WO2014160980A1

WO2014160980A1 - Interference alignment and cancellation for cognitive radio networks with secondary user access

Info

Publication number: WO2014160980A1
Application number: PCT/US2014/032256
Authority: WO
Inventors: Tianyi XU; Liangping Ma; Gregory S. Sternberg
Original assignee: InterDigital Patent Holdings Inc
Current assignee: InterDigital Patent Holdings Inc
Priority date: 2013-03-28
Filing date: 2014-03-28
Publication date: 2014-10-02
Anticipated expiration: 2015-09-28

Abstract

A wireless communication device may perform interference alignment and/or cancellation processes when accessing licensed wireless communicaiton spectrum in the role of a secondary user (SU) device of the licensed spectrum. The SU device may perform the interference alignment and/or cancellation processes such that communications of the SU device do not interfere with communications of a primary user (PU) device of the licensed spectrum, such that interference caused by communications of the PU device are mitigated at the SU device, and/or such that interference caused by respective communications of one or more other SU devices accessing the licensed spectrum are mitigated at the SU device. The SU device may communicate using a null space in the licensed spectrum that is associated with the SU device and the PU device. The SU device may use approximation algorithms in performing the interference alignment and/or cancellation processes.

Description

.INTERFERENCE ALIGNMENT AND CANCELLATION FOR COGNITIVE RADIO NETWORKS WITH SECONDARY USER ACCESS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. provisional patent application no,

61/806,366, filed March 2.8, 2013, which is incorporated herein by reference in its entirety.

BACKGROUND

[0002] As demand for wireless communication spectrum continues to increase, for example demand associated with applications executing on smart phones, spectrum shortages may occur. Spectrum shortages may detrimentally affect the performance of such applications. Techniques may be implemented to mitigate the impact of such spectrum shortages. One approach includes enabling wireless communication devices (e.g., smart phones) to leverage licensed wireless communication spectrum as secondary users of the spectrum.

[0003] Licensed wireless communication spectrum may typically be reserved for use by devices associated with a primary user (PU) of the spectrum (e.g., PU devices). However such spectrum may be made accessible for use by wireless communication devices (e.g., smart phones) that are not associated with the PU, for example by enabling one or more devices access to the spectrum as secondary users (SUs) of the spectrum.

[0004] In an example, an SU device may be configured to communicate using transmissions that are over the licensed spectrum and that are in the null space with respect to the SU device and a PU device of the licensed spectrum. The SU device may communicate using the null space such that SU communications do not interfere with communications of the PU. An SU device (e.g., having a cognitive radio) may be configured to determine characteristics of such a null space by performing a blind null-space learning (BNSL) algorithm.

[0005] An SU device communicating in a licensed wireless communication spectrum may observe interference. For example, an SU device may observe interference from communications of a PU device. Moreover, if one or more other SU devices are

communicating in the licensed wireless communication spectrum with an SLT device (e.g., using respective null spaces), the SU device may observe interference from communications of the one or more other SU devices. However, known interference mitigation techniques implemented for an SU device communicating in a licensed wireless communication spectrum fail to address interference observed at the SU device (e.g., are limited to mitigating interference by the SU device at the PU device).

SUMMARY

[0006] A wireless communication device may be configured to access licensed wireless communicaiton spectrum in the role of a secondary user (SU) device of the licensed spectrum. The SU device may communicate using a null space in the licensed spectrum that is associated with the SU device and with a primary user (PU) device of the licensed spectrum. The SU device may perform interference alignment and/or cancellation processes when communicating in the licensed spectrum, such that communications of the SU device do not interfere with communications of the PU device.

[0007] The SU device may perform interference alignment and/or cancellation processes such that interference observed at the SU device is mitigated (e.g., canceled). For example, the SU device may perform interference alignment and/or cancellation processes such that interference caused by communications of a PU device are mitigated at the SU device, and/or such that interference caused by communications of one or more other SU devices accessing the licensed spectrum are mitigated at the SU device. The SU device may be configured to use approximation algorithms in performing interference alignment and/or cancellation processes.

[0008] An example process of mitigating interference associated with access of a licensed spectrum by a secondary user (SU) device, and that may be performed by the SU device, may include determining first characteristics of a channel in the licensed spectrum between the SU device and a primary user (PU) device associated with the licensed spectrum. The first characteristics may pertain to a null space of the channel. The process may include deriving, based on the first characteristics, a preceding matrix. Application of the preceding matrix to a transmission by the SU device may cause the transmission to be within the null space of the channel, such that interference caused by the transmission, at the PU device, does not exceed a threshold interference level. The process may include applying the preceding matrix and/or the postcoding matrix to a signal transmitted by the SU device while accessing the licensed spectrum as a secondary user. [0009] The process may include determining second charac eristics of the channel in the licensed spectrum. The process may include receiving channel matrix information pertaining to a second SU device that is accessing the licensed spectrum. The process may include deriving a postcoding matrix. The postcoding matrix may he derived based on the second characteristics and or on the channel matrix information. The process may include applying the postcoding matrix to a signal received by the SU device while accessing the licensed spectrum as a secondary user.

[0010] A wireless transmit/receive unit (WTRU) may include a processor. The processor may be configured to, when the WTRU accesses licensed spectrum as a secondary user of the licensed spectrum, determine first characteristics of a channel in the licensed spectrum between the WTRU and a primary user (PU) device associated with the licensed spectrum. The first characteristics may pertain to a null space of the channel. The processor may be configured to derive, based on the first characteristics, a preceding matrix.

Application of the preceding matrix to a transmission by the WTRU may cause the transmission to be within the null space of the channel, such that interference caused by the transmission, at the PU device, does not exceed a threshold interference level. The processor may be configured to cause the VV^'T^'RU to apply the preceding matrix to a signal transmitted by the WTRU while accessing the licensed spectrum as a secondary user.

[0011 ] The processor may be configured to determine second charac teristics of the channel in the licensed spectrum. The processor may be configured to receive channel matrix information pertaining to a second VV^'T^'RU that is accessing the licensed spectrum. The processor may be configured to derive a postcoding matrix. The postcoding matrix may be deri ved based on the second characteristics and/or on the channel matrix information. The processor may be configured to apply the postcoding matrix to a signal received by the WTRU while accessing the licensed spectrum as a secondary user.

BRIEF DESCRIPTION OF THE DRAWINGS

[0012] FIG. 1A depicts a system diagram of an example communications system in which one or more disclosed embodiments may be implemented.

[0013] F G. IB depicts a system diagram of an example wireless transmit/receive unit

(WTRU) that may be used within the communications system illustrated in FIG. 1 A. [0014] FIG. 1C depicts a system diagram of an example radio access network and an example core network that may be used within the communications system illustrated in FIG. 1A.

[0015] FIG. ID depicts a system diagram of an example radio access network and an example core network that may be used within the communications system illustrated in FIG. 1A.

[0016] FIG. IE depicts a system diagram of an example radio access network and an example core network that may be used within the communications system illustrated in FIG. 1A.

[0017] FIG. 2 is a graph depicting sum rates of a simulated example interference alignment and/or cancellation process using an HA algorithm.

[0018] FIG. 3 is a graph depicting sum rates of a simulated example interference alignment and/or cancellation process using a Max-SINR algorithm.

[0019] FIG. 4 is a graph depicting bit error rates of a simulated example interference alignment and/or cancellation process using an IIA algorithm.

[0020] FIG. 5 is a graph depicting bit error rates of a simulated example interference alignment and/or cancellation process using a Max-SINR algorithm.

DETAILED DESCRIPTION

[0021] FIG. 1A is a diagram of an example communications system 100 in which one or more disclosed embodiments may be implemented. The communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communications system 100 may enable multiple wireless users to access such content through the sharing of system resources, including wireless bandwidth. For example, the communications systems 100 may employ one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single-carrier FDMA (SC-FDMA), and the like.

[0022] As shown in FIG. 1A, the communications system 100 may include at least one wireless transmit/receive unit (WTRl^j), such as a plurality of WTRUs, for instance WTRUs 102a, 102b, 102c, and 102d, a radio access network (RAN) 104, a core network 106, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112, though it should be appreciated that the disclosed embodiments contemplate any number of WT Us, base stations, networks, and/or network elements. Each of the WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and'Or communicate in a wireless environment. By way of example, the WTRUs 102a, 102b, 102c, 102d may be configured to transmit and/or receive wireless signals and may include user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a netbook, a personal computer, a wireless sensor, consumer electronics, and the like.

[0023] The communications systems 100 may also include a base station 1 14a and a base station 1 14b. Each of the base stations 1 14a, 1 14b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d to facilitate access to one or more communication networks, such as the core network 106, the Internet 1 10, and/or the networks 1 12. By way of example, the base stations 1 14a, 1 14b may be a base transceiver station (BTS), a Node-B, an eNode B, a Home Node B, a Home eNode B, a site controller, an access point (AP), a wireless router, and the like. While the base stations 1 14a, 1 14b are each depicted as a single element, it should be appreciated that the base stations 1 14a, 1 14b may include any number of interconnected base stations and/or network elements.

[0024] The base station 1 14a may be part of the RAN 104, which may also include other base stations and/or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc. The base station 1 14a and'Or the base station 1 14b may be configured to transmit and/or receive wireless signals within a particular geographic region, which may be referred to as a cell (not shown). The cell may further be divided into cell sectors. For example, the cell associated with the base station 1 14a may be divided into three sectors. Thus, in one embodiment, the base station 1 14a may include three transceivers, i.e., one for each sector of the cell. In another embodiment, the base station 1 14a may employ multiple-input multiple output (MIMO) technology and, therefore, may utilize multiple transceivers for each sector of the cell.

[0025] The base stations 1 14a, 1 14b may communicate with one or more of the

WTRUs 102a, 102b, 102c, 102d over an air interface 1 16, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 1 16 may be established using any- suitable radio access technology (RAT). [0026] More specifically, as noted above, the communications system 100 may be a multiple access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDM A, SC-FDMA, and the like. For example, the base station 1 14a in the RAN 104 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 1 16 using wideband CDMA (WCDMA). WCDMA may include communication protocols such as High-Speed Packet Access (HSPA) and/or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink Packet Access (HSDPA) and/or High-Speed Uplink Packet Access (HSUPA).

[0027] In another embodiment, the base station 1 4a and the WTRUs 102a, 102b,

102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E- UTRA), which may establish the air interface 1 16 using Long Term Evolution (LTE) and/or LTE-Advanced (LTE-A).

[0028] in other embodiments, the base station 1 14a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2G00 IX, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), and the like.

[0029] The base station 114b in FIG. 1A may be a wireless router, Home Node B,

Home eNode B, or access point, for example, and may utilize any suitable RAT for facilitating wireless connectivity in a localized area, such as a place of business, a home, a vehicle, a campus, and the like. In one embodiment, the base station 1 14b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN). In another embodiment, the base station 1 14b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN). In yet another embodiment, the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, etc.) to establish a picocell or temtocell. As shown in FIG. 1 A, the base station 1 14b may have a direct connection to the Internet 1 10. Thus, the base station 1 14b may not be required to access the Internet 1 10 via the core network 106,

[0030] The RAN 104 may be in communication with the core network 106, which may be any type of network configured to provide voice, data, applications, and/or voice over internet protocol (VoIP) services to one or more of the WTRUs l()2a, l()2b, 102c, 102d. For example, the core network 106 may provide cali control, billing services, mobile location- based services, pre-paid calling, Internet connectivity, video distribution, etc, and/or perform high-level security functions, such as user authentication. Although not shown in FIG. 1A, it should be appreciated that the RAN 104 and/or the core network 106 may be in direct or indirect communication with other RA s that employ the same RAT as the RAN 104 or a different RAT. For example, in addition to being connected to the RAN 104, which may be utilizing an E-UTRA radio technology, the core network 106 may also be in communication with another RAN (not shown) employing a GSM radio technology.

[0031 ] The core network 106 may also serve as a gateway for the WTRUs 102a,

102b, 102c, 102d to access the PSTN 108, the Internet 1 10, and/or other networks 1 12. The PSTN 108 may include circuit-switched telephone networks that provide plain old telephone service (POTS). The Internet 1 10 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the transmission control protocol (TCP), user datagram protocol (UDP) and the internet protocol (IP) in the TCP/IP internet protocol suite. The networks 1 12 may include wired or wireless communications networks owned and/or operated by other service providers. For example, the networks 1 12 may include another core network connected to one or more RANs, which may employ the same RAT as the RAN 104 or a different RAT.

[0032] Some or ail of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities, i.e., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links. For example, the WTRU 102c shown in FIG. 1A may be configured to communicate with the base station 1 14a, which may employ a cellular-based radio technology, and with the base station 1 14b, which may employ an IEEE 802 radio technology.

[0033] FIG. IB is a system diagram of an example WTRU 102. As shown in FIG,

I B, the WTRU 102 may include a processor 1 18, a transceiver 12.0, a transmit/receive element 122, a speaker/microphone 124, a keypad 126, a display/touchpad 128, nonremovable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and other peripherals 138. It should be appreciated that the WTRU 102 may include any sub-combination of the foregoing elements while remaining consistent with an embodiment. [0034] The processor 1 18 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific integrated Circuits (ASICs), Field Programmable Gate Array (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like. The processor 118 may perform signal coding, data processing, power control, input/output processing, and/or any other functionality that enables the W^'T^'RU 102 to operate in a wireless environment. The processor 1 18 may be coupled to the transceiver 120, which may be coupled to the transmit/receive element 122. While FIG. IB depicts the processor 1 18 and the transceiver 120 as separate components, it should be appreciated that the processor 1 18 and the transceiver 120 may be integrated together in an electronic package or chip.

[0035] The transmit/receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 1 14a) over the air interface 1 16. For example, in one embodiment, the transmit receive element 122 may be an antenna configured to transmit and/or receive RF signals. In another embodiment, the

transmit/receive element 122 may be an emitter/detector configured to transmit and/or receive TR, UV, or visible light signals, for example, ΐη yet another embodiment, the transmit/receive element 122 may be configured to transmit and receive both RF and light signals. It should be appreciated that the transmit/receive element 122 may be configured to transmit and/or receive any combination of wireless signals.

[0036] In addition, although the transmit/receive element 122 is depicted in FIG. IB as a single element, the WTRU 102 may include any number of transmit/receive elements 122. More specifically, the WTRU 102. may employ MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit/receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 1 16.

[0037] The transceiver 120 may be configured to modulate the signals that are to be transmitted by the transmit/receive element 122 and to demodulate the signals that are received by the transmit/receive element 122. As noted above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers for enabling the WTRU 102 to communicate via multiple RATs, such as UTRA and IEEE 802.1 1, for example. [0038] The processor 1 18 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker/microphone 12.4, the keypad 126, and/or the display/touchpad 128 (e.g., a liquid crystal display (LCD) display unit or organic light-emitting diode (OLED) display unit). The processor 1 18 may also output user data to the speaker/microphone 124, the keypad 126, and/or the display/touchpad 128. In addition, the processor 1 18 may access information from, and store data in, any type of suitable memory , such as the non-removable memory 130 and/or the removable memory 132. The non-removable memory 130 may include random-access memory (RAM), read-only memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132. may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other embodiments, the processor I I 8 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as on a server or a home computer (not shown).

[0039] The processor 1 18 may receive power from the power source 134, and may be configured to distribute and/or control the power to the other components in the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry cell batteries (e.g., nickel- cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar ceils, fuel cells, and the like.

[0040] The processor 1 18 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to, or in lieu of, the information from the GPS chipset 136, the WTRU 102 may receive location information over the air interface 1 16 from a base station (e.g., base stations 1 14a, 1 14b) and/or determine its location based on the timing of the signals being received from two or more nearby base stations. It should be appreciated that the WTRU 102 may acquire location information by way of any suitable location- determination method while remaining consistent with an embodiment.

[0041] The processor 1 18 may further be coupled to other peripherals 138, which may include one or more software and/or hardware modules that provide additional features, functionality and/or wired or wireless connectivity. For example, the peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (for photographs or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands free headset, a Bluetooth© module, a frequency modulated (FM) radio unit, a digital music player, a media player, a video game player module, an Internet browser, and the like.

[0042] FIG. 1 C is a system diagram of an embodiment of the communications system

100 that includes a RAN 104a and a core network 106a that comprise example

implementations of the RAN 104 and the core network 106, respectively. As noted above, the RAN 104, for instance the RAN 104a, may employ a UTRA radio technology to communicate with the W^'T^'RUs 102a, 102b, and 102c over the air interface ί 16. The RAN 104a may also be in communication with the core network 106a. As shown in FIG. 1 C, the RAN 104a may include Node-Bs 140a, 140b, 140c, which may each include one or more transceivers for communicating with the W^'T^'RLis 102a, 102b, 102c over the air interface 1 16. The Node-Bs 140a, 140b, 140c may each be associated with a particular cell (not shown) within the RAN 104a. The RAN 104a may also include RNCs 142a, 142b. It should be appreciated that the RAN 104a may include any number of Node-Bs and RN Cs while remaining consistent with an embodiment.

[0043] As shown in FIG. 1C, the Node-Bs 140a, 140b may be in communication with ihe RNC 142a. Additionally, the Node-B 140c may be in communication with the RNC 142b. The Node-Bs 140a, 140b, 140c may communicate with the respective RNCs 142a, 142b via an Tub interface. The RNCs 142a, 142b may be in communication with one another via an Iur interface. Each of the RNCs 142a, 142b may be configured to control the respective Node-Bs 140a, 140b, 140c to which it is connected. In addition, each of the RNCs 142a, 142b may be configured to carry out or support other functionality, such as outer loop power control, load control, admission control, packet scheduling, handover control, macrodiversity, security functions, data encryption, and the like.

[0044] The core network 106a shown in FIG. 1C may include a media gateway

(MGW) 144, a mobile switching center (MSC) 146, a serving GPRS support node (SGSN) 148, and or a gateway GPRS support node (GGSN) 150. While each of the foregoing elements is depicted as part of the core network 106a, it should be appreciated that any one of these elements may be owned and/or operated by an entity other than the core network operator.

[0045] The RNC 142a in the RAN 104a may be connected to the MSC 146 in the core network 106a via an IuCS interface. The MSC 146 may be connected to the MGW 144. The MSC 146 and the MGW 144 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate cominunications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices.

[0046] The RNC 142a in the RAN 104a may also be connected to the SOSN 148 in the core network 106a via an IuPS interface. The SGSN 148 may be connected to the GGSN 150. The SGSN 148 and the GGSN 150 may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between and the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0047] As noted above, the core network 106a may also be connected to the networks

1 12, which ma include other wired or wireless networks that are owned and'or operated by other service providers.

[0048] FIG. I D is a system diagram of an embodiment of the communications system

100 that includes a RAN 104b and a core network 106b that comprise example

implementations of the RAN 104 and the core network 106, respectively . As noted above, the RAN 104, for instance the RAN 104b, may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, and 102c over the air interface 1 16. The RAN 104b may also be in communication with the core network 106b.

[0049] The RAN 104b may include eNode-Bs 140d, 140e, 140f, though it should be appreciated that the RAN 104b may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 14()d, 140e, 14()f may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 1 16. In one embodiment, the eNode-Bs 140d, 140e, 140f may implement MIMQ technology. Thus, the eNode-B 140d, for example, may use multiple antennas to transmit wireless signals to, and receive wireless signals from, the WTRU 102a.

[0050] Each of the eNode-Bs 140d, I40e, and 140f may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the uplink and/or downlink, and the like. As shown in FIG. ID, the eNode-Bs 140d, 140e, 140f may communicate with one another over an X2 interface.

[0051] The core network 106b shown in FIG, ID may include a mobility

management gateway (MME) 143, a serving gateway 145, and a packet data network (PDN) gateway 147. While each of the foregoing elements is depicted as part of the core network 106b, it should be appreciated that any one of these elements may be owned and/or operated by an entity other than the core network operator. [0052] The MME 143 may be connected to each of the eNode-Bs 140d, 140e, and

140f in the RAN 104b via an SI interface and may serve as a control node. For example, the MME 143 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation/deactivation, selecting a particular serving gateway during an initial attach of the WTRUs 102a, 102b, 102c, and the like. The MME 143 may also provide a control plane function for switching between the RAN 104b and other RANs (not shown) that employ other radio technologies, such as GSM or WCDMA.

[0053] The serving gateway 145 may be connected to each of the eNode Bs 140d,

140e, 140f in the RAN 104b via the S I interface. The serving gateway 145 may generally route and forward user data packets to/from the WTRUs 102a, 102b, 102c, The serving gateway 145 may also perform other functions, such as anchoring user planes during inter- eNode B handovers, triggering paging when downlink data is available for the WTRUs 102a, 102b, 102c, managing and storing contexts of the WTRUs 102a, 102b, 102c, and the like.

[0054] The serving gateway 145 may also be connected to the PDN gateway 147, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 1 10, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0055] The core network 106b may facilitate communications with other networks.

For example, the core network 106b may provide the WTRUs 102a, 102b, 102c with access to circuit- switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices. For example, the core network 106b may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the core network 106b and the PSTN 108. In addition, the core network 106b may provide the WTRUs 102a, 102b, 102c with access to the networks 112, which may include other wired or wireless networks that are owned and/or operated by other service providers.

[0056] FIG. IE is a system diagram of an embodiment of the communications system

100 that includes a RAN 104c and a core network 106c that comprise example

implementations of the RAN 104 and the core network 106, respectively. The RAN 104, for instance the RAN 104c, may be an access sei'vice network (ASN) that employs IEEE 802.16 radio technology to communicate with the WTRUs 102a, 102b, and 102c over the air interface 1 16. As described herein, the communication links between the different functional entities of the WTRUs 102a, 102b, 102c, the RAN 104c, and the core network 106c may be defined as reference points.

[0057] As shown in F G. I E, the RAN 104c may include base stations 140g, 140h,

140i, and an ASN gateway 141, though it should be appreciated that the RAN 104c may- include any number of base stations and ASN gateways while remaining consistent with an embodiment. The base stations 140g, 140h, 1401 may each be associated wiih a particular cell (not shown) in the RA 104c and may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 1 16. In one embodiment, the base stations 140g, 140h, 140i may implement MIMO technology . Thus, the base station 140g, for example, may use multiple antennas to transmit wireless signals to, and receive wireless signals from, the WTRU 102a, The base stations 140g, 140b, 140i may also provide mobility management functions, such as handoff triggering, tunnel

establishment radio resource management traffic classification, quality of service (QoS) policy enforcement, and the like. The ASN Gateway 141 may serve as a traffic aggregation point and may be responsible for paging, caching of subscriber profiles, routing to the core network 106e, and the like,

[0058] The air interface 1 16 between the WTRUs 102a, 102b, 102c and the RAN

104c may be defined as an Rl reference point that implements the IEEE 802.16 specification. In addition, each of the WTRUs 102a, 102b, and 102c may establish a logical interface (not shown) with the core network 106c. The logical interface between the WTRUs 102a, 102b, 102c and the core network 106c may be defined as an R2 reference point, which may be used for authentication, authorization, IP host configuration management, and/or mobility management.

[0059] The communication link between each of the base stations 140g, 140h, 1401 may be defined as an R8 reference point that includes protocols for facilitating WTRU handovers and the transfer of data between base stations. The communication link between the base stations 140g, 140h, 1401 and the ASN gateway 141 may be defined as an R6 reference point. The R6 reference point may include protocols for facilitating mobility management based on mobility events associated with each of the WTRU s 102a, 102b, 102c.

[0060] As shown in FIG. IE, the RAN 104c may be connected to the core network

106c. The communication link between the RAN 104c and the core network 106c may defined as an R3 reference point that includes protocols for facilitating data transfer and mobility management capabilities, for example. The core network 106c may include a mobile IP home agent (MIP-HA) 144, an authentication, authorization, accounting (AAA) server 156, and a gateway 158. While each of the foregoing elements is depicted as part of the core network 106c, it should be appreciated that any one of these elements may be owned and/or operated by an entity other than the core network operator.

[0061 ] The MIP-HA may be responsible for IP address management, and may enable the WTRUs 102a, 102b, and 102c to roam between different ASNs and/or different core networks. The MIP-HA 154 may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 1 10, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The AAA server 156 may be responsible for user authentication and for supporting user services. The gateway 158 may facilitate interworking with other networks. For example, the gateway 158 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional landline communications devices. In addition, the gateway 158 may provide the WTRUs 102a, 102b, 102c with access to the networks 1 12, which may include other wired or wireless networks thai are owned and/or operated by other service providers,

[0062] Although not shown in FIG. 1 E, it should be appreciated that the RAN 104c may be connected to other ASNs and the core network 106c may be connected to other core networks. The communication link between the RAN 104c the other ASNs may be defined as an R4 reference point, which may include protocols for coordinating the mobility of the WTRUs 102a, 102b, 102c between the RAN 104c and the other ASNs. The communication link between the core network 106c and the other core networks may be defined as an R5 reference point, which may include protocols for facilitating interworking between home core networks and visited core networks.

[0063] A wireless communication device (e.g., one or more of the WTR.U 102a,

102b, or 102c) may be configured to perform interference alignment and/or cancellation processes when accessing licensed wiereless communication spectrum in the role of a secondary user (SU) device relative to the wireless communication spectrum. The wireless communication device may include a cognitive radio and/or a multiple input multiple output (MIMO) antenna configuration. Multiple wireless communication devices (e.g., two or more) thai include respective MIMO antenna configurations, and that are enabled to access licensed wireless communicatoin spectrum as SU devices, may be configured to participate in a MIMO underlay cognitive radio network. [0064] In an example of multiple SU devices participating in such a network, one or more of the SU de vices in the network may perform interference alignment and/or cancellation processes, which may restrict their communications in null spaces of respective channels in the licensed spectrum between the SU devices and the device of a primary user of the licensed spectrum (e.g., a PU device). The SU device may perform interference alignment and/or cancellation processes to mitigate (e.g., align and/or cancel) interference observed at the PU device that is caused by the SU device, to mitigate (e.g., align and/or cancel) interference observed at the SU device that is caused by the PU device, and/or to mitigate interference observed at the SU device ihai is caused by one or more other SU devices in the network. Mitigating interference by performing such interference alignment and/or cancellation processes may improve (e.g., optimize) performance of a wireless communication device accessing licenesed wireless communication spectrum in the role of an S U device. Interference alignment of communications by one or more S U devices may inlcude one or more of spatial alignment in the null space (e.g., using MIMO antennas), temporal alingment relative to the null space, or alignment in the nidi space with respect to frequency.

[0065] As used herein, a user device (e.g., an SU device or a PU device) may include a transmitter-rece ver pair, where the transmitter is configured to communicate with the receiver. With respect to a primary user device (PU device), a transmitter of the PU device may be referred to as a PU transmitter and a receiver of the PU device may be referred to as a PU receiver. With respect to a secondary user device (SU device), a transmitter of the S U device may be referred to as an SU transmitter and a receiver of the SU device may be referred to as an SU receiver.

[0066] In an example MIMO underlay cognitive radio network, an SU device may be configured to determine characteristics of a null space in a channel that associates the SU device with a PU device. This may be performed by each SU device in the example MIMO underlay cognitive radio network.

[0067] To i] Instate, an SU device may perform a null space sensing process that assumes channel reciprocity between a transmitter of an SU device (e.g., SU transmitter) and a receiver of the PU device (e.g., PU receiver). The SU device may learn from the signal of the PU device, and'or may estimat e the null space of the channel from the SU transmitter to the PU receiver based on second order statistics of the signal. Assuming channel reciprocity may limit the applicability of such a process to networks (e.g., communications systems) that use time division duplexing (TDD).

[0068] in another example, an SU device may perform a blind null-space {earning

(BNSL) algorithm that may be implemented without cooperation by the PU device. This may be implemented, for example, where reciprocity does not exist for the channel between the SU transmitter and the PU receiver. One or more SU devices may perform BNSL algorithms without the PU device having knowledge of the one or more SU devices.

[0069] An SU device may transmit a test signal, for example in the channel between the SU device and the PU device. The PU de v ice may respond to receipt of the test signal. For example, the PU transmitter may apply power control to adapt a transmit power of the PU device, for instance in order to keep a signal to interference plus noise ratio (SINR) at the PU receiver substantially unchanged. The SU device (e.g., the SU receiver) may monitor (e.g., sense) for the transmit power level adjustment of the PU transmitter. The SU device may infer channel state information of the channel from the SU transmitter to the PU receiver (e.g., estimate characteristics of the null space of the channel) blindly, based on the transmit power change at the PU device. Performance of the BNSL algorithm may enable the SU device to mitigate the generation of interference by the SU device at the PU device.

[0070] An SU device may be configured to employ one or more spatial dimensions provided by the use of a multiple antenna configuration (e.g., a MIMO configuration) to facilitate restricting signals generated by the SU device to the null space of the channel from the SU transmitter to the PU receiver. Such an SU device may be configured to estimate the null space of the channel in the absence of cooperation of the PU device, for example where the PU device does not provide explicit feedback to the SU transmitter.

[0071 ] In accordance with an example MIMO underlay cognitive radio network that includes multiple SU devices configured to communicate using licensed spectmm, the SU devices may be allowed to communicate using the licensed spectmm (e.g., to transmit messages in the licensed spectrum) if the detrimental impacis of such communications on the performance of the PU device does not exceed a threshold (e.g., a predetermined threshold). To illustrate, one or more SU devices may be allowed to communicate using the licensed spectrum if interference caused by the transmissions, at the PU device, do not exceed a threshold interference level The threshold interference level may be based on a policy requirement, for example in accordance a policy imposed by a regulatory body, such as the FCC. [0072] One or more SU devices participating in a cognitive radio network (e.g., a

MIMO underlay cognitive radio network), for example each SU device, may be configured to perform interference alignment and/or cancellation processes that may mitigate interference at an associated PU device, and/or may improve (e.g., optimize) the performance of one or more of the SU devices (e.g., by maximizing degrees of freedom for SU device

communication in the licensed spectrum). In an example, when a first SU device communicates in the licensed spectrum, for example substantially concurrently with a PU device and one or more other SU devices, interference observed at the first SU device from one or more of the other SU de vices may be mitigated (e.g., aligned and/or canceled), and/or interference observed at the first SU device from the PU device may be mitigated (e.g. , canceled). Perfromance of interference alignment and/or cancellation processes may mitigate interference, for example, in the spatial domain. An SU device may use approximation algorithms in the performance of interference alignment and/or cancellation processes.

[0073] Perfmoring an alignment and/or cancellation process in a congitive radio network (e.g., by one or more SU devices) may be reduced to an interference alignment problem that may not distinguish whether the device is a PU de vice or an SU de vice, for example if M_k > N_p and N_ic > M_p, and may not have a solution otherwise, Vfc = 1, ... , K, where M_k is the number of antennas at the SU transmitter k, N_k is the number of antennas at the SU receiver k, M_p is the number of antennas at the PU transmitter, N_p is the number of antennas at the PU receiver, and K is the number of SU devices in the network

[0074] In an equivalent interference alignment problem, the network may include K devices, the number of antennas at transmitter k may be M_k— N_p, the number of antennas at receiver k may be N_k --- M_p , V/c = 1, ... , K, and the channel may be transformed from that of the underlay cognitive radio network (e.g., in a particular way). Approximatio algorithms may be used, for example in accordance with the NP-hardness of the interference alignment and cancellation problem. These processes may be referred to as an underlay approach because of the existence of interference, which may be insignificant interference, caused by the SU device at the PU device during the blind null-space learning process.

[0075] An example underlay cognitive radio network (e.g., a MIMO underlay cognitive radio network) may include a PU transmitter-receiver pair (e.g., a PU device) and K SU transmitter-receiver pairs (e.g., a quantity K of SU devices). One or more of the SU devices (e.g., each SU device in the network) may be configured to transmit when resulting interference at the PU receiver does not exceed a threshold level of interference. The PU device may be configured such that the PU device does not cooperate with ihe SU devices. One or more of the SU devices (e.g., each SU device in the network) may be configured to cooperate with one or more other SU devices of the network. This may improve performance of the SU devices. The PU transmitter and the PU receiver may be equipped with M_p and N_p antennas, respectively. The SU transmitter k and the SU receiver k may be equipped with M_k and N_k antennas, V c = 1, ... , K, respectively. A channel model for the PU receiver may be expressed as: p = ^ΗρΛ +∑k=i ^Hpfe^Xfc + ⁷-'v

where Y_P 6 C'^VP^{x 1} is (he received signal vector at the PU receiver; E_PP e C^{N XM}P represents the channel matrix between the PU transmitter and the PU receiver and E_PK € ^NP^XMK' represents the channel matrix between the k-t SU transmitter and the PU receiver, whose respective entries are assumed i. .d. with circular normal distribution CJf (0,1); X_p E ^MP ^{X 1} represents signal vectors transmitted by the PU transmitter and X_¾€ C ^{FC X L} represents signal vectors transmitted by the k-t SU transmitter; and Z_p 6 C^NP^{X 1} is an additive white Gaussian noise vector with i.i.d. CJf (0,1) entries. A received signal at the j-th SU receiver may be expressed as follows:

Y_j = tt_jpXp + H-_feX_fe + Z_j, j = 1, ... , K

[0076] In accordance with an example interference alignment and/or cancellation process (e.g., ihai may be performed by an SU device, such as a WT U/UE), an interference alignment and cancellation problem may be formulated. To illustrate, in accordance with the example underlay cognitive radio network as expressed in equations (1) and (2), the following may be set: X_fe = V_fes¾, where V¾ represents the M_k x d_k transmit matrix at the k- th SU transmitter, and s_k represents the d_k x 1 symbol vector transmitted by the fe-th SU device with i.i.d. elements and an identity covariance matrix. In accordance with the example, s may not follow a normal distribution. It may be assumed that the columns ofV_fc are orthonormal, setting V V¾ = In accordance with the example, U_fe may respresent the N_k X d_k interference cancellation matrix at the k- h SU receiver, where the columns of U_fc are orthonormal, such that U¾U_fc " l_d . In accordance with the example, equations (T) and (2) may be rewritten as equations (3) and (4), respectively, as follows: - U i !,_;)X„ + j; , u;U_|A.V_A.s_A. + UJZ_j

[0077] An example interference alignment and/or cancellation problem, that may be referred to as Problem- 1, may then be: given degrees of freedom (d₁₍ . . . , d_K), determine the matrices V_fc and U_k such that the transmission of the FU device is not affected by the SU devices (e.g., by inteference from the SU devices), setting E_pkV_k = 0, Vfc = 1 ,2,— , K, where 0 represents an all-zero matrix of approriate size and the interference at an SU device caused by the PU device and/or by one or more other SU devices in the netowrk may be mitigaied (e.g., aligned and/or canceled) by the interference cancellation matrix, setting U H,-_p = 0, and UjH_jkV_k = 0, for Vk≠ j, where k = l,2,- -,K If a feasible /Γ -tuple (d_lf ... , d_K) is chosen, so as to improve (e.g., maximize) the sum of degrees of freedom d_k, the solution to the above problem may become an optimization problem. Such d_k 's may be determined using interference alignment feasibility conditions, for example.

[0078] The condition H_pfcV_fe = 0 may imply that one or more SU device

transmissions X¾ = V_ks_k are in the null space of H_pk, denoted as N(H_plc) = {v £

C^M*^X1 : H_wfev = 0], which may be nontrivial (e.g., containing more than the all-zero vector) if M_k > N_v .

[0079] One or more SU devices of the example underlay cognitive radio network may be configured to determine one or more characteristics of the null spaces of respective channels between the SU devices and the PU devics, for example when the PU device does not cooperate with the SU devices, and/or when the P U device is not aware of the existence of the SU devices. For example, an S U device may be configured to determine

characteristics (e.g, channel state information) of a channel in the licensed spectrum between the SU device and the PU device by performing a blind null-space learning (BNSL) algorithm. The null spaces characteristics determined by the SU device may be referred to as first characteristics determined in an example interference alignment and/or cancellation process. One or more SU devices (e.g., each SU device) in the example underlay cognitive radio network may be configured to determine first characteristics of the null spaces of corresponding channels between the SU devices and the PU device.

[0080] An example BNSL algorithm may be based on a first assumption that the PU transmitter is configitred to adapt its transmission power to maintain a required SINR at the PU receiver (e.g., if interference from the SU device is observed at the PU receiver), and a second assumption that one or more of ihe SU transmitters are configured to detect changes in the transmission power level of the PU transmitter. The example BNSL algorithm may be based on the null space of H_pk being the same as the null space of G_pk ~ H^* _{¾ pk} , which may be determined, for example, by blind Jacobi eigenvalue decomposition without observing G_pk itself or the rotated G_pk in the iterative Jacobi eigenvalue decomposition process.

[0081 ] The example BNSL algorithm may begin with A₀— G_pJ>, and each iteration of the algorithm may contain M_k (M_k ^■■■■ i)/2 learning stages. In each learning stage, the algorithm may perform line searches, for example by sending different training signals to obtain a rotation matrix R_; in order to update the matrix A> as A>₊₁ = R]A> Rj , such that two off-diagonal elements of A_i+1 are eliminated. After an iteration of M_k (M_k ^■■■■ i)/2 learning stages, each off-diagonal element of G_rik may be eliminated once. The algorithm may perform several iterations to improve ihe accuracy, and at the end, may obtain a matrix A = R^*G_?3¾ R, where the off- diagonal elements of A may be close to 0 and R may be the multiplication of the rotation matrices R_j. As a result, R may be an estimate of the eigenspace of G_pk, while the null space of G_pk may be the eigenvector space corresponding to the eigenvalues equal to 0. This example BNSL algorithm may be applied to a single SU device, and may be generalized to multiple secondary user systems, for example if in the fine searches one SLT device changes its training signal at each time.

[0082] Once the SU devices of the example MIMO underlay cognitive radio network learn the respective null spaces of the channels H_pk, transmissions from ihe SU devices may be restricted to be within the null spaces of the respective channels to the PU device. This may satisfy a constraint that transmissions of the SU de vices are not to affect the PU de vice, for example that transmissions of the SU devices are not to interfere with transmissions by the PU device.

[0083] Interference alignment feasibility conditions may be considered. For example, the received signal expressed in equation (3) at the PU receiver may be considered. By applying the BNSL, one or more SU deivces (e.g., each SU device) may obtain a

corresponding null space N^" (¾¾.). If the columns of the beamforming matrix V_k from the null space for each SU device are selected, the interference at the PU receiver may be mitigated (e.g., canceled), since H_pfcV_fe = 0, Vk. Stated differently, transmissions of the SU devices may not affect the PU device. To find V_fe, the dimensions of the null space should not be less than the dimensions of the signal vector, for example setting M_k — N_p≥ d._k. In order to ensure H_pkV_k = 0, V/c, it may be set V_k = B_k P_k, where B_k is a M_k X (M_k— N_p) matrix and the column vectors of B_k form an orthonormal basis of the null space 3 (H_pJ>), and where P_k is a (M_k— N_p) X d_k matrix such that P P_k = \_dk.

[0084] The received signal expressed in equation (4) at the SU receivers may be considered. Signals sent by the PU transmitter may cause interference at the SU devices. If an SU receiver knows the training sequence of the PU device, it may estimate an interference channel Hj_p> for example by overhearing the transmission of the training sequence from the PU transmitter to the PU receiver. To illustrate, if an SU device performs a cell search function (e.g., the cell search function of LTE), the SU device may determine a cell identity that is mapped to a cell specific downlink training signal (e.g., a reference signal). Based on this information, the SU device may estimate the interference channel H_;p . This process may be performed without cooperation by the PU device. Information pertaining to the

interference channel H_it! may be referred to as second characteristics of the channel from the PU device to the SU device. An SU device may use such second characteristics in deriving a postcoding matrix that may be used to mitigate interference from the PU device observed at the SU device. For example, assuming that the interference channel Η._ρ is known at the jt SU receiver, the jth. SU receiver may apply an Nj X (iV,— M_p ) interference suppression matrix W,-, satisfying W' H_j-,, = 0, which may mitigate (e.g., cancel) the interference from the PU device, for example as follows:

W/Y_y

W_j H_jkV_ks_k + W/Z,- where the column vectors of W,- are orthonormal. Such W_;- may be constructed, for example, from the null space of H^* _p, because the requirement \'V ^*H_ip = 0 is equivalent to H^W) = 0. Since the entries of H,-._B may be drawn from a continuous distribution, its columns may be linearly independent with probability 1 if N_j— M_p > 0, To find such W) , the null space of Η,-ρ may be nontrivial (e.g., the dimension of the null space Nj— M_p > 0).

[0085] It may be set Y) = W'- Y) , Z_j = \V^*Z_j, and

H_jk = \V; Hj_kB_k (6) where W.- 6 Λ^Γ(Η^* _Τ1) and B_fc £ JST(]-]_p ). The received signal at the j-th SU device may then be rewritten as =∑*=i ¾¾¾ + Z_j, j = l, ... , K which may be regarded as an -interference channel of a network of K SU devices and zero PU devices. In this interference channel, the channels H_jk— \\^!* H_jkB_k may reduce (e.g., cancel) interference from the SU devices to the PU device, and may reduce (e.g., cancel) interference from the PU device to the SU devices. The jth SU receiver may further apply a (Nj — M_p) X d_j interference suppression matrix D_; thai may satisfy D^* D, = l_d ., which may result in

where the effective noise D^*Z = DJ W^*Z may follow the same distribution as Ζ,·, for example because the columns of W, D - are ortho-normal.

[0086] The example interference alignment and cancellation problem, Problem- ] , may be reduced to the following example interference alignment problem, that ma be referred to as Problem-2: given degrees of freedom (d_1; . . . , d_K), find preceding matrices P_k and postcoding matrices D_k

P_k: (M_k - N_p) X d_k, P_k?P_k - i_dk, Vk - 1, ... , K

D_k: (N_k - Mp) X d_kl \T_k l - l_!ik, Vk - 1 K such that

D| H_jk¾ = 0_{dj Xdk>} Vk≠j rank (DJ H^P.) = d_j, V; = 1, ... , K where U_jk are defined in equation (6).

[0087] In Problem-2, there may be no distinction whether a device is a PU device or an SU device. If M_k > N_p and N_k > M_p, Vk. = 1, ... . A^", the example interference alignment and cancellation problem, Problem- 1 , may be reduced to the example interference alignment problem, Problem-2, as expressed in equations (9) - ( 12). If a precodin matrix P_k and a postcoding matrix D_k, respectively, that solve the interference alignment problem, Problem-2 are obtained, then V_k = B_fcP_fe and U_fc = W_k D_k for equations (3) and (4), respectively, may be determiend for the interference alignment and cancellation problem, Problem- 1.

[0088] Matrices P_k and D_fc that satisfy the interference alignment problem as expressed in equations (9) - (12) may be obtained. For example, in an interference network that may not include a PU device, if it is assumed that M_k — M, N_k— N, and d_k = d for all k, and Λί and N are divisible by d, then interference alignment may be feasible, for example, if and only if M + N≥ d (K + 1). Tn an example underlay cognitive radio network that includes a PU device and multiple SU devices, it may be that M_k ~ M_s, N_k = N_s and d_k = d_s for all k = 1, · · · , K, where the subscript s indicates secondary user devices.

Invoking the result from the interference network that may not include a PU device, it may be that if (M_s— Np) and (N_s — M_p ) are divisible by d, then the interference alignment problem as expressed in equations (9) - (12), and hence the interference alignment and cancellation problem, Problem- ! , may be feasible, for example, if and only if (M_s + N_s — M_p — N_p)≥ d(K + 1).

[0089] Approximation algorithms may be employed in the performance of an example interference alignment and/or cancellation problem, for example in solving Problem- 1 and/or Problem-2. The example interference alignment problem, Problem-2, as expressed in equations (9) - (12), may not be practical (e.g., computationally efficient) to solve numerically, for example using a computer to determine matrices ¾ and D_k. It has been shown that Problem-2 may be NP-hard in the number of SU devices, K. Accordingly, Problem- 1 may also be NP-hard.

[0090] A first approximation algorithm that may be used to solve Problem-2 is the iterative interference alignment (ΠΑ) algorithm. In accordance with the II algorithm, a reciprocal interference channel may be constructed such that the interference alignment condition for the reciprocal interference channel is the same as that of the original interference channel. In the reciprocal interference channel, the roles of the transmitters and receivers may be switched, and li_{k !} = lij_k may be the channel matrix from the y^'-th SU receiver to the fc-th SU transmitter. The reciprocal interference channel may be a theoretical apparatus, and it may not be related to whether ihe physical channels are reciprocal or not. The transmit and receive matrices of the reciprocal interference channel may be denoted by P¾ and D_fe, respectively. It may be that P = D and D_fe = P_k, and D¾H_fc/P- = (D^* !!,·_¾.?_¾)^*. The interference alignment of ihe reciprocal interference channel may be feasible, for example as long as that of the original in terference channel is feasible and vice versa, and the transmit and receive matrices may be obtained by exchanging those obtained on the original interference channel.

[0091 ] The IIA algorithm may begin with arbitrary preceding matrices P_fc, such that

P P_k = {. in each iteration, the fcth SU receiver may compute the interference covariance matrix

Qfc =∑^lj=i,j≠k : ¾ ^{p p} ¾y where P, is the total transmit power of transmitter j. In accordance with the herein-described definition of s_k, Q¾ may be closely related to the total interference leakage at receiver k. The mterfernee signal may be denoted by r_k =∑f_{^1 ≠k} ¾y /. The expected value of the interference power may be E [\ | D _C r_fc 1 1²] = E [tr(O_k ^* r_krl O_k)] = tr(¾Q_fc D_fc), where the covariance matrix of s¾ is assumed to be an identity matrix. Due to its non-negativity, the interference power may approach zero if its expected value approaches zero. The /c-th user may fry to minimize tr(D¾Q¾D_fe), which may be performed by choosing the columns of D_fc as the eigenvectors of Q¾ corresponding to the smallest d_k eigenvalues, such that D_kO_k = 1.

[0092] The communication direction may be reversed to consider the reciprocal channel. It may be set that P_k = D_fc. The interference covariance matrix may be computed, as expressed by

where P, is the total iransmit power of receiver j (which may serve as a transmitter in the reciprocal network), and the columns of O_k may be chosen as the eigenvectors of Q_fc corresponding to the smallest d_k eigenvalues, such that O O_k = I.

[0093] The communication direction may then be reversed and the original channel may be considered. It may be set that P = D_fc . The next iteration may then begin, for example until the algorithm converges.

[0094] The IIA algorithm may allow for a distributed implementation. Although the interference covariance matrix expressed in equation (13) may depend on all channel matrices and precoding matrices, it may be estimated as a whole by the /c-th user in a distributed manner. Example details of the II A algorithm are shown in Lines 6- 14 in Algorithm 1 below.

[0095] A second approximation algorithm that may be used to solve Problem- 2. is the

Max-SINR algorithm. The HA algorithm attempts to align the interference in a subspace orthogonal to the desired signal subspace, but makes no effort to maximize the desired signal power in ihe desired signal subspace. This characteristic of the IIA algorithm may be addressed by the Max-SINR algorithm. In accordance with the Max-SINR algorithm, in the original channel, the Zth column of D_fe, denoted by (O_k)._rl may be set as follows, in order to maximize the STNR of the Ith stream at receiver k

where (·)*ι represents the /th column of matrix (·), and

is the covariance matrix of the interference and noise. In the reciprocal network, it may be set that P_fc = D_fc, V . The interference covariance matrix T_kl may be calculated by replacing Ρ· and P_fc in equation (16) with Ρ_;· and P_k, respectively. (D_fc)₄._i may be calculated by replacing Tfc_j and Pfc in equation ( 16) with ¾ and P_k, respectively. Example details of the Max-SINR algorithm are shown in Lines 16-24 in Algorithm I , Both the ITA algorithm and the Max- SINR algorithm may converge.

Algorithm 1

Require: Channel matrices _kp and H_kj- for k,j ~ 1,2, · · · , K

Ensure: Determine transmit beamforming matrices V_fe and receive beamforming matrices U_k for k— 1,2, · ·^■ , K

1 ) Perform the BNSL algorithm to obtain N^"(H._pfc);

2) Let ihe columns of B_fc be a basis of JV(H_pfe):

3) Let the columns of W_& be a basis of Λ^"(Η^);

4) % = W_j*Yj, Hj_k = \N_j*ttj_kB_k ;

5) IF the approximation algorithm is the IIA algorithm

6) Initialize ¾ as a random (M_k — N_p) X d matrix such that P_k P — I_d ;

7) Begin iteration: 8) Compute Q_fc according to (13);

9) Let the columns of D_fe be the eigenvectors corresponding to the smallest d eigenvalues of Q_fe ;

10) Reverse the communication direction, set P_k = O_k, V/c;

1 1 ) Compute Q_fe according to ( 14);

12) Let the columns of P¾ be the eigenvectors corresponding to the smallest d_k eigenvalues of Q_fe ;

13) Reverse the communication direction, set P_k = D_fc, Vft;

14) Back to 7 until convergence;

15) ELSE IF the approximation algorithm is ihe Max-SINR algorithm

16) Initialize P_k as a M_k X d_k matrix such that the columns are linearly independent;

1 7) Begin iteration:

1 8) Compute T_kl, fk, I according to ( 16);

19) Compute (0_¾),·., Vk, I according to (15);

20) Reverse the communication direction, set ¾ = O_k, Vfc;

21) In the reciprocal network, compute T_kl, V/c, I;

22) Compute (D_fc)_tl, Vfe;

23) Reverse the communication direction, set P_fe = D_fe, V i;

24) Back to 17 until convergence;

25) END IF

26) V_fc = B_fcP_fc> U_fc ^ ν,Ο,

[0096] In accordance with the example interference alignment and/or cancellation process, the constraint that the SU devices may not affect the PU device may be stated as HpfcVfc = 0, where an equality may be used. However, due to the truncation of the digits of real and/or complex numbers, and/or other errors (e.g., in channel estimation and/or power measurement), equality may not be achieved. In such a case, the equality may be replaced with an inequality, for example setting H_pkV_k≤ £_kO_{N xdk}, where 0_{N xdk} is a N_p x d_k matrix with all entries being one, and ¾ > 0 is a constant determined by the overall error of the system. Similar modifications may be employed for ϋ^* Η_;ί) 0, for

≠ k = 1, 2, ... . K. [0097] Knowledge of global channel state information (CSI) may be associated with interference alignment (e.g., may be necessary for interference alignment). One or more devices in a network (e.g., an eNB in an LTE system) may be configured to be aware of all channel matrices H_S -. Training may be performed to obtain channels W_kk. During the training for an SU device k, one or more other SU receivers /≠ k may listen, for example to one or more training broadcasts by the SU device k. In this way, a single training e vent may result in K channel estimates. For example, an SU device in an underlay cognitive radio network may receive channel matrix information pertaining to another SU device that is accessing the licensed spectrum.

[0098] An SU device may use such received channel matrix information in deriving a postcoding matrix, such that application of the postcoding matrix to transmissions received from one or more other SU devices may mitigate (e.g., align and/or cancel) interference caused at the SU device. An SU device may derive a postcoding matrix based on the channel matrices H_kj and on the interference channel H_ip, such that the postcoding matrix may be applied to mitigate (e.g., cancel) interference by the PU device at the SU device, and/or to mitigate (e.g., align and/or cancel) interference by one or more other SU devices at the SU device.

[0099] Coordinating training sequence transmission and/or listening may be achieved by using a low-overhead protocol, for example a protocol based on time-division

multiplexing (TDM) scheduling, such that obtaining an estimate of global CSI may incur negligible communication overhead. In the event that such coordination is not possible, distributed implementations of the II A algorithm and/or the Max-SINR algorithm may be employed. For example, each SU device may be configured to estimate the channel matrix of the SU device itself, and/or to estimate the interference covariance matrix as a whole. The channel matrices H,_p may be estimated at an SU receiver /^' by overhearing the PU device training sequence transmission and/or by knowing the PU training sequence, and the channel matrix may be estimated via the BNSL algorithm, for example as described herein.

[0100] The use of a reciprocal network, for example in approximation algorithms, may be theoretical, as physical channels may not be reciprocal. Once an SU transmitter or SU receiver knows the global CSI, it may run the approximation algorithms, for example without incurring communication overhead. In practsce, an SU transmitter or SU receiver may ran the approximation algorithms to obtain matrices V_k and U>_K, and may distribute them to the one or more other SU devices. In accordance with a distributed implementation of the approximation algorithms, channel reciprocity of the physical channel may exist, and real transmissions may occur in each iteration. In such an example, communicatio overhead may be large, for example if the convergence rates are slow.

[0101 ] Channel coherence time may be accounted for. When the channels are static, the BNSL algorithm, other channel estimation algorithms, and/or the approximation algorithms may work without issue. In practice, the channels may vary over time. The BNSL algorithm may be augmented to track changes (e.g., slow changes) in one or more channels. For other channel estimation algorithms, as long as the channel coherence time is larger (e.g., much larger) than K times of the channel training time, channel estimates may be accurate. For the approximation algorithms, the convergence time may be less (e.g., much less) than the channel coherence time. Distributed implementations may be more restrictive.

[0102] Simulations employing Algorithm 1 were performed. In the simulations, the

BNSL algorithm was performed to determine the null space of the channel from each S U transmitter to the PU receiver. An approximation algorithm was then executed, for example the IIA. algorithm or the max-SINR algorithm.

[0103] Example systems with three, four and five SU transmitters and receivers, respectively, setting K = 3, 4, or 5, and letting M_p = N_p— 2, M_k — M_s = 6 and N_k = N_s— 4 for all k, were simulated. Two independent information streams were sent by the PU device, and one independent information stream was sent by each SU device. It was assumed that the respective transmit power of the PLT device and the SU devices were effectively the same. In FIGs. 2-5, the performance of the PU devcie is illurated using solid lines and the respective performance of the SU devices are illustrated using dashed lines.

[0104] FIG. 2 depicts example sum rates of the PU device and the SLT devices when the IIA algorithm is employed. FIG, 3 depicts example sum rates of the PU device and the SU devices when the max-SINR algorithm is employed. The averaged rates of a single S device are depicted as dotted lines. The numerical results were averaged over 100 channel realizations.

[0105] FIGs. 3 and 4 depict example bit error rates (BER) of the PU de vice and the

SU devices using the IIA. alignment algorithm and the max-SINR algorithm, respectively. A BPSK. constellation was used for the simulations. The BER performance of the PU device, when no SLT devices exist, is depicted in FIG. 4. [0106] It was observed that while the sum rate and BER performance of the PU device remains nearly the same, the performance of the SU devices degrade as the number of SU devices increases. Interference alignment and/or cancellation may be feasible, for example, if and only if M_s + N_s— M_p— N_p≥ d(K + I). Although the singulation setup satisfies the feasibility condition, if may be observed in FIGs. 2 and 4 that interference alignment may fail with K = 5, which may be due to a weakness of the ΠΑ algorithm.

[0107] It was observed that the max-SINR algorithm may provide better sum rate and

BER performance than the TIA algorithm, even if interference alignment fails at K = 5. Iiowever, the max-S!NR algorithm may require more computation than the HA algorithm, for example to converge. For example, in an example where SNR ~ 8 dB and K ~ 4, the average time to converge for the max-SINR algorithm is 2.35 times as long as that for the IIA algorithm, with the same termination criterion and the same simulation environment. In practice, the SINR may converge if the SINR as a function of the number of iterations flattens out.

[0108] Although features and elements are described above in particular

combinations, one of ordinary skill in the art will appreciate that each feature or element may be used alone or in any combination with the other features and elements. In addition, the methods described herein may be implemented in a computer program, software, or firmware incorporated in a computer-readable medium for execution by a computer or processor. Examples of computer-readable media include electronic signals (transmitted over wired or wireless connections) and computer-readable storage media. Examples of computer- readable storage media include, but are not limited to, a read only memory (ROM), a random access memory (RAM), a register, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks, and digital versatile disks (DVDs). A processor in association with software may be used to implement a radio frequency transceiver for use in a WTRU, WTRU, terminal, base station, RNC, or any host computer.

Claims

CLAIMS What is claimed:

1 . A method of mitigating interference associated with access of a licensed spectrum by a secondar user (SO) device, the method comprising, by the SU device:

determining first characteristics of a channel in the licensed spectmm between the SU device and a primary user (PU) device associated with the licensed spectmm, wherein the first characteristics pertain to a null space of the channel;

deriving, based on the first characteristics, a precoding matrix, wherein application of the precoding matrix to a transmission by the SU device causes the transmission to be within the null space of the channel, such that interference caused by the transmission, at the PU device, does not exceed a threshold interference level; and

applying the precoding matrix to a signal transmitted by the SU device while accessing the licensed spectrum as a secondary user.

2. The method of claim 1, wherein determining the first characteristics includes performing a blind null-space learning algorithm.

3. The method of claim 2, wherein performing the null space learning algorithm includes transmitting a test signal in the channel, and monitoring for a transmit power level adjustment by the PU device.

4. The method of claim 1, wherein the threshold interference level is based on a policy requirement.

5. The method of claim 1, further comprising: determining second characteristics of the channel in the licensed spectrum; and deriving, based on the second characteristics, a postcoding matrix.

6. The method of claim 5, wherein the postcoding matrix is derived such that if a transmission received at the SU device originates from the PU device, application of the postcodmg matrix to the received transmission cancels interference caused at the SU device by the received transmission,

7. The method of claim 1, further comprising:

receiving channel matrix information pertaining to a second SU device that is accessing the licensed spectrum; and

deriving, based on the channel matrix information, a postcoding matrix.

8. The method of claim 7, wherein the postcoding matrix is derived such that if a transmission received at the SU device originates from the second SU device, application of the postcodmg matrix to the received transmission cancels interference caused at the SU device by the received transmission.

9. The method of claim 1, further comprising:

determining second characteristics of the channel in the licensed spectrum;

deriving, based on the second characteristics and the channel matrix information, a postcoding matrix.

10. The method of claim 9, wherein the postcoding matrix is derived such thai: if a transmission received at the SU device originates from the PU device, application of the postcodmg matrix to the received transmission cancels interference caused at the SU de vice by the received transmission; and

if a transmission received at the SU device originates from the second SU device, application of the postcoding matrix to the received transmission cancels interference caused at the SU device by the received transmission.

1 1. A wireless transmit/receive unit (WTRU) comprising:

a processor that is configured to, when the WTRU accesses licensed spectrum as a secondary user of the licensed spectrum:

determine first characteristics of a channel in the licensed spectrum between the WTRU and a primary user (PU) device associated with the licensed spectrum, wherein the first characteristics pertain to a null space of the channel;

derive, based on the first characteristics, a precoding matrix, wherein application of the precoding matrix to a transmission by the WTRU causes the transmission to be within the null space of the channel, such that interference caused by the transmission, at the PU device, does not exceed a threshold interference level; and

cause the WTRU to apply the precoding matrix to a signal transmitted by the WTRU while accessing the licensed spectrum as a secondary user.

12. The WTRU of claim 1 1, wherein the processor is configured to determine the first characteristics by performing a blind null-space learning algorithm.

13. The WTRU of claim 12, wherein the processor is configured to perform the null space learning algorithm by transmitting a test signal in the channel, and monitoring for a transmit power level adjustment by the PU device.

14. The WTRU of claim 1 1 , wherein the threshold interference level is based on a policy requirement.

15. The WTRU of claim 1 1 , wherein the processor is further configured to:

determine second characteristics of the channel in the licensed spectrum; and derive, based on the second characteristics, a postcodmg matrix.

16. The WTRU of claim 15, wherein the processor is configured to derive the postcoding matrix such that if a transmission received at the WTRU originates from the PU device, application of the postcoding matrix to the received transmission cancels interference caused at the WTRU by the received transmission.

1 7. The WTRU of claim 1 1 , wherein the processor is further configured to:

receive channel matrix information pertaining to a second WTRU that is accessing the licensed spectrum: and

derive, based on the channel matrix information, a postcoding matrix.

1 8. The WTRU of claim 1 7, wherein the processor is configured to derive the postcoding matrix such that if a transmission received at the WTRU originates from the second WTRU, application of the postcoding matrix to the received transmission cancels interference caused at the WTRU by the received transmission.

19. The WTRU of claim 1 1 , wherein the processor is configured to:

determine second characteristics of the channel in the licensed spectrum;

receive channel matrix information pertaining to a second WTRU that is accessing the licensed spectrum; and derive, based on the second characteristics and the channel matrix information, a postcoding matrix.

20. The WTRU of claim 19, wherein the processor is configured to derive the postcoding matrix such that:

if a transmission received at the WTRU originates from the PU device, application of the postcoding matrix to the received transmission cancels interference caused at the WTRU by the received transmission; and

if a transmission received at the WTRU originates from the second WTRU , application of the postcoding matrix to the received transmission cancels interference caused at the WTRU by the received transmission.