For instance, the first, second, third, fourth, and fifth numerologies (i.e., μ=0, μ=1, μ=2, μ=3, μ=4) associated with respective subcarrier spacings of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz may utilize a single slot per subframe, two slots per subframe, four slots per subframe, eight slots per subframe, and 16 slots per subframe, respectively. Each slot may include a number (e.g., quantity) of symbols (e.g., OFDM symbols) . In some implementations, the number (e.g., quantity) of slots for a subframe may depend on a numerology. For a normal cyclic prefix, a slot may include 14 symbols. For an extended cyclic prefix (e.g., applicable for 60 kHz subcarrier spacing) , a slot may include 12 symbols. The relationship between the number of symbols per slot, the number of slots per subframe, and the number of slots per frame for a normal cyclic prefix and an extended cyclic prefix may depend on a numerology. It should be understood that reference to a first numerology (e.g., μ=0) associated with a first subcarrier spacing (e.g., 15 kHz) may be used interchangeably between subframes and slots. In this disclosure, a time unit could be one or multiple frame, subframe, slot, symbol.

In the wireless communications system 100A, an electromagnetic (EM) spectrum may be split, based on frequency or wavelength, into various classes, frequency bands, frequency channels, etc. By way of example, the wireless communications system 100 may support one or multiple operating frequency bands, such as frequency range designations FR1 (410 MHz –7.125 GHz) , FR2 (24.25 GHz –52.6 GHz) , FR3 (7.125 GHz –24.25 GHz) , FR4 (52.6 GHz –114.25 GHz) , FR4a or FR4-1 (52.6 GHz –71 GHz) , and FR5 (114.25 GHz –300 GHz) . In some implementations, the network entities 102 and the UEs 104 may perform wireless communications over one or more of the operating frequency bands. In some implementations, FR1 may be used by the network entities 102 and the UEs 104, among other equipment or devices for cellular communications traffic (e.g., control information, data) . In some implementations, FR2 may be used by the network entities 102 and the UEs 104, among other equipment or devices for short-range, high data rate capabilities.

FR1 may be associated with one or multiple numerologies (e.g., at least three numerologies) . For example, FR1 may be associated with a first numerology (e.g., μ=0) , which includes 15 kHz subcarrier spacing; a second numerology (e.g., μ=1) , which includes 30 kHz subcarrier spacing; and a third numerology (e.g., μ=2) , which includes 60 kHz subcarrier spacing. FR2 may be associated with one or multiple numerologies (e.g., at least 2 numerologies) . For example, FR2 may be associated with a third numerology (e.g., μ=2) , which includes 60 kHz subcarrier spacing; and a fourth numerology (e.g., μ=3) , which includes 120 kHz subcarrier spacing.

FIG. 1B illustrates an example of sub-band full duplex (SBFD) scheme 100B. To realize the superior data rate and latency, 5G spectrum on higher frequency band is inevitable. How to overcome the coverage reduction on such carriers is a problem. In the 3rd generation partnership poject (3GPP) Release 18, it will probably introduce a new duplexing scheme that enables simultaneous use of downlink and uplink within a TDD carrier using non-overlapped frequency resource, which could be named as sub-band full duplex (SBFD) . The intention of this scheme is to extend the duration over which uplink transmission could occur for improved the uplink coverage and capacity. The simultaneous use of DL and UL is at gNB and not at UE side. As shown in FIG. 1B, slot #0 and slot #1 are SBFD slots. Slot #2 is a UL slot. A SBFD symbol/slot may mean that this symbol/slot can support simultaneous DL and UL transmissions. A symbol/slot being SBFD symbol/slot may mean that there could be at least two sub-bands with different transmission directions in this symbol, where one is DL transmission direction, and the other one is UL transmission direction, or a BS may simultaneously perform a downlink transmission and an uplink transmission in this symbol. It is to be noted that another name may be used to denote such symbol. In the context of the present disclosure, a non-SBFD symbol may refer to a DL, flexible, or UL symbol.

According to the background new radio (NR) resource allocation above, it is observed that a gNB may indicate one frequency domain resource in the bandwidth part (BWP) . Considering the frequency resource allocation for CSI-RS is configured continuous, and then there may be a case that the CSI-RS would overlapped with UL subband in some slot or symbol configured UL subband. In this case, following options may be considered. Option (1) is that two contiguous CSI-RS resources that are linked. Option (2) is that one CSI-RS resource. In option (2) , there may be two sub-options. Sub- option (2.1) is non-contiguous CSI-RS resource allocation, and option (2.2) is one contiguous CSI-RS resource allocation with non-contiguous CSI-RS resource derived by excluding frequency resources outside DL subband (s) .

No matter which option is selected, the same result may be obtained, the CSI-RS in SBFD symbol or slot is non-continuous and is not the same with the CSI-RS in DL symbol or slot. Further, the CSI-RS in SBFD symbol/slot and CSI-RS in DL symbol/slot may correspond to the same CSI-report or different CSI-reports. If they are in the same CSI report, separated CSI measurements may be derived based on the first and second CSI-RSs respectively, or the CSI report may be derived based on CSI-RS which is in SBFD symbols or non-SBFD symbols in different time instances.

FIG. 1C illustrates an example 100C showing frequency domain resources of CSI-RS in SBFD slot, as shown in a CSI-RS in the upper DL subband and a CSI-RS in the lower DL subband in slot #0. It could be seen that the CSI-RS in slot#0 is non-continuous and is not the same as the CSI-RS in slot#2 (DL slot) .

FIG. 1D illustrates an example 100D of an uplink (UL) /a downlink (DL) configuration by tdd-UL-DL-ConfigCommon. The time division duplex (TDD) slot format in 5G NR includes downlink symbols, uplink symbols and flexible symbols. The slot format may be determined by a cell common UL/DL configuration tdd-UL-DL-ConfigCommon, which is provided to the UE through system information. The tdd-UL-DL-ConfigCommon includes configurations of a transmission pattern 1, which includes the following: (1) a slot configuration period of P msec by dl-ul-transmission-periodicity; (2) a number of downlink slots d_slots by nrofDownlinkSlots; (3) a number of downlink symbols d_sym by nrofDownlinkSymbols; (4) a number of uplink slots u_slots by nrofUplinkSlots; and (5) a number of uplink symbols u_sym by nrofUplinkSymbol.

A slot configuration period of P msec includes S slots. From the S slots, a first d_slots slots includes only downlink symbols and a last u_slots includes only uplink symbols. The d_sym symbols after the d_slots slots are downlink symbols. The u_sym symbols before the last u_slots are uplink symbols. The remaining (S-d_slot-u_slot) *N_sym -d_sym-u_sym are flexible symbols, where N_sym is the number of symbols in a slot. Here “flexible” means that the UE cannot make any assumptions on the transmission direction. Downlink control signal (i.e., PDCCH) should be monitored in the flexible symbols and if a scheduling message is found, the UE should transmit/receive accordingly. In addition, the flexible symbols also served as a guard period for the UEs to switch from DL reception to UL transmission.

As shown in FIG. 1D, the example of the slot format 100D is for 10 slots with 5ms dl-ul-TransmissionPeiodicity. nrofDownlinkSlots = 6 indicates that the first 6 slots are DL slots (120 to 122) . nrofUplinkSlots = 3, indicates that the last 3 slots are UL slots (126 to 128) . nrofDownlinkSymbols = 7 and nrofUplinkSymbols = 3 indicate that there is a slot with 7 DL symbols, 3 UL symbols and 4 flexible symbols between the DL slots and UL slots. Here, the 4 flexible symbols (124) are mostly served as guard period for DL to UL switching.

The UE might be further provided with a UE specific configuration RRC signalling tdd-UL-DL-ConfigDedicated, which indicates the flexible symbols configured in tdd-UL-DL-ConfigDedicated to be either UL or DL. It should be noted that the transmission direction of the non-flexible symbols configured in tdd-UL-DL-ConfigCommon cannot be override by tdd-UL-DL-ConfigDedicated.

Furthermore, the transmission directions of the flexible symbols may be indicated by a dynamically signalling. Such signalling carries a slot format indicator (SFI) and will be received by a configured group of one or more devices. The SFI could indicate the flexible symbol into DL or UL symbol, and it is to be noted that the transmission direction of the non-flexible symbols configured in tdd-UL-DL-ConfigCommon and tdd-UL-DL-ConfigDedicated cannot be override by SFI.

If UE is configured to receive CSI-RS in some resource, the CSI-RS would be cancelled in following cases (1) to (11) . Case (1) : for operation on a single carrier in unpaired spectrum, if a UE is configured by higher layers to receive a PDCCH, or a PDSCH, or a CSI-RS, or a DL PRS in a set of symbols of a slot, the UE receives the PDCCH, the PDSCH, the CSI-RS, or the DL PRS if the UE does not detect a DCI format that indicates to the UE to transmit a PUSCH, a PUCCH, a PRACH, or a SRS in at least one symbol of the set of symbols of the slot; otherwise, the UE does not receive the PDCCH, or the PDSCH, or the CSI-RS, or the DL PRS in the set of symbols of the slot.

Case (2) : for a UE operation with shared spectrum channel access in FR1, or in FR2-2 when the UE is provided ChannelAccessMode2 = 'enabled' , if the UE is provided csi-RS-ValidationWithDCI, is not provided CO-DurationsPerCell, and is not provided SlotFormatCombinationsPerCell, and if the UE is configured by higher layers to receive a CSI-RS in a set of symbols of a slot, the UE cancels the CSI-RS reception in the set of symbols of the slot if the UE does not detect a DCI format indicating an aperiodic CSI-RS reception or scheduling a PDSCH reception in the set of symbols of the slot.

Case (3) : for a set of symbols of a slot that are indicated to a UE as uplink by tdd-UL-DL-ConfigurationCommon, or tdd-UL-DL-ConfigurationDedicated, the UE does not receive PDCCH, PDSCH, or CSI-RS when the PDCCH, PDSCH, or CSI-RS overlaps, even partially, with the set of symbols of the slot.

Case (4) : for a set of symbols of a slot corresponding to a valid PRACH occasion and N_gap symbols before the valid PRACH occasion, as described in clause 8.1, the UE does not receive PDCCH, PDSCH, or CSI-RS in the slot if a reception would overlap with any symbol from the set of symbols. The UE does not expect the set of symbols of the slot to be indicated as downlink by tdd-UL-DL-ConfigurationCommon or tdd-UL-DL-ConfigurationDedicated.

Case (5) : if the reference cell and another cell among the cells configured with directionalCollisionHandling-r16 operate in different frequency bands, the UE assumes symbol as flexible, is not required to receive higher layer configured PDCCH, PDSCH, or CSI-RS and not expected to transmit higher layer configured SRS, PUCCH, PUSCH, or PRACH, when tdd-UL-DL-ConfigurationCommon or tdd-UL-DL-ConfigurationDedicated indicates symbol as downlink or uplink on another cell and as uplink or downlink for the reference cell, respectively. The UE is not required to receive a higher layer configured PDCCH, PDSCH, or CSI-RS on flexible symbols on the reference cell in a set of symbols, if the UE detects a DCI format scheduling a transmission on one or more symbols in the set of symbols on another cell.

Case (6) : the UE does not receive a PDCCH, PDSCH or CSI-RS that is configured by higher layers on a set of symbols on another cell if at least one symbol from the set of symbols is indicated as uplink by tdd-UL-DL-ConfigurationCommon or tdd-UL-DL-ConfigurationDedicated or is a symbol corresponding to a SRS, PUCCH, PUSCH, or PRACH transmission that is configured by higher layers on the reference cell.

Case (7) : if the UE is configured by higher layers to receive PDSCH or CSI-RS in the set of symbols of the slot, the UE receives the PDSCH or the CSI-RS in the set of symbols of the slot only if an SFI-index field value in DCI format 2_0 indicates the set of symbols of the slot as downlink and, if applicable, the set of symbols is within remaining channel occupancy duration.

Case (8) : if a UE is configured by higher layers to receive a CSI-RS or a PDSCH in a set of symbols of a slot and the UE detects a DCI format 2_0 with a slot format value other than 255 that indicates a slot format with a subset of symbols from the set of symbols as uplink or flexible, or the UE detects a DCI format indicating to the UE to transmit PUSCH, PUCCH, SRS, or PRACH in at least one symbol in the set of the symbols, the UE cancels the CSI-RS reception in the set of symbols of the slot or cancels the PDSCH reception in the slot.

Case (9) : for a UE operation with shared spectrum channel access in FR1, or in FR2-2 when the UE is provided ChannelAccessMode2 = 'enabled', if a UE is configured by higher layers to receive a CSI-RS and the UE is provided CO-DurationsPerCell, for a set of symbols of a slot that are indicated as downlink or flexible by tdd-UL-DL-ConfigurationCommon or tdd-UL-DL-ConfigurationDedicated, or when tdd-UL-DL-ConfigurationCommon and tdd-UL-DL-ConfigurationDedicated are not provided, the UE cancels the CSI-RS reception in the set of symbols of the slot that are not within the remaining channel occupancy duration.

Case (10) : if a UE is configured by higher layers to receive a CSI-RS or detects a DCI format 0_1 indicating to the UE to receive a CSI-RS in one or more RB sets and a set of symbols of a slot, and the UE detects a DCI format 2_0 with bitmap indicating that any RB set from the one or more RB sets is not available for reception, the UE cancels the CSI-RS reception in the set of symbols of the slot.

Case (11) : for a set of symbols of a slot that are indicated as flexible by tdd-UL-DL-ConfigurationCommon, and tdd-UL-DL-ConfigurationDedicated if provided, or when tdd-UL-DL-ConfigurationCommon, and tdd-UL-DL-ConfigurationDedicated are not provided to the UE, and if the UE does not detect a DCI format 2_0 providing a slot format for the slot. If the UE is configured by higher layers to receive CSI-RS in the set of symbols of the slot, the UE does not receive the CSI-RS in the set of symbols of the slot, except when UE is provided CO-DurationsPerCell and the set of symbols of the slot are within the remaining channel occupancy duration.

FIG. 1E illustrates an example of procedures 100E of UE-side training based CSI prediction. FIG. 1F illustrates an example of procedures 100F of network (NW) -side training based CSI prediction. In procedures 100E, UE 130 may perform some CSI-RS related data collection and then a model could be trained by UE 130 or gNB 132, and then UE could predict the CSI report in the future based on the model the CSI report in the future. In this way, the gNB does not need send CSI-RS in the future, which would increase the system capacity. Similarly, the corresponding procedures 100F of CSI prediction could be shown in the following, respectively.

For model training, the collection of CSIs may be categorized into the collection of historical CSIs and the collection of future CSIs. For example, a series of consecutive samples using sliding manner may be described by slot ID like [0, 5, 10, 15, 20, 25->28] , [5, 10, 15, 20, 25, 30->33] , [10, 15, 20, 25, 30, 35->38] …, and these samples may be generated from CSI-RS-Resource-1 with slot ID of [0, 5, 10, 15, 20, 25, 30, 35, …] with 5 slots spacing and CSI-RS-Resource-2 with slot ID of [28, 33, 38, …] with 5 slots spacing and 3 slots shift from the first ones. A series of consecutive samples using non-sliding manner can be described by slot ID like [0, 5, 10, 15, 20, 25->28] , [30, 35, 40, 45, 50, 55->58] , [60, 65, 70, 75, 80, 85->88] …, and these samples may be generated from CSI-RS-Resource-1 with slot ID of [0, 5, 10, 15, 20, 25, 30, 35, …] with 5 slots spacing and CSI-RS-Resource-2 with slot ID of [28, 58, 88, …] with 30 slot spacing. The applicable conditions of AI-based CSI prediction may be highly correlated with the process of data collection.

FIG. 1G illustrates an example of a model 100G and its measurement window and prediction window. Model 100G is trained and used for CSI prediction. Model 100G is associated with one or more of the following parameters, such as the number of CSI-RS instance in the measurement window 190, and the interval between the CSI-RS in the measurement window 190, and the interval between the measurement window 190 and the prediction window 192, and the number of CSI-RS instance in the prediction window 192 and the interval between the CSI-RS in the prediction window 192.

Now in the data collection procedure, the CSI-RS in the measurement window has fix interval and fix number, and the model is trained based on these simples associated with one or more of the parameters. But when the model is used for prediction, there may be a case that the CSI-RS pattern (including the CSI-RS position or interval or number) in the measurement window would be different with the data collocation procedure considering some CSI-RS may be cancelled in some scenarios mentioned or part of CSI-RSs are in SBFD symbol and the other in Non-SBFD symbol. As such, the prediction is not reasonable, and the resource used to report the CSI may cause resource wasting and the CSI report for the prediction position could not be got timely.

That is, even if at least one models are trained, and each model is trained based on CSI-RS associated with at least one parameter, if parameter of the CSI-RS in a certain measurement window is not the same with the associated parameter of any model, then how to the prediction using the CSI-RS in the certain measurement window should be discussed. The at least one parameter may include one or multiple of the following: the number of CSI-RS, the interval of the CSI-RS, the symbol for CSI-RS is configured with SBFD or not, the CSI-RS pattern in the measurement window and so on.

By implementing the embodiments of the present disclosure, a solution of how to predict CSI using different prediction models trained with different parameters and how to use different CSI-RSs in a measurement window can be provided, and thus the accuracy and efficiency of the prediction results can be improved.

FIG. 2 illustrates example signalling procedures 200 for predicting CSI in accordance with aspects of the present disclosure. UE 104 determines (206) at least one prediction model. Each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter. Similarly, BS 102 determines (208) at least one prediction model, and each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter. If the at least one prediction model is determined (for example, trained with CSI-RS samples and CSI report samples) by BS 102, BS 102 may transmit the at least one prediction model to UE 104. In some example embodiments, each prediction model may be associated with at least one parameter. The at least one parameter may be used to determining the prediction model.

BS 102 may transmit (210) one or more CSI-RSs 212 to UE 104. UE 104 may receive (214) the one or more CSI-RSs 212 from the BS 102. UE 104 determines (216) to predict, using one or more of the at least one prediction model, one or more CSI reports 220 for a prediction window based on at least one CSI-RS 212 in a measurement window corresponding to the prediction window. UE 104 transmits (218) the one or more CSI reports 220 to BS 102. BS 102 receives (222) the one or more CSI reports 220 from UE 104. In some example embodiments, BS 102 may predict a CSI report for some position in a prediction window.

In some example embodiments, the at least one parameter may comprise a number of CSI-RSs in a measurement window. The at least one parameter may comprise an interval of CSI-RSs in a measurement window. The at least one parameter may comprise a symbol for a CSI-RS being configured with UL subband or not (can be referred to as a SBFD symbol or a DL symbol, respectively) .

The at least one parameter may comprise a CSI-RS pattern in a measurement window. The CSI-RS pattern may indicate at least one of a CSI-RS position, at least one interval of CSI-RSs, or a number of CSI-RSs in the measurement window. Each of the at least one prediction model may be determined based on CSI-RSs associated with at least one parameter. This may mean that each predication model may be associated with at least one parameter, or the at least one parameter may be used to determine the predication model.

In some example embodiments, if one or more CSI-RSs are cancelled in the measurement window, the at least one CSI-RS used for predicting the CSI report may comprise at least one remaining CSI-RS in the measurement window, or the at least one remaining CSI-RS and at least one supplementary CSI-RS. Here, a supplementary CSI-RS may be determined based on the remaining CSI-RS.

For example, a CSI-RS among the one or more CSI-RSs may be cancelled if the CSI-RS overlaps with UL symbols. The CSI-RS may be cancelled if the CSI-RS is in a symbol or slot not configured with UL subband, and a prediction model associated with symbol or slot configured with UL subband is used. The CSI-RS may be cancelled if one or more CSI-RSs may be in a symbol or slot configured with UL subband and a prediction model associated with symbol or slots not configured with UL subband is used.

For example, the CSI-RS may be cancelled by the cases (1) - (11) mentioned before, or the CSI-RS in DL symbol may be cancelled if model for SBFD symbol/slot is used, or the CSI-RS in SBFD symbol/slot may be cancelled if model for DL symbol/slot is used. UE 104 may determine how to predict the CSI for a prediction window based on the remaining CSI-RS after a cancellation of some CSI-RSs in a certain measurement window corresponding to the prediction window.

Referring to FIG. 3, reference numeral 330 represents a DL symbol, and reference numeral 332 represents a SBFD symbol. It is to be noted that reference numerals 330 and 332 also apply throughout FIG. 3 to FIG. 9. Assuming the trained model (s) is/are associated with the CSI-RS in DL symbol (non-SBFD symbol) , then the in the measurement window 302, the CSI-RS overlapped with SBFD symbol should be canceled (such as CSI-RSs 310 and 312) . Four CSI-RS (such as CSI-RSs 306, 308, 314 and 316) are used to perform prediction (such as one or more of CSI-RSs 320, 322, 324 and 326) .

Referring back to FIG. 2, each of the at least one prediction model may be determined based on a combination of CSI-RSs associated with symbols or slots configured with UL subband and CSI-RSs associated with symbols or slots not configured with UL subband, CSI-RSs associated with symbols or slots configured with UL subband, or CSI-RSs associated with symbols or slots not configured with UL subband.

Referring to FIG. 4, for example, UE 104 may determine how to predict the CSI for a prediction window based on the remaining CSI-RS and supplement CSI-RS. A supplementary CSI-RS may be determined based on the remaining CSI-RS by replacing a cancelled CSI-RS with a remaining CSI-RS in the measurement window. For example, the supplement CSI-RS may be determined by using the remaining CSI-RS to replace the cancelled CSI-RS, for example, using the remaining CSI-RS before or after a cancelled CSI-RS and close to the cancelled CSI-RS to replace the cancelled CSI-RS. As shown in FIG. 4, CSI-RS 406 may be replaced by the CSI-RS 402, and CSI-RS 408 may be replaced by the CSI-RS 404. Then 6 CSI-RS may be used to perform the prediction.

Referring to FIG. 2, if all CSI-RSs are in the symbols or slots configured with UL subband in the measurement window, a prediction model of the at least one prediction model determined based on the CSI-RSs associated with symbols or slots configured with UL subband may be used for prediction. If all CSI-RSs are in symbols or slots not configured with UL subband in the measurement window, a prediction model of the at least one prediction model determined based on the CSI-RSs associated with symbols or slots not configured with UL subband may be used for prediction.

For example, UE 104 may use the model trained based on CSI-RS associated with parameters the same with the parameters of the CSI-RS in a certain measurement window. UE 104 does not expect the corresponding parameter of the CSI-RS in the measurement window is not the same as any parameters associated with any model.

Referring to FIGS. 5A to 5D, if one model 500A is trained by the CSI-RS associated with SBFD symbol/slot (such as symbols 502, 504, 506, 508, 510 and 512) , and the other model 500B is trained by the CSI-RS associated with DL symbol/slot (such as symbols 514, 516, 518, 520, 522 and 524) , then for a measurement window, the CSI-RSs used for the prediction may be all in DL symbol/slot (as shown in CSI report 2 in FIG. 500C and FIG. 500D) or in SBFD symbol/slot (as shown in CSI report 1 in FIG. 500C and FIG. 500D) .

Referring back to FIG. 2, if none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, UE 104 may not predict the CSI report. If a number of corresponding parameters of CSI-RSs in a measurement window with different parameters exceeds a threshold, UE 104 may not predict the CSI report.

In some example embodiments, if UE 104 does not predict the CSI report, UE 104 may cancel the CSI report for the prediction window. UE 104 may transmit the CSI report for the CSI-RSs in the measurement window as legacy. UE 104 may detect scheduling information from a base station for scheduling the CSI report for the prediction window. The CSI report may be determined without using the at least one prediction model.

Referring to FIG. 6, for example, multiple models (or model parameters) may be trained by CSI-RSs associated with multiple slot format combinations, such as models 1-4. According to the slot format combination of the CSI-RSs in a certain measurement window to choose which model (s) will be used predict. UE 104 expect that the slot format combination of CSI-RSs in a certain measurement window is the same as at least one of the trained model.

In some example embodiments, if a number of CSI-RSs in the measurement window is the same with a number of CSI-RSs used for determining the selected prediction model, or a symbol or slot format associated with the CSI-RSs in the measurement window is the same with a slot format associated with the CSI-RSs used for determining the selected prediction model, UE 104 may predict the CSI report based on a selected prediction model of the at least one prediction model. For example, UE 104 may select one or more models out of models 1-4.

Referring back to FIG. 2, if the corresponding parameter of the CSI-RS in a certain measurement window is not same as any parameters associated with any model. UE may not predict the CSI for the prediction window in this case or if the number of CSI-RSs with the different parameters exceeds a threshold. The threshold may be predefined or associated with the model parameter. In such cases, UE 104 may cancel the report carrying the CSI for the prediction window. UE 104 may report the CSI for the CSI-RS in the measurement window in the report in a traditional manner. UE 104 may wait for BS 102 to schedule report the CSI-RS for the prediction window.

In some example embodiments, if a number of CSI-RSs in symbols or slots configured with UL subband in the measurement window is greater than a number of CSI-RSs in symbols or slots not configured with UL subband in the measurement window, or if first CSI-RS in symbols or slots configured with UL subband in the measurement window, UE 104 may predict the CSI report based on a prediction model for symbols or slots configured with UL subband of the at least one prediction model.

For example, the models may be determined based on the real parameter of the CSI-RS in the certain measurement window, and the number of the CSI-RS in the certain measurement window may be the same as the number of CSI-RS trained the one model. The slot format of the CSI-RS in the certain measurement window may be the same as the slot format of CSI-RS trained the one model. If more CSI-RS instance is in SBFD symbol or the first instance is in SBFD symbol, then model for SBFD may be used.

In some example embodiments, if a number of CSI-RSs in symbols or slots configured with UL subband in the measurement window is the same with a number of CSI-RSs in symbols or slots not configured with UL subband in the measurement window, UE 104 may predict the CSI report based on a predefined or indicated prediction model. If the same instance number in SBFD symbol and non-SBFD Symbol, model for SBFD or model for non-SBFD may be used according to predefined or indication.

Referring to FIG. 7, in some example embodiments, if a prediction model of the at least one prediction model may be determined based on CSI-RSs associated with parameters X and Y, where X is a minimum number of CSI-RS instances, and Y is a maximum interval of the CSI-RS instances. If X for a first prediction model is smaller than or equal to a number of CSI-RSs in the measurement window, and/or if Y for the first prediction model is greater than or equal to an interval of CSI-RSs in the measurement window, UE 104 may predict the CSI report based on the first prediction model, and UE 104 may determine a prediction model of the at least one prediction model based on parameters X and Y.

For example, assuming the parameter includes X and Y and assuming the number of CSI-RS in a certain measurement window is X1, then the model with X smaller than or equal to X1 may be selected. Assuming maximum interval of the CSI-RS instance in the certain measurement window is Y1, then the model with Y lager than or equal to Y1 may be selected. If multiple models meet the requirement, then UE 104 may select a model with the same pattern, a smaller interval, or a maximum CSI-RS instance.

Referring back to FIG. 2, if the selected models are more than one, UE 104 may select one of prediction models to predict the CSI report. The selected prediction model may be associated with the same CSI-RS patterns as CSI-RS patterns in the measurement window; the same interval of CSI-RSs as an interval of CSI-RSs in the measurement window; or the same number of CSI-RSs as a number of CSI-RSs in the measurement window.

In some example embodiments, UE 10 may predict the CSI report based on a prediction model which is predefined, preconfigured or indicated by a base station. The used model may be predefined in a 3GPP specification or pre-configured or indicated by a base station.

In some example embodiments, UE 104 may predict a plurality of CSI reports (such as for each position) based on a plurality of prediction models among the at least one prediction model, and the plurality of prediction models are determined based on at least one parameter which is the same as at least one parameter in a measurement window. UE 104 may predict the plurality of CSI reports based on the at least one prediction model. UE 104 may transmit, to BS 102, the plurality of CSI reports. UE 104 may transmit, to BS 102, a CSI report determined based on an average of the plurality of CSI reports.

For example, UE 104 may predict multiple CSI for the prediction window based on multiple models among the at least one models. The multiple models may be all the models, or the models among the multiple models having at least one parameter same as the certain measurement window. UE 104 may report multiple CSI corresponding to the predicted CSI based on the multiple models. In some example, one CSI is reported based on an avenge of the multiple predicted CSI.

Referring to FIG. 8, in some example embodiments, UE 104 may predict a first CSI report based on a prediction model associated with symbols or slots configured with UL subband. UE 104 may predict a second CSI report based on a prediction model associated with symbols or slots not configured with UL subband. UE 104 may transmit, to BS 102, the first CSI report and the second CSI report.

For example, UE 104 may predict multiple CSI for the prediction window based on multiple models among the at least one models. The multiple models may be all the models, or the models among the multiple models having at least one parameter same as the certain measurement window. UE 104 may report multiple CSI corresponding to the predicted CSI based on the multiple models. UE 104 may report one CSI based on an avenge of the multiple prediction CSI. In some example embodiments, UE 104 may report two prediction based on SBFD model 802 and non-SBFD model 804.

Referring to FIG. 9, in some example embodiments, if none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, UE 104 may determine an extended measurement window based on extending the measurement window by one or more time units. UE 104 may determine to predict the CSI report based on the one or more prediction models until one or more parameters of CSI-RSs in the extended measurement window are the same as one or more parameters associated with one or more prediction models of the at least one prediction model.

For example, UE 104 may enlarge a measurement window 902 one time unit by one time unit, to until UE 104 finds that the valid CSI-RSs 920 and 922 meets one trained model in the enlarged measurement window 908. Then UE 104 may use this model to predict the CSI in the corresponding prediction window 910 which may be moved from the original prediction window 904.

In some example embodiments, the parameter associated with the at least one CSI-RS in the measurement window may be the same as parameters used for determining one or more prediction model among the at least one prediction model.

In some example embodiments, BS 102 may transmit, to UE 104, an indication indicative of using which prediction models of the at least one prediction model to predict the CSI report.

In some example embodiments, if none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, or if a number of corresponding parameters of CSI-RSs in a measurement window with different parameters exceeds a threshold, BS 104 may not receive the CSI report. BS 102 may receive the CSI report for the CSI-RSs in the measurement window. BS 102 may transmit scheduling information for scheduling the CSI report for the prediction window. The CSI report may be determined without using the at least one prediction model.

In some example embodiments, BS 102 may receive a plurality of CSI reports (such as for each position) based on a plurality of prediction models among the at least one prediction model. The plurality of prediction models may be determined based on at least one parameter which is the same as at least one parameter in a measurement window. BS 102 may receive a plurality of CSI reports based on the at least one prediction model.

FIG. 10 illustrates an example of a device 1000 that supports the solution for predicting CSI in accordance with aspects of the present disclosure. The device 1000 may be an example of a network entity 102 as described herein. The device 1000 may support wireless communication with one or more network entities 102, UEs 104, or any combination thereof. The device 1000 may include components for bi-directional communications including components for transmitting and receiving communications, such as a processor 1002, a memory 1004, a transceiver 1006, and, optionally, an I/O controller 1008. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 1002, the memory 1004, the transceiver 1006, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. For example, the processor 1002, the memory 1004, the transceiver 1006, or various combinations or components thereof may support a method for performing one or more of the operations described herein.

In some implementations, the processor 1002, the memory 1004, the transceiver 1006, or various combinations or components thereof may be implemented in hardware (e.g., in communications management circuitry) . The hardware may include a processor, a digital signal processor (DSP) , an application-specific integrated circuit (ASIC) , a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, discrete hardware components, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure. In some implementations, the processor 1002 and the memory 1004 coupled with the processor 1002 may be configured to perform one or more of the functions described herein (e.g., executing, by the processor 1002, instructions stored in the memory 1004) .

For example, the processor 1002 may support wireless communication at the device 1000 in accordance with examples as disclosed herein. The processor 1002 may be configured to operable to support means for predicting CSI.

The processor 1002 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof) . In some implementations, the processor 1002 may be configured to operate a memory array using a memory controller. In some other implementations, a memory controller may be integrated into the processor 1002. The processor 1002 may be configured to execute computer-readable instructions stored in a memory (e.g., the memory 1004) to cause the device 1000 to perform various functions of the present disclosure.

The memory 1004 may include random access memory (RAM) and read-only memory (ROM) . The memory 1004 may store computer-readable, computer-executable code including instructions that, when executed by the processor 1002 cause the device 1000 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some implementations, the code may not be directly executable by the processor 1002 but may cause a computer (e.g., when compiled and executed) to perform functions described herein. In some implementations, the memory 1004 may include, among other things, a basic I/O system (BIOS) which may control basic hardware or software operation such as the interaction with peripheral components or devices.

The I/O controller 1008 may manage input and output signals for the device 1000. The I/O controller 1008 may also manage peripherals not integrated into the device M02. In some implementations, the I/O controller 1008 may represent a physical connection or port to an external peripheral. In some implementations, the I/O controller 1008 may utilize an operating system such as or another known operating system. In some implementations, the I/O controller 1008 may be implemented as part of a processor, such as the processor 1006. In some implementations, a user may interact with the device 1000 via the I/O controller 1008 or via hardware components controlled by the I/O controller 1008.

In some implementations, the device 1000 may include a single antenna 1010. However, in some other implementations, the device 1000 may have more than one antenna 1010 (i.e., multiple antennas) , including multiple antenna panels or antenna arrays, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. The transceiver 1006 may communicate bi-directionally, via the one or more antennas 1010, wired, or wireless links as described herein. For example, the transceiver 1006 may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The transceiver 1006 may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas 1010 for transmission, and to demodulate packets received from the one or more antennas 1010. The transceiver 1006 may include one or more transmit chains, one or more receive chains, or a combination thereof.

A transmit chain may be configured to generate and transmit signals (e.g., control information, data, packets) . The transmit chain may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM) , frequency modulation (FM) , or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM) . The transmit chain may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmit chain may also include one or more antennas 1010 for transmitting the amplified signal into the air or wireless medium.

A receive chain may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receive chain may include one or more antennas1010 for receive the signal over the air or wireless medium. The receive chain may include at least one amplifier (e.g., a low-noise amplifier (LNA) ) configured to amplify the received signal. The receive chain may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receive chain may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

FIG. 11 illustrates an example of a device 1100 that supports the solution for predicting CSI in accordance with aspects of the present disclosure. The device 1100 may be an example of a UE 104 as described herein. The device 1100 may support wireless communication with one or more network entities 102, UEs 104, or any combination thereof. The device 1100 may include components for bi-directional communications including components for transmitting and receiving communications, such as a processor 1102, a memory 1104, a transceiver 1106, and, optionally, an I/O controller 1108. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 1102, the memory 1104, the transceiver 1106, or various combinations thereof or various components thereof may be examples of means for performing various aspects of the present disclosure as described herein. For example, the processor 1102, the memory 1104, the transceiver 1106, or various combinations or components thereof may support a method for performing one or more of the operations described herein.

In some implementations, the processor 1102, the memory 1104, the transceiver 1106, or various combinations or components thereof may be implemented in hardware (e.g., in communications management circuitry) . The hardware may include a processor, a digital signal processor (DSP) , an application-specific integrated circuit (ASIC) , a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, discrete hardware components, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure. In some implementations, the processor 1102 and the memory 1104 coupled with the processor 1102 may be configured to perform one or more of the functions described herein (e.g., executing, by the processor 1102, instructions stored in the memory 1104) .

For example, the processor 1102 may support wireless communication at the device 1100 in accordance with examples as disclosed herein. The processor 1102 may be configured to operable to support means for predicting CSI.

The processor 1102 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof) . In some implementations, the processor 1102 may be configured to operate a memory array using a memory controller. In some other implementations, a memory controller may be integrated into the processor 1102. The processor 1102 may be configured to execute computer-readable instructions stored in a memory (e.g., the memory 1104) to cause the device 1100 to perform various functions of the present disclosure.

The memory 1104 may include random access memory (RAM) and read-only memory (ROM) . The memory 1104 may store computer-readable, computer-executable code including instructions that, when executed by the processor 1102 cause the device 1100 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some implementations, the code may not be directly executable by the processor 1102 but may cause a computer (e.g., when compiled and executed) to perform functions described herein. In some implementations, the memory 1104 may include, among other things, a basic I/O system (BIOS) which may control basic hardware or software operation such as the interaction with peripheral components or devices.

The I/O controller 1108 may manage input and output signals for the device 1100. The I/O controller 1108 may also manage peripherals not integrated into the device M02. In some implementations, the I/O controller 1108 may represent a physical connection or port to an external peripheral. In some implementations, the I/O controller 1108 may utilize an operating system such as or another known operating system. In some implementations, the I/O controller 1108 may be implemented as part of a processor, such as the processor 1106. In some implementations, a user may interact with the device 1100 via the I/O controller 1108 or via hardware components controlled by the I/O controller 1108.

In some implementations, the device 1100 may include a single antenna 1110. However, in some other implementations, the device 1100 may have more than one antenna 1110 (i.e., multiple antennas) , including multiple antenna panels or antenna arrays, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. The transceiver 1106 may communicate bi-directionally, via the one or more antennas 1110, wired, or wireless links as described herein. For example, the transceiver 1106 may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The transceiver 1106 may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas 1110 for transmission, and to demodulate packets received from the one or more antennas 1110. The transceiver 1106 may include one or more transmit chains, one or more receive chains, or a combination thereof.

A transmit chain may be configured to generate and transmit signals (e.g., control information, data, packets) . The transmit chain may include at least one modulator for modulating data onto a carrier signal, preparing the signal for transmission over a wireless medium. The at least one modulator may be configured to support one or more techniques such as amplitude modulation (AM) , frequency modulation (FM) , or digital modulation schemes like phase-shift keying (PSK) or quadrature amplitude modulation (QAM) . The transmit chain may also include at least one power amplifier configured to amplify the modulated signal to an appropriate power level suitable for transmission over the wireless medium. The transmit chain may also include one or more antennas 1110 for transmitting the amplified signal into the air or wireless medium.

A receive chain may be configured to receive signals (e.g., control information, data, packets) over a wireless medium. For example, the receive chain may include one or more antennas 1110 for receive the signal over the air or wireless medium. The receive chain may include at least one amplifier (e.g., a low-noise amplifier (LNA) ) configured to amplify the received signal. The receive chain may include at least one demodulator configured to demodulate the receive signal and obtain the transmitted data by reversing the modulation technique applied during transmission of the signal. The receive chain may include at least one decoder for decoding the processing the demodulated signal to receive the transmitted data.

FIG. 12 illustrates an example of a processor 1200 that supports the solution for predicting CSI in accordance with aspects of the present disclosure. The processor 1200 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 1200 may include a controller 1202 configured to perform various operations in accordance with examples as described herein. The processor 1200 may optionally include at least one memory 1204, such as L1/L2/L3 cache. Additionally, or alternatively, the processor 1200 may optionally include one or more arithmetic-logic units (ALUs) 1200. One or more of these components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 1200 may be a processor chipset and include a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) in accordance with examples as described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to or included in the processor chipset (e.g., the processor 1200) or other memory (e.g., random access memory (RAM) , read-only memory (ROM) , dynamic RAM (DRAM) , synchronous dynamic RAM (SDRAM) , static RAM (SRAM) , ferroelectric RAM (FeRAM) , magnetic RAM (MRAM) , resistive RAM (RRAM) , flash memory, phase change memory (PCM) , and others) .

The controller 1202 may be configured to manage and coordinate various operations (e.g., signaling, receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) of the processor 1200 to cause the processor 1200 to support various operations of a base station in accordance with examples as described herein. For example, the controller 1202 may operate as a control unit of the processor 1200, generating control signals that manage the operation of various components of the processor 1200. These control signals include enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.

The controller 1202 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 1204 and determine subsequent instruction (s) to be executed to cause the processor 1200 to support various operations in accordance with examples as described herein. The controller 1202 may be configured to track memory address of instructions associated with the memory 1204. The controller 1202 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 1202 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 1200 to cause the processor 1200 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 1202 may be configured to manage flow of data within the processor 1200. The controller 1202 may be configured to control transfer of data between registers, arithmetic logic units (ALUs) , and other functional units of the processor 1200.

The memory 1204 may include one or more caches (e.g., memory local to or included in the processor 1200 or other memory, such RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementation, the memory 1204 may reside within or on a processor chipset (e.g., local to the processor 1200) . In some other implementations, the memory 1204 may reside external to the processor chipset (e.g., remote to the processor 1200) .

The memory 1204 may store computer-readable, computer-executable code including instructions that, when executed by the processor 1200, cause the processor 1200 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. The controller 1202 and/or the processor 1200 may be configured to execute computer-readable instructions stored in the memory 1204 to cause the processor 1200 to perform various functions. For example, the processor 1200 and/or the controller 1202 may be coupled with or to the memory 1204, and the processor 1200, the controller 1202, and the memory 1204 may be configured to perform various functions described herein. In some examples, the processor 1200 may include multiple processors and the memory 1204 may include multiple memories. One or more of the multiple processors may be coupled with one or more of the multiple memories, which may, individually or collectively, be configured to perform various functions herein.

The one or more ALUs 1200 may be configured to support various operations in accordance with examples as described herein. In some implementation, the one or more ALUs 1200 may reside within or on a processor chipset (e.g., the processor 1200) . In some other implementations, the one or more ALUs 1200 may reside external to the processor chipset (e.g., the processor 1200) . One or more ALUs 1200 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 1200 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 1200 be configured with a variety of logical and arithmetic circuits, including adders, subtractors, shifters, and logic gates, to process and manipulate the data according to the operation. Additionally, or alternatively, the one or more ALUs 1200 may support logical operations such as AND, OR, exclusive-OR (XOR) , not-OR (NOR) , and not-AND (NAND) , enabling the one or more ALUs 1200 to handle conditional operations, comparisons, and bitwise operations.

The processor 1200 may support wireless communication in accordance with examples as disclosed herein. The processor 1200 may be configured to or operable to support means for predicting CSI.

FIG. 13 illustrates an example of a processor 1300 that supports the solution for predicting CSI in accordance with aspects of the present disclosure. The processor 1300 may be an example of a processor configured to perform various operations in accordance with examples as described herein. The processor 1300 may include a controller 1302 configured to perform various operations in accordance with examples as described herein. The processor 1300 may optionally include at least one memory 1304, such as L1/L2/L3 cache. Additionally, or alternatively, the processor 1300 may optionally include one or more arithmetic-logic units (ALUs) 1300. One or more of these components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more interfaces (e.g., buses) .

The processor 1300 may be a processor chipset and include a protocol stack (e.g., a software stack) executed by the processor chipset to perform various operations (e.g., receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) in accordance with examples as described herein. The processor chipset may include one or more cores, one or more caches (e.g., memory local to or included in the processor chipset (e.g., the processor 1300) or other memory (e.g., random access memory (RAM) , read-only memory (ROM) , dynamic RAM (DRAM) , synchronous dynamic RAM (SDRAM) , static RAM (SRAM) , ferroelectric RAM (FeRAM) , magnetic RAM (MRAM) , resistive RAM (RRAM) , flash memory, phase change memory (PCM) , and others) .

The controller 1302 may be configured to manage and coordinate various operations (e.g., signaling, receiving, obtaining, retrieving, transmitting, outputting, forwarding, storing, determining, identifying, accessing, writing, reading) of the processor 1300 to cause the processor 1300 to support various operations of a UE in accordance with examples as described herein. For example, the controller 1302 may operate as a control unit of the processor 1300, generating control signals that manage the operation of various components of the processor 1300. These control signals include enabling or disabling functional units, selecting data paths, initiating memory access, and coordinating timing of operations.

The controller 1302 may be configured to fetch (e.g., obtain, retrieve, receive) instructions from the memory 1304 and determine subsequent instruction (s) to be executed to cause the processor 1300 to support various operations in accordance with examples as described herein. The controller 1302 may be configured to track memory address of instructions associated with the memory 1304. The controller 1302 may be configured to decode instructions to determine the operation to be performed and the operands involved. For example, the controller 1302 may be configured to interpret the instruction and determine control signals to be output to other components of the processor 1300 to cause the processor 1300 to support various operations in accordance with examples as described herein. Additionally, or alternatively, the controller 1302 may be configured to manage flow of data within the processor 1300. The controller 1302 may be configured to control transfer of data between registers, arithmetic logic units (ALUs) , and other functional units of the processor 1300.

The memory 1304 may include one or more caches (e.g., memory local to or included in the processor 1300 or other memory, such RAM, ROM, DRAM, SDRAM, SRAM, MRAM, flash memory, etc. In some implementation, the memory 1304 may reside within or on a processor chipset (e.g., local to the processor 1300) . In some other implementations, the memory 1304 may reside external to the processor chipset (e.g., remote to the processor 1300) .

The memory 1304 may store computer-readable, computer-executable code including instructions that, when executed by the processor 1300, cause the processor 1300 to perform various functions described herein. The code may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. The controller 1302 and/or the processor 1300 may be configured to execute computer-readable instructions stored in the memory 1304 to cause the processor 1300 to perform various functions. For example, the processor 1300 and/or the controller 1202 may be coupled with or to the memory 1304, and the processor 1300, the controller 1302, and the memory 1304 may be configured to perform various functions described herein. In some examples, the processor 1300 may include multiple processors and the memory 1304 may include multiple memories. One or more of the multiple processors may be coupled with one or more of the multiple memories, which may, individually or collectively, be configured to perform various functions herein.

The one or more ALUs 1300 may be configured to support various operations in accordance with examples as described herein. In some implementation, the one or more ALUs 1300 may reside within or on a processor chipset (e.g., the processor 1300) . In some other implementations, the one or more ALUs 1300 may reside external to the processor chipset (e.g., the processor 1300) . One or more ALUs 1300 may perform one or more computations such as addition, subtraction, multiplication, and division on data. For example, one or more ALUs 1300 may receive input operands and an operation code, which determines an operation to be executed. One or more ALUs 1300 be configured with a variety of logical and arithmetic circuits, including adders, subtractors, shifters, and logic gates, to process and manipulate the data according to the operation. Additionally, or alternatively, the one or more ALUs 1300 may support logical operations such as AND, OR, exclusive-OR (XOR) , not-OR (NOR) , and not-AND (NAND) , enabling the one or more ALUs 1300 to handle conditional operations, comparisons, and bitwise operations.

The processor 1300 may support wireless communication in accordance with examples as disclosed herein. The processor 1300 may be configured to or operable to support means for predicting CSI.

FIG. 14 illustrates a flowchart of a method 1400 that supports a solution for predicting CSI in accordance with aspects of the present disclosure. The operations of the method 1400 may be implemented by a device or its components as described herein. For example, the operations of the method 1400 may be performed by a UE 104 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 1405, the method may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter. The operations of 1405 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1405 may be performed by a device as described with reference to FIG. 1.

At 1410, the method may include determining to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window. The operations of 1410 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1410 may be performed by a device as described with reference to FIG. 1.

FIG. 15 illustrates a flowchart of a method 1500 that supports a solution for predicting CSI in accordance with aspects of the present disclosure. The operations of the method 1500 may be implemented by a device or its components as described herein. For example, the operations of the method 1500 may be performed by a network entity 102 as described herein. In some implementations, the device may execute a set of instructions to control the function elements of the device to perform the described functions. Additionally, or alternatively, the device may perform aspects of the described functions using special-purpose hardware.

At 1505, the method may include determining at least one prediction model, wherein each of the at least one prediction model is determined based on CSI-RSs associated with at least one parameter. The operations of 1505 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1505 may be performed by a device as described with reference to FIG. 1.

At 1510, the method may include receive, via the transceiver from a UE, one or more CSI reports for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window. The operations of 1510 may be performed in accordance with examples as described herein. In some implementations, aspects of the operations of 1510 may be performed by a device as described with reference to FIG. 1.

It should be noted that the methods described herein describes possible implementations, and that the operations and the steps may be rearranged or otherwise modified and that other implementations are possible. Further, aspects from two or more of the methods may be combined.

The various illustrative blocks and components described in connection with the disclosure herein may be implemented or performed with a general-purpose processor, a DSP, an ASIC, a CPU, an FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope of the disclosure and appended claims. For example, due to the nature of software, functions described herein may be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.

Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer. By way of example, non-transitory computer-readable media may include RAM, ROM, electrically erasable programmable ROM (EEPROM) , flash memory, compact disk (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that may be used to carry or store desired program code means in the form of instructions or data structures and that may be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor.

As used herein, including in the claims, an article “a” before an element is unrestricted and understood to refer to “at least one” of those elements or “one or more” of those elements. The terms “a, ” “at least one, ” “one or more, ” and “at least one of one or more” may be interchangeable. As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of” or “one or more of” or “one or both of” ) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C) . Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an example step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on”shall be construed in the same manner as the phrase “based at least in part on. Further, as used herein, including in the claims, a “set” may include one or more elements.

The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

Claims

A user equipment (UE) comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

determine at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter; and

determine to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.
The UE of claim 1, wherein the at least one parameter comprises one of the following:

a number of CSI-RSs in a measurement window;

an interval of CSI-RSs in a measurement window;

a symbol for a CSI-RS being configured with an uplink (UL) subband or not; or

a CSI-RS pattern in a measurement window, wherein the CSI-RS pattern indicates at least one of a CSI-RS position, at least one interval of CSI-RSs, or a number of CSI-RSs in the measurement window.
The UE of claim 1, wherein in the case of one or more CSI-RSs are cancelled in the measurement window, the at least one CSI-RS used for predicting the CSI report comprises:

at least one remaining CSI-RS in the measurement window; or

the at least one remaining CSI-RS and at least one supplementary CSI-RS, wherein a supplementary CSI-RS is determined based on the remaining CSI-RS.
The UE of claim 3, wherein a CSI-RS among the one or more CSI-RSs is cancelled in one of the following cases:

the CSI-RS overlaps with UL symbols;

the CSI-RS is in a symbol or slot not configured with UL subband, and a prediction model associated with symbol or slot configured with UL subband is used; or

one or more CSI-RSs are in a symbol or slot configured with UL subband and a prediction model associated with symbol or slots not configured with UL subband is used.
The UE of claim 1, wherein each of the at least one prediction model is determined based on one of the following:

a combination of CSI-RSs associated with symbols or slots configured with UL subband and CSI-RSs associated with symbols or slots not configured with UL subband;

CSI-RSs associated with symbols or slots configured with UL subband; or

CSI-RSs associated with symbols or slots not configured with UL subband.
The UE of claim 1, wherein the processor is further configured to:

in the case that all CSI-RSs are in the symbols or slots configured with UL subband in the measurement window, a prediction model of the at least one prediction model determined based on the CSI-RSs associated with symbols or slots configured with UL subband is used for prediction; or

in the case that all CSI-RSs are in symbols or slots not configured with UL subband in the measurement window, a prediction model of the at least one prediction model determined based on the CSI-RSs associated with symbols or slots not configured with UL subband is used for prediction.
The UE of claim 1, wherein the processor is further configured to:

in the case that none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, prevent from predicting the CSI report; or

in the case that a number of corresponding parameters of CSI-RSs in a measurement window with different parameters exceeds a threshold, prevent from predicting the CSI report.
The UE of claim 7, wherein the processor is further configured to:

cancel the CSI report for the prediction window;

transmit, via the transceiver, the CSI report for the CSI-RSs in the measurement window; or

detect, via the transceiver, scheduling information from a base station for scheduling the CSI report for the prediction window.
The UE of claim 1, wherein the processor is further configured to predict the CSI report based on a selected prediction model of the at least one prediction model in the following case:

a number of CSI-RSs in the measurement window is the same with a number of CSI-RSs used for determining the selected prediction model; or

a symbol or slot format of the CSI-RSs in the measurement window is the same with a slot format associated with the CSI-RSs used for determining the selected prediction model.
The UE of claim 1, wherein the processor is further configured to predict the CSI report based on a prediction model for symbols or slots configured with UL subband of the at least one prediction model in the following case:

a number of CSI-RSs in symbols or slots configured with UL subband in the measurement window is greater than a number of CSI-RSs in symbols or slots not configured with UL subband in the measurement window; or

first CSI-RS in symbols or slots configured with UL subband in the measurement window.
The UE of claim 1, wherein the processor is further configured to:

in the case that a number of CSI-RSs in symbols or slots configured with UL subband in the measurement window is the same with a number of CSI-RSs in symbols or slots not configured with UL subband in the measurement window, predict the CSI report based on a predefined or indicated prediction model.
The UE of claim 1, wherein a prediction model of the at least one prediction model is determined based on CSI-RSs associated with parameters X and Y, wherein X is a minimum number of CSI-RS instances, and Y is a maximum interval of the CSI-RS instances,

and wherein the processor is further configured to:

in the case that X for a first prediction model is smaller than or equal to a number of CSI-RSs in the measurement window, and/or

in the case that Y for the first prediction model is greater than or equal to an interval of CSI-RSs in the measurement window,

predict the CSI report based on the first prediction model.
The UE of claim 12, wherein the processor is further configured to select one of first prediction models to predict the CSI report, wherein the selected first prediction model is associated with the same CSI-RS patterns as CSI-RS patterns in the measurement window; the same interval of CSI-RSs as an interval of CSI-RSs in the measurement window; or the same number of CSI-RSs as a number of CSI-RSs in the measurement window.
The UE of claim 1, wherein the processor is further configured to predict the CSI report based on a prediction model which is predefined, preconfigured or indicated by a base station.
The UE of claim 1, wherein the processor is further configured to:

predict a plurality of CSI reports based on a plurality of prediction models among the at least one prediction model, wherein the plurality of prediction models are determined based on at least one parameter which is the same as at least one parameter in a measurement window; or

predict the plurality of CSI reports based on the at least one prediction model.
The UE of claim 15, wherein the processor is further configured to:

transmit, via the transceiver to a base station, the plurality of CSI reports; or

transmit, via the transceiver to the base station, a CSI report determined based on an average of the plurality of CSI reports.
The UE of claim 1, wherein the processor is further configured to:

predict a first CSI report based on a prediction model associated with symbols or slots configured with UL subband;

predict a second CSI report based on a prediction model associated with symbols or slots not configured with UL subband; and

transmit, via the transceiver to the base station, the first CSI report and the second CSI report.
The UE of claim 1, wherein determining to predict the CSI report using one or more of the at least one prediction model comprises:

in the case that none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, determine an extended measurement window based on extending the measurement window by one or more time units;

until one or more parameters of CSI-RSs in the extended measurement window are the same as one or more parameters associated with one or more prediction models of the at least one prediction model, determine to predict the CSI report based on the one or more prediction models.
The UE of claim 1, wherein the parameter associated with the at least one CSI-RS in the measurement window is the same as parameters used for determining one or more prediction model among the at least one prediction model.
A base station (BS) comprising:

a processor; and

a transceiver coupled to the processor,

wherein the processor is configured to:

determine at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter; and

receive, via the transceiver from a user equipment (UE) , one or more CSI reports for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.
The BS of claim 20, wherein the at least one parameter comprises one of the following:

a number of CSI-RSs in a measurement window;

an interval of CSI-RSs in a measurement window;

a symbol for a CSI-RS being configured with an uplink (UL) subband or not; or

a CSI-RS pattern in a measurement window, wherein the CSI-RS pattern indicates at least one of a CSI-RS position, at least one interval of CSI-RSs, or a number of CSI-RSs in the measurement window.
The BS of claim 20, wherein the parameter associated with the at least one CSI-RS in the measurement window is same as parameters used for determining one or more prediction model among the at least one prediction model.
The BS of claim 20, wherein the processor is further configured to:

transmit, via the transceiver to the UE, an indication indicative of using which prediction models of the at least one prediction model to predict the CSI report.
The BS of claim 20, wherein the processor is further configured to:

in the case that none of parameters of CSI-RSs in the measurement window is the same as a parameter associated with one of the at least one prediction model, or in the case that a number of corresponding parameters of CSI-RSs in a measurement window with different parameters exceeds a threshold,

prevent from receiving the CSI report;

receive, via the transceiver, the CSI report for the CSI-RSs in the measurement window; or

transmit, via the transceiver, scheduling information for scheduling the CSI report for the prediction window.
The BS of claim 20, wherein the processor is further configured to:

receive, via the transceiver, a plurality of CSI reports based on a plurality of prediction models among the at least one prediction model, wherein the plurality of prediction models are determined based on at least one parameter which is the same as at least one parameter in a measurement window; or

receive, via the transceiver, a plurality of CSI reports based on the at least one prediction model.
A processor for wireless communication, comprising:

at least one memory; and

a controller coupled with the at least one memory and configured to cause the controller to:

determine at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter; and

determine to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.
A processor for wireless communication, comprising:

at least one memory; and

a controller coupled with the at least one memory and configured to cause the controller to:

determine at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter; and

receive, via the transceiver from a user equipment (UE) , one or more CSI reports for a prediction window at least one CSI-RS in a measurement window corresponding to the prediction window.
A method performed by a user equipment (UE) comprising:

determining at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter; and

determining to predict, using one or more of the at least one prediction model, a CSI report for a prediction window based on at least one CSI-RS in a measurement window corresponding to the prediction window.
A method performed by a base station (BS) comprising:

determining at least one prediction model, wherein each of the at least one prediction model is determined based on channel state information (CSI) reference signals (RS) associated with at least one parameter; and

receiving, from a user equipment (UE) , one or more CSI reports for a prediction window at least one CSI-RS in a measurement window corresponding to the prediction window.