WO2021260410A1

WO2021260410A1 - Radio design using machine learning

Info

Publication number: WO2021260410A1
Application number: PCT/IB2020/055884
Authority: WO
Inventors: Yashar NEZAMI; Sepideh AFSAR DOOST
Original assignee: Telefonaktiebolaget LM Ericsson AB
Current assignee: Telefonaktiebolaget LM Ericsson AB
Priority date: 2020-06-22
Filing date: 2020-06-22
Publication date: 2021-12-30
Anticipated expiration: 2022-12-22

Abstract

According to certain embodiments, a method for use in a server for efficiently sizing resources of a network node comprising the following steps. The network node comprises a plurality of features, and the method comprises: obtaining network information for one or more operational wireless networks; mapping portions of the obtained network information to one or more related features of the plurality of features of the network node; clustering the portions of the obtained network information for each feature of the plurality of features to find clusters of similar patterns; and based on the clustering results, determining a plurality of network node types (K), wherein each network node type comprises network node resources for each feature of the network node and wherein the network node resources are allocated according to a cluster of similar patterns for the feature.

Description

RADIO DESIGN USING MACHINE LEARNING

TECHNICAL FIELD

Embodiments of the present disclosure are directed to radio product portfolio design for wireless networks using machine learning and artificial intelligence.

BACKGROUND

Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and/or is implied from the context in which it is used. All references to a/an/the element, apparatus, component, means, step, etc. are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and/or where it is implicit that a step must follow or precede another step. Any feature of any of the embodiments disclosed herein may be applied to any other embodiment, wherever appropriate. Likewise, any advantage of any of the embodiments may apply to any other embodiments, and vice versa. Other objectives, features, and advantages of the enclosed embodiments will be apparent from the following description.

Currently, base stations and radios for wireless communication networks are engineered based on requirements provided by product management engineers. The requirements are derived from different sources such as market research, customer inputs and business intelligence. The input sources are susceptible to errors due to reasons such as customer ambiguity on their own requirements and contradictory market research information. One way to mitigate such errors is to add margins in the product specifications and consider peak use cases of the market.

FIGURE 1 illustrates an example of typical base station radio product portfolio design. In the illustrated example, multiple product managers receive input from multiple sources such as customer input, business intelligence, and market research. The input results in requirements for one or more radio types.

There currently exist certain challenges. For example, there are several issues with the product strategy and requirement generation as described above and illustrated in FIGURE 1. The decisions about the product requirements are derived from a wide range of data sources which are prone to errors. Furthermore, the product requirements are input from humans, and humans are naturally subjective.

Another issue is that the product requirements are normally written for the peak use cases as mentioned above and may not correctly represent the actual deployment scenarios of operators. While the products designed with such requirements can potentially cover more use cases, they lack efficient design and are over-dimensioned for most of the use cases. In other words, lack of accurate and detailed knowledge about each operator’s deployment scenarios and actual needs lead to suboptimum design targets and less competitive product portfolio.

Furthermore, as illustrated in FIGURE 1, the specifications and requirements of different product types are often coming from different sources which may not be aligned and can break the modular productization.

Detailed network knowledge might enable product managers and engineers to make data- driven decisions about the radio attributes and optimize for the targeted markets and customers. However, network deployment data is scattered and messy and even if access to cleaned and organized data is available via manual techniques, finding the right attributes for a given set of networks can be difficult and prone to errors and subjective biases via conventional methods.

SUMMARY

As described above, there currently exist certain challenges with designing efficiently sized radio products for wireless networks. Certain aspects of the present disclosure and their embodiments may provide solutions to these or other challenges.

For example, particular embodiments include a method for use in a server for efficiently sizing resources of a network node comprising the following steps. The network node comprises a plurality of features, and the method comprises: obtaining network information for one or more operational wireless networks; mapping portions of the obtained network information to one or more related features of the plurality of features of the network node; clustering the portions of the obtained network information for each feature of the plurality of features to find clusters of similar patterns; and based on the clustering results, determining a plurality of network node types (K), wherein each network node type comprises network node resources for each feature of the network node and wherein the network node resources are allocated according to a cluster of similar patterns for the feature. In particular embodiments, the method further comprises generating network node product requirements based on the determined K network node types. The method may further comprise cleaning the obtained network information to remove or correct erroneous information.

In particular embodiments, the network information comprises static information, such as one or more of spectrum holdings; geographical data of network nodes; and hardware configuration. The network information may comprise dynamic information, such as one or more of key performance indicator (KPI) logs, traffic load information, and output power information.

In particular embodiments, the clustering comprises any one or more of centroid-based clustering, density-based clustering, distribution-based clustering; spectral clustering, and MeanShift clustering. Determining the plurality of network node types (K) may be optimized using one or more of the statistical testing methods Elbow and Silhouette.

In particular embodiments, the network node comprises a base station.

According to some embodiments, a server comprises processing circuitry operable to perform any of the server methods described above.

Also disclosed is a computer program product comprising a non-transitory computer readable medium storing computer readable program code, the computer readable program code operable, when executed by processing circuitry to perform any of the methods performed by the server described above.

Certain embodiments may provide one or more of the following technical advantages. For example, particular embodiments include data-driven centralized radio product portfolio design that matches customers’ requirements and avoids a segmented non-modular portfolio.

Particular embodiments facilitate efficient radio design with optimized requirements that avoid targeting peak use cases. Particular embodiments optimize design targets tightly with realistic requirements resulting in efficient and competitive radio designs.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosed embodiments and their features and advantages, reference is now made to the following description, taken in conjunction with the accompanying drawings, in which:

FIGURE 1 illustrates an example of typical base station radio product portfolio design; FIGURE 2 is a block diagram illustrating an example system for efficiently sizing resources of a network node;

FIGURE 3 is a graphical representation of cluster data, according to a particular embodiment;

FIGURE 4 is chart illustrating two radio clusters, according to a particular embodiment;

FIGURE 5 is table listing attributes of two clusters, according to a particular embodiment;

FIGURE 6 is a block diagram illustrating an example wireless network;

FIGURE 7 is a block diagram illustrating an example server for optimally sizing resources of a network node; and

FIGURE 8 is a flowchart illustrating an example method in a server for optimally sizing resources of a network node.

DETAILED DESCRIPTION

As described above, there currently exist certain challenges with designing efficiently sized radio products for wireless networks.. Certain aspects of the present disclosure and their embodiments may provide solutions to these or other challenges.

For example, particular embodiments include a centralized artificial intelligence (AI)- powered solution used by base station radio architects and designers as well as product managers. The intelligent data-driven tool may be referred to as a Centralized AI -Powered Product Portfolio Recommendation System (PPRS) and recommends the most efficient radio types for a given set of markets and operators. It demonstrates the required radio attributes of the proposed portfolio, such as the number of radio frequency (RF) branches, total channel bandwidth (CBW), instantaneous bandwidth (IBW), number of channels, radio access technology (RAT), max output power, equivalent isotropic radiated power (EIRP), power spectral density (PSD), radio capacity in terms of physical resource block (PRB) utilization and multiple -input multiple -output (MIMO) layers, etc. Particular embodiments include database resources providing static or dynamic information on the network attributes.

Particular embodiments may be integrated with multiple databases and dynamically extract the network attributes for a set of operators and markets. After data pre-processing, feature mapping and engineering, particular embodiments analyze and interpret the data by applying clustering algorithms to find similarities and group the attributes to a known number of clusters. Each cluster defines a different radio type defined by all or some of characteristics listed above.

Particular embodiments are described more fully with reference to the accompanying drawings. Other embodiments, however, are contained within the scope of the subject matter disclosed herein. The disclosed subject matter should not be construed as limited to only the embodiments set forth herein; rather, these embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

FIGURE 2 is a block diagram illustrating an example system for efficiently sizing resources of a network node. The illustrated example optimally sizes radio resources for use as a product portfolio recommendation system, but other embodiments may optimize radio resources for any suitable purpose.

System 10 includes server 12 for efficiently sizing resources of a network node. In the illustrated example, the resources are related to radio types for a network node, such as a base station. The network node comprises a plurality of features, such as number of RF branches, maximum output power, number of bands, band combinations, radio capacity, CBW, IBW, and RAT.

Server 12 obtains network information for one or more operational wireless networks, such as the wireless network described with respect to FIGURE 6. In particular embodiments, several different network data sources 14 are used as input. Some examples of such data sources include but are not limited to: spectrum holdings of operators; geographical data of base stations; hardware configuration datasets; and key performance indicator (KPI) logs.

The data from the static and/or dynamic sources 14 are fed into server 12, which in the illustrated example is a product recommendation system. The recommendation system may be referred to as a product portfolio recommendation system (PPRS).

Server 12 includes feature mapping and generation engine 16 and clustering engine 18. Feature mapping and generation engine 16 maps portions of the obtained network information to one or more related features of the plurality of features of the network node. For example, the raw input data goes through a feature mapping and generation pipeline that, after cleaning and correcting the data, maps the input features to radio related attributes used in the next step. An example is calculating IBW and CBW using the operators’ spectrum holdings. Another example of a new feature is the estimated number of RF/antenna branches based on hardware configuration of existing radios, their geographical location (urban, suburban, rural, etc.) and their traffic load requirement (PRB utilization). Some of the features (e.g., radio max output power or EIRP) can be decided to be used in raw data format with no further processing.

Next, clustering engine 18 takes the preprocessed data containing new features and uses a machine learning model to find similar patterns and attributes of the radios. Clustering algorithms are best choices for the purpose of grouping objects to specific number of clusters. Some of the clustering algorithms that can be used include: centroid-based clustering methods such as K- means; density-based clustering such as DBSCAN; distribution-based clustering; spectral clustering; and MeanShift clustering.

Output 20 from the model is K radio types defined by specifications such as number of RF branches/antennas, maximum output power; number of bands; band combinations; radio capacity; CBW, IBW; and RAT.

The number of radio types (K) can be optimized using methods such as Elbow, Silhouette or other statistical testing methods. The number of radio types is also based on a balance of business needs and resource capacity.

FIGURE 3 is a graphical representation of cluster data, according to a particular embodiment. The example illustrates cluster data for radio band 5 for an example wireless network. The clusters are for radio attributes such as CBW, IBW, number of transmit antennas, number of receive antennas, and configured maximum transmission power. Other embodiments may use a larger number of attributes or different attributes.

FIGURE 4 is chart illustrating two radio clusters, according to a particular embodiment. For example, based on the data in FIGURE 3, the clustering algorithm identified two clusters, cluster 0 and cluster 1. The vertical axis represents the number of radios in each cluster.

FIGURE 5 is table listing attributes of two clusters, according to a particular embodiment. For example, the two clusters illustrated in FIGURE 4 may include the indicated values for each feature.

An advantage of the radio product portfolio recommended by the example system above is that the product portfolio covers the customers’ requirements tightly, but also avoids a segmented and cluttered portfolio.

PPRS input and expected output attributes can be modified and list above provide as an example.

FIGURE 6 illustrates an example wireless network, according to certain embodiments. The wireless network may comprise and/or interface with any type of communication, telecommunication, data, cellular, and/or radio network or other similar type of system. In some embodiments, the wireless network may be configured to operate according to specific standards or other types of predefined rules or procedures. Thus, particular embodiments of the wireless network may implement communication standards, such as Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Uong Term Evolution (UTE), and/or other suitable 2G, 3G, 4G, or 5G standards; wireless local area network (WLAN) standards, such as the IEEE 802.11 standards; and/or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave and/or ZigBee standards.

Network 106 may comprise one or more backhaul networks, core networks, IP networks, public switched telephone networks (PSTNs), packet data networks, optical networks, wide-area networks (WANs), local area networks (LANs), wireless local area networks (WLANs), wired networks, wireless networks, metropolitan area networks, and other networks to enable communication between devices.

Network node 160 and WD 110 comprise various components described in more detail below. These components work together to provide network node and/or wireless device functionality, such as providing wireless connections in a wireless network. In different embodiments, the wireless network may comprise any number of wired or wireless networks, network nodes, base stations, controllers, wireless devices, relay stations, and/or any other components or systems that may facilitate or participate in the communication of data and/or signals whether via wired or wireless connections.

As used herein, network node refers to equipment capable, configured, arranged and/or operable to communicate directly or indirectly with a wireless device and/or with other network nodes or equipment in the wireless network to enable and/or provide wireless access to the wireless device and/or to perform other functions (e.g., administration) in the wireless network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)). Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and may then also be referred to as femto base stations, pico base stations, micro base stations, or macro base stations.

A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units and/or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

Yet further examples of network nodes include multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell/multicast coordination entities (MCEs), core network nodes (e.g., MSCs, MMEs), O&M nodes, OSS nodes, SON nodes, positioning nodes (e.g., E-SMLCs), and/or MDTs. As another example, a network node may be a virtual network node as described in more detail below. More generally, however, network nodes may represent any suitable device (or group of devices) capable, configured, arranged, and/or operable to enable and/or provide a wireless device with access to the wireless network or to provide some service to a wireless device that has accessed the wireless network.

In FIGURE 6, network node 160 includes processing circuitry 170, device readable medium 180, interface 190, auxiliary equipment 184, power source 186, power circuitry 187, and antenna 162. Although network node 160 illustrated in the example wireless network of FIGURE 6 may represent a device that includes the illustrated combination of hardware components, other embodiments may comprise network nodes with different combinations of components (e.g., the same components, different components, fewer components, or more components). It is to be understood that a network node comprises any suitable combination of hardware and/or software needed to perform the tasks, features, functions and methods disclosed herein. Moreover, while the components of network node 160 are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, a network node may comprise multiple different physical components that make up a single illustrated component (e.g., device readable medium 180 may comprise multiple separate hard drives as well as multiple RAM modules). Similarly, network node 160 may be composed of multiple physically separate components (e.g., a NodeB component and an RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which network node 160 comprises multiple separate components (e.g., BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeB’s. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, network node 160 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate device readable medium 180 for the different RATs) and some components may be reused (e.g., the same antenna 162 may be shared by the RATs). Network node 160 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 160, such as, for example, GSM, WCDMA, LTE, NR, WiFi, or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node 160.

Processing circuitry 170 is configured to perform any determining, calculating, or similar operations (e.g., certain obtaining operations) described herein as being provided by a network node, such as the scheduling operations described herein and with respect of FIGURES 2-4. The operations performed by processing circuitry 170 may include processing information obtained by processing circuitry 170 by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and/or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination.

Processing circuitry 170 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and/or encoded logic operable to provide, either alone or in conjunction with other network node 160 components, such as device readable medium 180, network node 160 functionality. For example, processing circuitry 170 may execute instructions stored in device readable medium 180 or in memory within processing circuitry 170. Such functionality may include providing any of the various wireless features, functions, or benefits discussed herein. In some embodiments, processing circuitry 170 may include a system on a chip (SOC).

In some embodiments, processing circuitry 170 may include one or more of radio frequency (RF) transceiver circuitry 172 and baseband processing circuitry 174. In some embodiments, radio frequency (RF) transceiver circuitry 172 and baseband processing circuitry 174 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry 172 and baseband processing circuitry 174 may be on the same chip or set of chips, boards, or units.

In certain embodiments, some or all of the functionality described herein as being provided by a network node, base station, eNB or other such network device may be performed by processing circuitry 170 executing instructions stored on device readable medium 180 or memory within processing circuitry 170. In alternative embodiments, some or all of the functionality may be provided by processing circuitry 170 without executing instructions stored on a separate or discrete device readable medium, such as in a hard-wired manner. In any of those embodiments, whether executing instructions stored on a device readable storage medium or not, processing circuitry 170 can be configured to perform the described functionality. The benefits provided by such functionality are not limited to processing circuitry 170 alone or to other components of network node 160, but are enjoyed by network node 160 as a whole, and/or by end users and the wireless network generally.

Device readable medium 180 may comprise any form of volatile or non-volatile computer readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and/or any other volatile or non-volatile, non-transitory device readable and/or computer-executable memory devices that store information, data, and/or instructions that may be used by processing circuitry 170. Device readable medium 180 may store any suitable instructions, data or information, including a computer program, software, an application including one or more of logic, rules, code, tables, etc. and/or other instructions capable of being executed by processing circuitry 170 and, utilized by network node 160. Device readable medium 180 may be used to store any calculations made by processing circuitry 170 and/or any data received via interface 190. In some embodiments, processing circuitry 170 and device readable medium 180 may be considered to be integrated.

Interface 190 is used in the wired or wireless communication of signaling and/or data between network node 160, network 106, and/or WDs 110. As illustrated, interface 190 comprises port(s)/terminal(s) 194 to send and receive data, for example to and from network 106 over a wired connection. Interface 190 also includes radio front end circuitry 192 that may be coupled to, or in certain embodiments a part of, antenna 162. Radio front end circuitry 192 comprises fdters 198 and amplifiers 196. Radio front end circuitry 192 may be connected to antenna 162 and processing circuitry 170. Radio front end circuitry may be configured to condition signals communicated between antenna 162 and processing circuitry 170. Radio front end circuitry 192 may receive digital data that is to be sent out to other network nodes or WDs via a wireless connection. Radio front end circuitry 192 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 198 and/or amplifiers 196. The radio signal may then be transmitted via antenna 162. Similarly, when receiving data, antenna 162 may collect radio signals which are then converted into digital data by radio front end circuitry 192. The digital data may be passed to processing circuitry 170. In other embodiments, the interface may comprise different components and/or different combinations of components.

In certain alternative embodiments, network node 160 may not include separate radio front end circuitry 192, instead, processing circuitry 170 may comprise radio front end circuitry and may be connected to antenna 162 without separate radio front end circuitry 192. Similarly, in some embodiments, all or some of RF transceiver circuitry 172 may be considered a part of interface 190. In still other embodiments, interface 190 may include one or more ports or terminals 194, radio front end circuitry 192, and RF transceiver circuitry 172, as part of a radio unit (not shown), and interface 190 may communicate with baseband processing circuitry 174, which is part of a digital unit (not shown).

Antenna 162 may include one or more antennas, or antenna arrays, configured to send and/or receive wireless signals. Antenna 162 may be coupled to radio front end circuitry 190 and may be any type of antenna capable of transmitting and receiving data and/or signals wirelessly. In some embodiments, antenna 162 may comprise one or more omni-directional, sector or panel antennas operable to transmit/receive radio signals between, for example, 2 GHz and 66 GHz. An omni-directional antenna may be used to transmit/receive radio signals in any direction, a sector antenna may be used to transmit/receive radio signals from devices within a particular area, and a panel antenna may be a line of sight antenna used to transmit/receive radio signals in a relatively straight line. In some instances, the use of more than one antenna may be referred to as MIMO. In certain embodiments, antenna 162 may be separate from network node 160 and may be connectable to network node 160 through an interface or port.

Antenna 162, interface 190, and/or processing circuitry 170 may be configured to perform any receiving operations and/or certain obtaining operations described herein as being performed by a network node. Any information, data and/or signals may be received from a wireless device, another network node and/or any other network equipment. Similarly, antenna 162, interface 190, and/or processing circuitry 170 may be configured to perform any transmitting operations described herein as being performed by a network node. Any information, data and/or signals may be transmitted to a wireless device, another network node and/or any other network equipment.

Power circuitry 187 may comprise, or be coupled to, power management circuitry and is configured to supply the components of network node 160 with power for performing the functionality described herein. Power circuitry 187 may receive power from power source 186. Power source 186 and/or power circuitry 187 may be configured to provide power to the various components of network node 160 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). Power source 186 may either be included in, or external to, power circuitry 187 and/or network node 160. For example, network node 160 may be connectable to an external power source (e.g., an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry 187. As a further example, power source 186 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry 187. The battery may provide backup power should the external power source fail. Other types of power sources, such as photovoltaic devices, may also be used.

Alternative embodiments of network node 160 may include additional components beyond those shown in FIGURE 6 that may be responsible for providing certain aspects of the network node’s functionality, including any of the functionality described herein and/or any functionality necessary to support the subject matter described herein. For example, network node 160 may include user interface equipment to allow input of information into network node 160 and to allow output of information from network node 160. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for network node 160.

As used herein, wireless device (WD) refers to a device capable, configured, arranged and/or operable to communicate wirelessly with network nodes and/or other wireless devices. Unless otherwise noted, the term WD may be used interchangeably herein with user equipment (UE). Communicating wirelessly may involve transmitting and/or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and/or other types of signals suitable for conveying information through air.

In some embodiments, a WD may be configured to transmit and/or receive information without direct human interaction. For instance, a WD may be designed to transmit information to a network on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the network.

Examples of a WD include, but are not limited to, a smart phone, a mobile phone, a cell phone, a voice over IP (VoIP) phone, a wireless local loop phone, a desktop computer, a personal digital assistant (PDA), a wireless cameras, a gaming console or device, a music storage device, a playback appliance, a wearable terminal device, a wireless endpoint, a mobile station, a tablet, a laptop, a laptop-embedded equipment (LEE), a laptop-mounted equipment (LME), a smart device, a wireless customer-premise equipment (CPE) a vehicle-mounted wireless terminal device, etc. A WD may support device -to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, vehicle-to-vehicle (V2V), vehicle- to-infrastructure (V2I), vehicle -to-everything (V2X) and may in this case be referred to as a D2D communication device.

As yet another specific example, in an Internet of Things (IoT) scenario, a WD may represent a machine or other device that performs monitoring and/or measurements and transmits the results of such monitoring and/or measurements to another WD and/or a network node. The WD may in this case be a machine-to-machine (M2M) device, which may in a 3GPP context be referred to as an MTC device. As one example, the WD may be a UE implementing the 3GPP narrow band internet of things (NB-IoT) standard. Examples of such machines or devices are sensors, metering devices such as power meters, industrial machinery, or home or personal appliances (e.g. refrigerators, televisions, etc.) personal wearables (e.g., watches, fitness trackers, etc.). In other scenarios, a WD may represent a vehicle or other equipment that is capable of monitoring and/or reporting on its operational status or other functions associated with its operation.

A WD as described above may represent the endpoint of a wireless connection, in which case the device may be referred to as a wireless terminal. Furthermore, a WD as described above may be mobile, in which case it may also be referred to as a mobile device or a mobile terminal.

In some embodiments, the wireless device may comprise a component of an aerial vehicle, such as a drone. In some embodiments, the wireless device may provide command and control for the aerial vehicle. In some embodiments, the wireless device may provide multimedia transmission from the aerial vehicle.

As illustrated, wireless device 110 includes antenna 111, interface 114, processing circuitry 120, device readable medium 130, user interface equipment 132, auxiliary equipment 134, power source 136 and power circuitry 137. WD 110 may include multiple sets of one or more of the illustrated components for different wireless technologies supported by WD 110, such as, for example, GSM, WCDMA, LTE, NR, WiFi, WiMAX, or Bluetooth wireless technologies, just to mention a few. These wireless technologies may be integrated into the same or different chips or set of chips as other components within WD 110.

Antenna 111 may include one or more antennas or antenna arrays, configured to send and/or receive wireless signals, and is connected to interface 114. In certain alternative embodiments, antenna 111 may be separate from WD 110 and be connectable to WD 110 through an interface or port. Antenna 111, interface 114, and/or processing circuitry 120 may be configured to perform any receiving or transmitting operations described herein as being performed by a WD. Any information, data and/or signals may be received from a network node and/or another WD. In some embodiments, radio front end circuitry and/or antenna 111 may be considered an interface.

As illustrated, interface 114 comprises radio front end circuitry 112 and antenna 111. Radio front end circuitry 112 comprise one or more filters 118 and amplifiers 116. Radio front end circuitry 114 is connected to antenna 111 and processing circuitry 120 and is configured to condition signals communicated between antenna 111 and processing circuitry 120. Radio front end circuitry 112 may be coupled to or a part of antenna 111. In some embodiments, WD 110 may not include separate radio front end circuitry 112; rather, processing circuitry 120 may comprise radio front end circuitry and may be connected to antenna 111. Similarly, in some embodiments, some or all of RF transceiver circuitry 122 may be considered a part of interface 114. Radio front end circuitry 112 may receive digital data that is to be sent out to other network nodes or WDs via a wireless connection. Radio front end circuitry 112 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of fdters 118 and/or amplifiers 116. The radio signal may then be transmitted via antenna 111. Similarly, when receiving data, antenna 111 may collect radio signals which are then converted into digital data by radio front end circuitry 112. The digital data may be passed to processing circuitry 120. In other embodiments, the interface may comprise different components and/or different combinations of components.

In some embodiments, WD 110 may include regular-power radio front end circuitry and/or antenna 111 and low-power radio front end circuitry and/or antenna 111. In some embodiments, the same radio circuitry may be configurable to operate as a low-power radio or a regular-power radio as needed over time.

Processing circuitry 120 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software, and/or encoded logic operable to provide, either alone or in conjunction with other WD 110 components, such as device readable medium 130, WD 110 functionality. Such functionality may include providing any of the various wireless features or benefits discussed herein. For example, processing circuitry 120 may execute instructions stored in device readable medium 130 or in memory within processing circuitry 120 to provide the functionality disclosed herein.

As illustrated, processing circuitry 120 includes one or more of RF transceiver circuitry 122, baseband processing circuitry 124, and application processing circuitry 126. In other embodiments, the processing circuitry may comprise different components and/or different combinations of components. In certain embodiments processing circuitry 120 ofWD 110 may comprise a SOC. In some embodiments, RF transceiver circuitry 122, baseband processing circuitry 124, and application processing circuitry 126 may be on separate chips or sets of chips. In alternative embodiments, part or all of baseband processing circuitry 124 and application processing circuitry 126 may be combined into one chip or set of chips, and RF transceiver circuitry 122 may be on a separate chip or set of chips. In still alternative embodiments, part or all of RF transceiver circuitry 122 and baseband processing circuitry 124 may be on the same chip or set of chips, and application processing circuitry 126 may be on a separate chip or set of chips. In yet other alternative embodiments, part or all of RF transceiver circuitry 122, baseband processing circuitry 124, and application processing circuitry 126 may be combined in the same chip or set of chips. In some embodiments, RF transceiver circuitry 122 may be a part of interface 114. RF transceiver circuitry 122 may condition RF signals for processing circuitry 120.

In certain embodiments, some or all of the functionality described herein as being performed by a WD may be provided by processing circuitry 120 executing instructions stored on device readable medium 130, which in certain embodiments may be a computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by processing circuitry 120 without executing instructions stored on a separate or discrete device readable storage medium, such as in a hard-wired manner. In any of those embodiments, whether executing instructions stored on a device readable storage medium or not, processing circuitry 120 can be configured to perform the described functionality. The benefits provided by such functionality are not limited to processing circuitry 120 alone or to other components of WD 110, but are enjoyed by WD 110, and/or by end users and the wireless network generally.

Processing circuitry 120 may be configured to perform any determining, calculating, or similar operations (e.g., certain obtaining operations) described herein as being performed by a WD. These operations, as performed by processing circuitry 120, may include processing information obtained by processing circuitry 120 by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored by WD 110, and/or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination.

Device readable medium 130 may be operable to store a computer program, software, an application including one or more of logic, rules, code, tables, etc. and/or other instructions capable of being executed by processing circuitry 120. Device readable medium 130 may include computer memory (e.g. RAM or ROM), mass storage media (e.g., a hard disk), removable storage media (e.g., a CD or a DVD), and/or any other volatile or non-volatile, non-transitory device readable and/or computer executable memory devices that store information, data, and/or instructions that may be used by processing circuitry 120. In some embodiments, processing circuitry 120 and device readable medium 130 may be integrated. User interface equipment 132 may provide components that allow for a human user to interact with WD 110. Such interaction may be of many forms, such as visual, audial, tactile, etc. User interface equipment 132 may be operable to produce output to the user and to allow the user to provide input to WD 110. The type of interaction may vary depending on the type of user interface equipment 132 installed in WD 110. For example, if WD 110 is a smart phone, the interaction may be via a touch screen; if WD 110 is a smart meter, the interaction may be through a screen that provides usage (e.g., the number of gallons used) or a speaker that provides an audible alert (e.g., if smoke is detected). User interface equipment 132 may include input interfaces, devices and circuits, and output interfaces, devices and circuits. User interface equipment 132 is configured to allow input of information into WD 110 and is connected to processing circuitry 120 to allow processing circuitry 120 to process the input information. User interface equipment 132 may include, for example, a microphone, a proximity or other sensor, keys/buttons, a touch display, one or more cameras, a USB port, or other input circuitry. User interface equipment 132 is also configured to allow output of information from WD 110, and to allow processing circuitry 120 to output information from WD 110. User interface equipment 132 may include, for example, a speaker, a display, vibrating circuitry, a USB port, a headphone interface, or other output circuitry. Using one or more input and output interfaces, devices, and circuits, of user interface equipment 132, WD 110 may communicate with end users and/or the wireless network and allow them to benefit from the functionality described herein.

Auxiliary equipment 134 is operable to provide more specific functionality which may not be generally performed by WDs. This may comprise specialized sensors for doing measurements for various purposes, interfaces for additional types of communication such as wired communications etc. The inclusion and type of components of auxiliary equipment 134 may vary depending on the embodiment and/or scenario.

Power source 136 may, in some embodiments, be in the form of a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic devices or power cells, may also be used. WD 110 may further comprise power circuitry 137 for delivering power from power source 136 to the various parts of WD 110 which need power from power source 136 to carry out any functionality described or indicated herein. Power circuitry 137 may in certain embodiments comprise power management circuitry. Power circuitry 137 may additionally or alternatively be operable to receive power from an external power source; in which case WD 110 may be connectable to the external power source (such as an electricity outlet) via input circuitry or an interface such as an electrical power cable. Power circuitry 137 may also in certain embodiments be operable to deliver power from an external power source to power source 136. This may be, for example, for the charging of power source 136. Power circuitry 137 may perform any formatting, converting, or other modification to the power from power source 136 to make the power suitable for the respective components of WD 110 to which power is supplied.

Although the subject matter described herein may be implemented in any appropriate type of system using any suitable components, the embodiments disclosed herein are described in relation to a wireless network, such as the example wireless network illustrated in FIGURE 6. For simplicity, the wireless network of FIGURE 6 only depicts network 106, network nodes 160 and 160b, and WDs 110, 110b, and 110c. In practice, a wireless network may further include any additional elements suitable to support communication between wireless devices or between a wireless device and another communication device, such as a landline telephone, a service provider, or any other network node or end device. Of the illustrated components, network node 160 and (WD 110 are depicted with additional detail. The wireless network may provide communication and other types of services to one or more wireless devices to facilitate the wireless devices’ access to and/or use of the services provided by, or via, the wireless network.

The communication system 106 may itself be connected to a host computer (not shown), which may be embodied in the hardware and/or software of a standalone server, a cloud- implemented server, a distributed server or as processing resources in a server farm. The host computer may be under the ownership or control of a service provider or may be operated by the service provider or on behalf of the service provider.

The communication system of FIGURE 6 as a whole enables connectivity between one of the connected WDs 110 and the host computer. The connectivity may be described as an over- the-top (OTT) connection. The host computer and the connected WDs 110 are configured to communicate data and/or signaling via the OTT connection, using an access network, a core network, any intermediate network and possible further infrastructure (not shown) as intermediaries. The OTT connection may be transparent in the sense that at least some of the participating communication devices through which the OTT connection passes are unaware of routing of uplink and downlink communications. The host computer may provide host applications which may be operable to provide a service to a remote user, such as a WD 110 connecting via an OTT connection terminating at the WD 110 and the host computer. In providing the service to the remote user, the host application may provide user data which is transmitted using the OTT connection. The “user data” may be data and information described herein as implementing the described functionality. In one embodiment, the host computer may be configured for providing control and functionality to a service provider and may be operated by the service provider or on behalf of the service provider. The host computer may be enabled to observe, monitor, control, transmit to and/or receive from the network node 160 and or the WD 110.

One or more of the various embodiments in this disclosure improve the performance of OTT services provided to the WD 110 using the OTT connection. More precisely, the teachings of some of these embodiments may improve the data rate, latency, and/or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc.

FIGURE 7A is a block diagram illustrating an example embodiment of a server for optimally sizing resources of a network node. The server is an example of server 12 illustrated in FIGURE 2. In particular embodiments, the server may be integrated with multiple databases and dynamically extracts the network attributes for a set of operators and markets. After data pre processing, feature mapping and engineering, particular embodiments analyze and interpret the data by applying clustering algorithms to find similarities and group the attributes to a known number of clusters.

The server includes processing circuitry 1102. Processing circuitry 1102 includes at least one processor 1120, at least one memory 1130, and at least one network interface 1140. In some embodiments, processor 1120 executes instructions to provide some or all of the functionality described herein. Memory 1130 stores the instructions executed by processor 1120. Network interface 1140 communicates signals to other network components, such as a gateway, switch, router, Internet, Public Switched Telephone Network (PSTN), controller, network nodes, and other servers.

Processor 1120 includes any suitable combination of hardware and software implemented in one or more integrated circuits or modules to execute instructions and manipulate data to perform some or all of the described functions of the server. In some embodiments, processor 1120 may include, for example, one or more computers, one more programmable logic devices, one or more central processing units (CPUs), one or more microprocessors, one or more applications, and/or other logic, and/or any suitable combination of the preceding. Processor 1120 may include analog and/or digital circuitry configured to perform some or all of the described functions of server 12. For example, processor 1120 may include resistors, capacitors, inductors, transistors, diodes, and/or any other suitable circuit components.

Memory 1130 is generally operable to store computer executable code and data. Examples of memory 1130 include computer memory (e.g., Random Access Memory (RAM) or Read Only Memory (ROM)), mass storage media (e.g., a hard disk), removable storage media (e.g., a Compact Disk (CD) or a Digital Video Disk (DVD)), and/or or any other volatile or non-volatile, non-transitory computer-readable and/or computer-executable memory devices that store information.

In some embodiments, network interface 1140 is communicatively coupled to processor 1120 and refers to any suitable device operable to receive input for server 12, send output from server 12, perform suitable processing of the input or output or both, communicate to other devices, or any combination of the preceding. Network interface 1140 includes appropriate hardware (e.g., port, modem, network interface card, etc.) and software, including protocol conversion and data processing capabilities, to communicate through a network.

Other embodiments of the server may include additional components (beyond those shown in FIGURE 7) responsible for providing certain aspects of the server’s functionality, including any of the functionality described above and/or any additional functionality (including any functionality necessary to support the solution described above).

FIGURE 8 is a flowchart illustrating an example method in a server for efficiently sizing resources of a network node, according to certain embodiments. In particular embodiments, one or more steps of FIGURE 8 may be performed by server 12 described with respect to FIGURE 2.

The method begins at step 812 where the server obtains network information for one or more operational wireless networks. For example, the server may obtain static information, such as one or more of spectrum holdings; geographical data of network nodes; and hardware configuration and/or dynamic information, such as one or more of key performance indicator (KPI) logs, traffic load information, and output power information. The server may obtain the network information according to any of the embodiments and examples described above. At step 814, the server may clean the obtained network information to remove or correct erroneous information.

At step 816, the server maps portions of the obtained network information to one or more related features of the plurality of features of the network node. For example, some network information may be relevant to some features but not others. As one example, some of the features like hardware information may be mapped to number of antennas. In some embodiments, the mapping may also include generating. For example, some of the features are generated like IBW from spectrum holding data.

At step 818, the server clusters the portions of the obtained network information for each feature of the plurality of features to find clusters of similar patterns, according to any of the embodiments and examples described herein (e.g., FIGURES 2-4).

At step 820, the server determines a plurality of network node types (K). Each network node type comprises network node resources for each feature of the network node. The network node resources are allocated according to a cluster of similar patterns for the feature. The server determines the network node types according to any of the embodiments and examples described herein (e.g., FIGURES 2 and 5).

At step 822, the server may generate network node product requirements based on the determined K network node types.

Modifications, additions, or omissions may be made to method 800 of FIGURE 8. Additionally, one or more steps in the method of FIGURE 8 may be performed in parallel or in any suitable order.

Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and/or is implied from the context in which it is used. All references to a/an/the element, apparatus, component, means, step, etc. are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and/or where it is implicit that a step must follow or precede another step. Any feature of any of the embodiments disclosed herein may be applied to any other embodiment, wherever appropriate. Likewise, any advantage of any of the embodiments may apply to any other embodiments, and vice versa. The foregoing description sets forth numerous specific details. It is understood, however, that embodiments may be practiced without these specific details. In other instances, well-known circuits, structures and techniques have not been shown in detail in order not to obscure the understanding of this description. Those of ordinary skill in the art, with the included descriptions, will be able to implement appropriate functionality without undue experimentation.

References in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. 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 implement such feature, structure, or characteristic in connection with other embodiments, whether or not explicitly described.

Although this disclosure has been described in terms of certain embodiments, alterations and permutations of the embodiments will be apparent to those skilled in the art. Accordingly, the above description of the embodiments does not constrain this disclosure. Other changes, substitutions, and alterations are possible without departing from the scope of this disclosure, as defined by the claims below.

Claims

CLAIMS:

1. A method (800) for use in a server for efficiently sizing resources of a network node, the network node comprising a plurality of features, the method comprising: obtaining (812) network information for one or more operational wireless networks; mapping (816) portions of the obtained network information to one or more related features of the plurality of features of the network node; clustering (818) the portions of the obtained network information for each feature of the plurality of features to find clusters of similar patterns; and based on the clustering results, determining (520) a plurality of network node types (K), wherein each network node type comprises network node resources for each feature of the network node and wherein the network node resources are allocated according to a cluster of similar patterns for the feature.

2. The method of claim 1, further comprising generating (822) network node product requirements based on the determined K network node types.

3. The method of any one of claims 1-2, further comprising cleaning (814) the obtained network information to remove or correct erroneous information.

4. The method of any one of claims 1-3, wherein the network information comprises static information.

5. The method of claim 4, wherein the static information includes one or more of spectrum holdings; geographical data of network nodes; and hardware configuration.

6. The method of any one of claims 1-2, wherein the network information comprises dynamic information.

7. The method of claim 6, wherein the dynamic information includes one or more of key performance indicator (KPI) logs, traffic load information, and output power information.

8. The method of any one of claims 1-7, wherein the clustering comprises any one or more of centroid-based clustering, density-based clustering, distribution-based clustering; spectral clustering, and MeanShift clustering.

9. The method of any one of claims 1-8, wherein determining the plurality of network node types (K) is optimized using one or more of the statistical testing methods Elbow and Silhouette.

10. The method of any one of claims 1-9, wherein the network node comprises a base station.

11. A server (1100) operable to efficiently size resources of a network node, the network node comprising a plurality of features, the server comprising processing circuitry (1102) operable to: obtain network information for one or more operational wireless networks; map portions of the obtained network information to one or more related features of the plurality of features of the network node; cluster the portions of the obtained network information for each feature of the plurality of features to find clusters of similar patterns; and based on the clustering results, determine a plurality of network node types (K), wherein each network node type comprises network node resources for each feature of the network node and wherein the network node resources are allocated according to a cluster of similar patterns for the feature.

12. The server of claim 11, the processing circuitry further operable to generate network node product requirements based on the determined K network node types.

13. The server of any one of claims 11-12, the processing circuitry further operable to clean the obtained network information to remove or correct erroneous information.

14. The server of any one of claims 11-13, wherein the network information comprises static information.

15. The server of claim 14, wherein the static information includes one or more of spectrum holdings; geographical data of network nodes; and hardware configuration.

16. The server of any one of claims 11-12, wherein the network information comprises dynamic information.

17. The server of claim 16, wherein the dynamic information includes one or more of key performance indicator (KPI) logs, traffic load information, and output power information.

18. The server of any one of claims 11-17, wherein the clustering comprises any one or more of centroid-based clustering, density-based clustering, distribution-based clustering; spectral clustering, and MeanShift clustering.

19. The server of any one of claims 11-18, wherein determining the plurality of network node types (K) is optimized using one or more of the statistical testing methods Elbow and Silhouette.

20. The server of any one of claims 11-19, wherein the network node comprises a base station.