SCANNING EMPLOYING COMPRESSED SENSING

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. provisional application

Nos. 61/619,718 filed April 3, 2012 and 61/794,315 filed March 15, 2013, the contents of which are hereby incorporated by reference herein.

BACKGROUND

[0002] In recent years there has been an ever-increasing demand from the mobile consumer community for instantaneous access to large quantities of content while energy and spectrum resources have remained scarce. It is expected that the spectrum crunch problem may be addressed by the future deployment of Cognitive Radio technology that may enable a mobile device to opportunistically use under-utilized spectrum. Under-utilized resource or spectrum may, however, be scattered over a large range of frequencies spanning several Giga Hertz (GHz). To further complicate matters, the spectrum scenario may change with time. Intra and inter-band noncontiguous bandwidth aggregation along with dynamic spectrum management in a wireless transmit receive unit (WTRU), as well as in infrastructure equipment, may be used for spectrum access.

SUMMARY

[0003] A method and apparatus for use in a wireless communication system includes compressed sensing for wide spectrum scanning. A single or multiple parallel compressed scanners may use compressed sensing for wide spectrum scanning. A single compressed scanner may include, for example, a spectrum shifting and reassembly block, an array or parallel arrangement of mixers, a low pass filter, a sampler, and a spectrum recovery engine. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings wherein:

[0005] FIG. 1A is a system diagram of an example communications system in which one or more disclosed embodiments may be implemented;

[0006] FIG. IB is a system diagram of an example wireless transmit/receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1A;

[0007] FIG. 1C is 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;

[0008] Figures 2A and 2B show an example of a bandpass sampling of a single signal;

[0009] Figure 3 shows an example of artificial sparsity in the spectrum of a signal;

[0010] Figure 4 shows an example of natural sparsity in the spectrum of a signal;

[0011] Figure 5 shows a flow diagram of an example method of compressed sensing employing spectrum shifting;

[0012] Figure 6 shows an example of shifting an entire spectrum chunk of bandpass signals where sparsity is present;

[0013] Figure 7 shows an example of a receiver configured to perform compressed sensing by employing spectrum shifting;

[0014] Figure 8 shows an example of segment- wise shifting of bandpass signals where sparsity is present;

[0015] Figure 9 shows another example of a receiver configured to perform compressed sensing by employing spectrum shifting;

[0016] Figure 10 shows a flow diagram of an example method of compressed sensing employing band reassembling; [0017] Figure 11 shows an example of band reassembling of bandpass signals where sparsity is present for compressed sensing;

[0018] Figure 12 shows an example of band reassembling of bandpass signals using band grouping;

[0019] Figure 13 shows an example of band reassembling of bandpass signals using band partitioning;

[0020] Figure 14 shows an example of a sparse wideband signal;

[0021] Figure 15 shows another example of a receiver configured to perform compressed sensing by employing spectrum shifting using in- phase/quadrature (IQ) vector de-modulation;

[0022] Figure 16 shows an example of down-converted complex

baseband spectrum;

[0023] Figure 17 shows another example of a sparse wideband signal;

[0024] Figure 18 shows another example of a receiver structure; and

[0025] Figure 19 shows an example sparse-wideband signal spectrum re-assembled at baseband.

DETAILED DESCRIPTION

[0026] 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. [0027] As shown in FIG. 1A, the communications system 100 may include wireless transmit/receive units (WTRUs) 102a, 102b, 102c, 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 will be appreciated that the disclosed embodiments contemplate any number of WTRUs, 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.

[0028] The communications systems 100 may also include a base station

114a and a base station 114b. Each of the base stations 114a, 114b 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 110, and/or the networks 112. By way of example, the base stations 114a, 114b 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 114a, 114b are each depicted as a single element, it will be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and/or network elements.

[0029] The base station 114a 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 114a and/or the base station 114b 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 114a may be divided into three sectors. Thus, in one embodiment, the base station 114a may include three transceivers, i.e., one for each sector of the cell. In another embodiment, the base station 114a may employ multiple -input multiple output (MIMO) technology and, therefore, may utilize multiple transceivers for each sector of the cell.

[0030] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0031] 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, OFDMA, SC-FDMA, and the like. For example, the base station 114a 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 116 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).

[0032] In another embodiment, the base station 114a 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 116 using Long Term Evolution (LTE) and/or LTE- Advanced (LTE-A).

[0033] In other embodiments, the base station 114a and the WTRUs

102a, 102b, 102c may implement radio technologies such as IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 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.

[0034] 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 114b 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 114b 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 femtocell. As shown in FIG. 1A, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not be required to access the Internet 110 via the core network 106.

[0035] 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 102a, 102b, 102c, 102d. For example, the core network 106 may provide call 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 will be appreciated that the RAN 104 and/or the core network 106 may be in direct or indirect communication with other RANs 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. [0036] The core network 106 may also serve as a gateway for the

WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and/or other networks 112. The PSTN 108 may include circuit-switched telephone networks that provide plain old telephone service (POTS). The Internet 110 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 112 may include wired or wireless communications networks owned and/or operated by other service providers. For example, the networks 112 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.

[0037] Some or all 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 114a, which may employ a cellular -based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.

[0038] FIG. IB is a system diagram of an example WTRU 102. As shown in FIG. IB, the WTRU 102 may include a processor 118, a transceiver 120, a transmit/receive element 122, a speaker/microphone 124, a keypad 126, a display/touchpad 128, non-removable memory 106, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and other peripherals 138. It will be appreciated that the WTRU 102 may include any sub- combination of the foregoing elements while remaining consistent with an embodiment.

[0039] The processor 118 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 WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit/receive element 122. While FIG. IB depicts the processor 118 and the transceiver 120 as separate components, it will be appreciated that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.

[0040] The transmit/receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 114a) over the air interface 116. 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 IR, UV, or visible light signals, for example. In yet another embodiment, the transmit/receive element 122 may be configured to transmit and receive both RF and light signals. It will be appreciated that the transmit/receive element 122 may be configured to transmit and/or receive any combination of wireless signals.

[0041] 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 116. [0042] 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 802.11, for example.

[0043] The processor 118 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker/microphone 124, 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 118 may also output user data to the speaker/microphone 124, the keypad 126, and/or the display/touchpad 128. In addition, the processor 118 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 nonremovable 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 118 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).

[0044] The processor 118 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 cells, fuel cells, and the like. [0045] The processor 118 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 116 from a base station (e.g., base stations 114a, 114b) and/or determine its location based on the timing of the signals being received from two or more nearby base stations. It will be appreciated that the WTRU 102 may acquire location information by way of any suitable location- determination method while remaining consistent with an embodiment.

[0046] The processor 118 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.

[0047] FIG. 1C is a system diagram of the RAN 104 and the core network 106 according to an embodiment. As noted above, the RAN 104 may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 104 may also be in communication with the core network 106.

[0048] The RAN 104 may include eNode-Bs 140a, 140b, 140c, though it will be appreciated that the RAN 104 may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 140a, 140b, 140c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the eNode-Bs 140a, 140b, 140c may implement MIMO technology. Thus, the eNode-B 140a, for example, may use multiple antennas to transmit wireless signals to, and receive wireless signals from, the WTRU 102a.

[0049] Each of the eNode-Bs 140a, 140b, 140c 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. 1C, the eNode-Bs 140a, 140b, 140c may communicate with one another over an X2 interface.

[0050] The core network 106 shown in FIG. 1C may include a mobility management gateway entity (MME) 142, a serving gateway 144, and a packet data network (PDN) gateway 146. While each of the foregoing elements are depicted as part of the core network 106, it will be appreciated that any one of these elements may be owned and/or operated by an entity other than the core network operator.

[0051] The MME 142 may be connected to each of the eNode-Bs 140a,

140b, 140c in the RAN 104 via an Si interface and may serve as a control node. For example, the MME 142 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 142 may also provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM or WCDMA.

[0052] The serving gateway 144 may be connected to each of the eNode-

Bs 140a, 140b, 140c in the RAN 104 via the Si interface. The serving gateway 144 may generally route and forward user data packets to/from the WTRUs 102a, 102b, 102c. The serving gateway 144 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.

[0053] The serving gateway 144 may also be connected to the PDN gateway 146, which may provide the WTRUs 102a, 102b, 102c with access to packet- switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0054] The core network 106 may facilitate communications with other networks. For example, the core network 106 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 106 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 106 and the PSTN 108. In addition, the core network 106 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.

[0055] Cognitive communication and dynamic spectrum management may include the discovery of under-utilized spectrum. In an example of this, a single component carrier in a licensed band may be utilized to establish the primary link. A scan of a large swath of spectrum may be conducted to identify underutilized spectrum in licensed or unlicensed bands. Additional component carriers from licensed and unlicensed bands may be aggregated to establish a supplementary link as needed to deliver the requested throughput. Scans of the relevant swaths of spectrum may be conducted to determine interference levels in the supplementary link. The supplementary link may be adapted, for example, by re-allocating component carrier frequencies, or changing modulation type and/or order, as needed. The above procedures may be repeated several times during the life of a single call or session. Given a certain set of conditions, it is possible that the spectrum scanning process described above may consume significant energy and reduce the mobile device activity, or talk time to unacceptable levels. Therefore, fast and efficient wideband spectrum scanning technology may address these issues. [0056] In recent years, compressed sensing based wideband scanners have become a very popular topic of research in academia. This type of scanner may be useful when a large range of spectrum may be searched and there exists no prior knowledge of the spectrum occupancy, or frequency support of the wideband signal. While the complexity of the compressed sensing (CS) scanner may be higher, its efficiency may be appreciably better than that of the analog channel scanner depending on spectrum occupancy.

[0057] In some commercial bandwidth (BW) aggregation applications, however, the WTRU may be restricted to a finite number of licensed and unlicensed bands scattered over a wide range of frequencies. While the total available bandwidth may only be a few hundred Mega Hertz (MHz), the range of frequencies may extend from 500MHz to 6GHz, for example. The typical CS scanner may not perform so well when there is a need to search a few disjointed swaths of spectrum at known center frequencies scattered throughout a wide range of frequencies. In this case, the uppermost edge of the highest frequency swath or band and not the aggregate bandwidth or spectrum of interest may determine the complexity of a CS scanner. Therefore, it is desirable to design a CS scanner for such commercial bandwidth aggregation applications.

[0058] Table 1 shows a survey of scanner technology. The complexity of the analog narrow band channel scanner may be the lowest of the three types included in Table 1. This type of scanner may be useful for monitoring a single channel, or small swath of spectrum, at a time. If a broad range of frequencies needs to be monitored, a single channel scanner may be employed several times sequentially or many channel scanners may be employed simultaneously. The energy consumed by the analog channel scanner may be used as a baseline of comparison in Table 1. Instantaneous Frequency Receiver Reconfigurability nge and Dynamic Energy /

Receiver Type Ra Complexity

Range Energy Data detection*MHz

Typical Use Case Detection Demodulation

Narrow

Analog narrow

band (channel) Useful for monitoring single Low Low Yes No High scanner channels (a relatively small

range of spectrum)

Wide

Moderate to

Useful for monitoring a very

Compressed High

large range of spectrum

sensing wideband (spectrum occupancy or the Adjustable High Yes Yes (Depends on scanner frequency support of the spectral wideband signal is unoccupancy) known)

Wide

Useful for monitoring a very

large range of spectrum Low to

Enhanced CS made up of a few disjointed Moderate scanner (present swaths of interest located at Adjustable Moderate Yes Yes (Depends on invention) known center frequencies

spectral (spectrum occupancy or the

occupancy) frequency support of the

wideband signal is partially

known)

Table 1

[0059] Bandpass sampling may be used to sample a continuous bandpass signal located at a center frequency above 0 Hz. Bandpass sampling may be considered as a band-limited signal. Bandpass sampling may reduce the sampling rate of analog/digital converters (ADCs) below the rate required for conventional low-pass sampling.

[0060] Figures 2A and 2B show an example of a bandpass sampling of a single signal. Figure 2A shows a bandpass signal centered at f _c = 20 MHz with a bandwidth of B = 5 MHz . By using a sampling rate of f _s - f _c -B/2 - \l .5 MHz l7.5 MHz, the bandpass signal may be sampled and translated down, through aliasing, to a center frequency of 2.5 MHz, as shown in Figure 2B. Since the translated bandpass signal may be a real signal, a mirror image of the bandpass signal may appear at a center frequency of -2.5 MHz. Figures 2A and 2B illustrate that there are certain sampling rates that will have no spectral overlap.

[0061] More than two bandpass signals may be translated down using a common sampling rate, however the more signals that may be translated down simultaneously, the more difficult it may be to find a suitable common sampling rate. Iterative methods may be available for calculating a suitable sampling rate based on the set of bandpass signals' upper and lower frequencies.

[0062] When sub-Nyquist rate sampling or compressed sensing techniques are used for wideband sensing, the sampling rate may be decreased and power consumption may be reduced. As a result, receiver complexity may be reduced. In cases where the bands of interest are known, filtering the particular bands of interest may be possible, which may help improve the performance of compressed sensing.

[0063] Figure 3 shows an example of artificial sparsity in the spectrum of a signal. In Figure 3, the signal has a sampling bandwidth of Wl GHz measured from direct current (DC) or an intermediate frequency (IF), and includes sub-bands of interest 1, 2 ... K-l, K. When pre-filtering or spectrum masking is used to filter out the bands that are not of interest so that only the bands of interest (in this example, sub-bands 1...K) remain, then artificial sparsity may be created across the spectrum. Some of that sparsity may be considered undesirable or "bad" sparsity, as discussed further below.

[0064] Figure 4 shows an example of natural sparsity in the spectrum of a signal. Like in Figure 3, the signal has a sampling bandwidth of Wl GHz measured from direct current (DC) or an intermediate frequency (IF), and includes sub-bands of interest 1, 2 ... K-l, K. Artificial sparsity is shown in between DC or IF and sub-band 1, and in between each adjacent pair of sub- bands, for example, between sub-band 1 and 2. In addition, natural sparsity may exist inside the bands of interest. For each band of interest, there may be some unused spectrum which results in sparsity. An example is shown for sub-band 2, with bandwidth B MHz. Sub-band 2 includes occupied spectrum shaded in grey as well as sparsity shown in white.

[0065] More sparsity may result in better compression ratio and thus lower sampling rates. However, artificial sparsity may not necessarily result in receiver complexity reduction, such that no real savings in aggregate sampling rate may be possible. Although sparsity may reduce sampling rates and achieve sub-Nyquist rate sampling, some artificial sparsity, as shown for example in Figure 3, may be considered "bad sparsity" and may not improve the aggregated sampling rates. Instead, it may cause higher power consumption and introduce additional complexity. Only natural sparsity or what may be considered as good sparsity may be useful. In order to enhance compressed sensing and receiver structure to achieve low complexity and high performance for spectrum sensing, techniques and methods may be used to remove bad sparsity and only keep good sparsity for spectrum scanning employing compressed sensing.

[0066] Possible solutions for enhancing a receiver and system for wideband spectrum scanning may employ compressed sensing. For example, with reference to Figure 3, the "bad" sparsity may be removed while keeping other sparsity that is good for spectrum scanning, using compressed sensing. As discussed above, there may be different kinds of sparsity, namely natural sparsity and artificial sparsity. Artificial sparsity may result from pre- filtering particular bands of interest, while natural sparsity may result from dynamic usage of spectrum resources. The types of sparsity may be exploited in a compressed sensing receiver. In an example, a receiver structure may employ spectrum shifting for compressed sensing. In another example, a receiver structure may employ band reassembly for compressed sensing. Compressed sensing may be combined with bandpass sampling or direct conversion or may be implemented with conventional down-conversion techniques. Examples of such methods are described below. The examples described herein may operate on the signal spectrum, such that a signal may be converted from the time domain to the frequency domain using a time-to- frequency domain converter prior to processing. Examples of time-to- frequency domain converters may include, for example, a short-time Fourier transform (STFT) or a discrete Fourier transform (DFT).

[0067] Objectives for the design of compressed sensing may include saving sampling power, lowering complexity and reducing overall power consumption. Receiver structures may be developed to combine advantages of both compressed sensing and bandpass sampling. Since compressed sensing may reduce the sampling rate from the Nyquist rate and bandpass sampling techniques may further reduce the sampling rate, bandpass sampling may be used to remove artificial sparsity and allow compressed sensing to work with natural sparsity afterward. By doing so, the receiver may benefit from both sensing and sampling techniques to achieve a lower overall sampling rate, a lower complexity, and lower power consumption.

[0068] Prior knowledge of spectrum may be utilized and a semi-blind compressed sensing approach may be used instead of a totally blind compressed sensing approach. The spectrum shift and reassembly may be utilized, which may result in reduced sampling bandwidth of the signal. Due to the reduced sampling bandwidth, multiple folds reduction in mixer rates may be achievable. This may translate into lower power consumption and power savings. In addition, the reduced sampling bandwidth may mitigate the noise folding effects due to spectrum folding in compressed sensing which may result in significant SNR enhancement.

[0069] The use of spectrum shifting and band reassembly, including grouping and partitioning approaches, may allow radio frequency (RF) branches to be divided into multiple subsets. This may enable multiple separate but smaller recovery engines associated with each RF branch subset, which may reduce system matrix sizes and reduce matrix dimensions for the signal recovery processing. Accordingly, lower computational complexity and hardware complexity may be achieved for the signal processing, baseband processing and overall receiver. Band grouping and partitioning may produce efficient signal aggregation of the detected signals received from multiple parallel and smaller dimension signal recovery engines for compressed sensing.

[0070] Figure 5 shows a flow diagram of an example method 500 of compressed sensing employing spectrum shifting. A signal spectrum may be filtered to generate at least one portion of signal spectrum to include the frequency bands of interest, 505. The at least one portion of signal spectrum may be, for example, a spectrum chunk or one or more spectrum segments. The at least one portion of signal spectrum may be shifted to a lower center frequency, 510. The lower center frequency may be, for example, DC or an IF. Shifting of the spectrum for compressed sensing may be accomplished, for example, by shifting a large swath of spectrum (i.e. spectrum chunk), or by shifting in a segment-wise manner (i.e. one or more spectrum segments). According to the former method, the entire chunk that contains bands of interest may be shifted to DC or a lower center frequency for compressed sensing. According to the latter method, the spectrum may be shifted segment-wise for compressed sensing. A segmentation block may divide the spectrum into multiple segments. Only the segments of interest may be shifted to DC or lower center frequencies for compressed sensing. Compressed sensing is applied to the shifted at least one portion of signal spectrum, 515. Further details and examples of the methods shown in Figure 5 are discussed below.

[0071] Any method of spectrum shifting may use pre-masking or pre- filtering to filter the spectrum chunk or segments that contain bands of interest. A bandpass sampling, direct conversion or down conversion, may be used to perform the spectrum shifting, for example. If bandpass sampling is used, a unique sampling rate may be used to shift the entire chunk to a lower center frequency. For more than one frequency band or sub-band of interest, a common sampling rate may be used to shift multiple segments or multiple bandpass signals to a lower center frequency. If down conversion is used for the entire chunk, a single mixer may be employed. For a segment-wise approach with two spectrum segments, two mixers may be used. More generally, for a segment-wise method with x spectrum segments, x mixers may be used. The sampling rate may be reduced to a lower rate (an example of which is shown in Figure 6, discussed below). However, the sampling power may not be completely saved and may be optimized. A trade-off between sampling bandwidth, sampling rate, power, sparsity, and SNR may be performed.

[0072] According to an example method, the entire chunk may be shifted to DC or lower frequency for compressed sensing. Figure 6 shows an example of shifting an entire spectrum chunk of bandpass signals where sparsity is present. Figure 6 shows bandpass signals 1...K, where it is assumed that any or each of the K bandpass signals have sparsity within. Through the use of an appropriate sampling rate, the bandpass signals may be bandpass sampled and translated down, through aliasing, to lower center frequencies. The entire group of K bandpass signals may be sampled with one unique sampling rate and then may be processed by a single compressed sampling receiver.

[0073] The spectrum of interest may be first pre-filtered and down converted to a lower frequency or DC, as shown in Figure 6. By doing so, the "bad" sparsity from DC or low frequency to the lowest frequency of the spectrum of interest (in this example, the edge of subband 1) may be removed. The spectrum of interest may then be shifted to the DC or low frequency ready for compressed sensing to process. Spectrum shifting may be achieved by down conversion of the original frequency. The resulting signal after spectrum shifting may then be at a lower frequency or DC and be processed by a compressed sensing receiver. As compared to the other compressed sensing approaches, which may need to sample at a much larger bandwidth of Wl GHz, the spectrum shifting based compressed sensing as shown by example in Figure 6 may sample at the smaller bandwidth of W2 GHz. In many cases, bandwidth W2 may be much smaller than bandwidth Wl.

[0074] Figure 7 shows an example of a receiver 700 configured to perform compressed sensing by employing spectrum shifting. The original signal x(t) may be pre-processed and pre-filtered by a spectrum shifting and reassembling block 702 to down convert and shift the spectrum from high frequency to low frequency or DC and the resulting signals may be filtered. The pre-filtering and low-pass filtering may be performed inside the spectrum shift and reassembly block 702. Alternatively, the output of spectrum shift and reassembly block 702 may be filtered by, for example, a LPF (not shown). The resulting signal may then be processed by one or multiple RF branches 703i...m, where m branches are shown in Figure 7. For each RF branch 703i...m, the resulting signal may be first mixed by a mixer 704i... _m . Each mixer 704i... _m may employ a random waveform or may employ a corresponding pseudorandom code or sequence as denoted by pl(t) , p2(t), pm(t). After signal mixing, the resulting signal in each branch may be filtered by a low- pass filter (LPF) or an integrator 706i... _m . The output of each LPF (or integrator) 706i... _m may be sampled by a sampling device 708i... _m such as, for example, an analog- to- digital converter (ADC). The sampled signal yi, y2, y _m may then be fed to a compressed sensing recovery engine 710 to detect or recover the original signal and generate recovered signal X(f).

[0075] Assume the spectrum of interest (e.g., the entire chunk) may be located between f _L and f _H Hz, where f _L is the lowest frequency of the spectrum of interest and f _H is the highest frequency of the spectrum of interest. The sampling rate for the spectrum of interest may be chosen in the range of — ≤f _s ≤ , for some integer n , where 1 < n≤ The

lowest sampling rate may be determined using the largest possible n .

[0076] In another example, the segment-wise spectrum may be shifted for compressed sensing. The spectrum may be divided into segments. The segments of interest may be shifted to DC or lower frequency for compressed sensing.

[0077] Figure 8 shows an example of segment-wise shifting of bandpass signals where sparsity is present. Figure 8 shows bandpass signals 1...K, where each or any of the K bandpass signals may have sparsity within. Through the use of appropriate sampling rates, the bandpass signals may be bandpass sampled and translated down, through aliasing, to lower center frequencies. The K bandpass signals may be sampled with K unique sampling rates, and may then be processed by K different compressed CS receivers 1...K.

[0078] As shown in Figure 8, the spectrum may be divided into segments. A segment containing a band of interest (i.e. any of sub-bands 1, 2, K-l, K) may be shifted and down converted to lower frequency or DC. Each segment containing a band of interest may be shifted to lower frequency or DC and processed by a respective compressed sensing receiver. For example, the segment containing band 1 may be shifted and down converted to lower frequency or DC and processed by CS receiver 1; the segment containing band 2 may be shifted and down converted to lower frequency or DC and processed by CS receiver 2, and so on. The segments that do not contain any band of interest may not be shifted and down converted. They may not be processed by the compressed sensing receiver. By doing so, not only the "bad" sparsity from DC or lower frequency to the lowest frequency of the lowest segments may be removed, but also the additional "bad" sparsity between segments may be removed. For example, segment 1 may have bandwidth W3 MHz, segment 2 may have bandwidth W4 MHz, segment K-l may have bandwidth W5 MHz, and segment K may have bandwidth W6 MHz, as shown in Figure 8. In many cases W3+W4+W5+W6 may be smaller than bandwidth W2 GHz. This may result in better performance for compressed sensing. [0079] Figure 9 shows an example of a receiver 900 configured to perform compressed sensing by employing spectrum shifting, where segment- wise shifting is used. Each spectrum segment of the input signal x(t) may be pre-processed and pre-filtered by a corresponding spectrum shift and band reassembly block 902I...L. Pre-filtering and low-pass filtering may be performed inside the spectrum shift and reassembly block 902I...L. The output of each spectrum shift and reassembly block 902I...L may go through one or more RF branches 903i... _m . In another example, the output of each spectrum shift and reassembly block 902I...L may be filtered, using for example LPFs (not shown), and the resulting signals may go through one or more RF branches 903i... _m . In the example of Figure 9, the output of each spectrum shift and reassembly block 902I...L passes through two RF branches, however, any number of branches may be used. For example, the number of RF branches may be equal to the number of frequency bands of interest in each spectrum segment. In each RF branch 903i... _m the signal may be mixed by a corresponding mixer 904i... _m , filtered by a corresponding low-pass filter 906i... _m and sampled by a corresponding sampling device 908i... _m . The output of sampling devices 908i... _m may be fed to corresponding recovery engines 710I...L to detect or recover the original signal X(f).

[0080] For each spectrum shift and reassembly block 902I...L, there may be, for example, two RF branches associated with it, as shown in the example of Figure 9. The output of the first spectrum shift and reassembly block 902i may go through two RF branches 903i,2. The output of the m ^th spectrum shift and reassembly block 902L may go through another two RF branches 903 _m -i,m. Each mixer 904i... _m may be a mixer employing random waveform or a mixer employing the pseudorandom code or sequence as denoted by pl(t) , p2(t), pm(t). The output of the recovery engines 910I...L ri...L may then be aggregated to form a complete set of detected or recovered signal X(f). The detected or recovered signal X(f) may be, for example, the spectrum profiles, power spectrum density (PSD), spectrum whitespaces, or detected original signals. [0081] Assume the i-th segment is located between f _Lj and f _Hj Hz, where f _Li is the lowest frequency and f _Hi is the highest frequency of the i-th segment. The sampling rate for the i-th segment may be chosen in the range of

For each

segment, the common sampling rate may be the sampling rate determined by its own parameter n. For example, the common sampling rate for segment containing band 1 is determined by n _v . The common sampling rate for segment containing band 2 is determined by n ₂ . The common sampling rate for the segment containing band 1 may be properly chosen according to the range of f _sl , the common sampling rate for the segment containing band 2 may be properly chosen according to the range of f _S2 , and so on. The common sampling rate for the segments containing bands 1, K may be chosen according to the common ranges of f _sl ,...,f _SK . The common sampling rates may be the design parameters and may be chosen according to design needs and implementation.

[0082] According to another example, band reassembling may be used for compressed sensing. Figure 10 shows a flow diagram of an example method 1000 of compressed sensing employing band reassembling. A signal spectrum may be processed to generate at least one group of spectrum bands using band grouping and/or band partitioning, 1005. There may be several variants of band reassembling, for example, band reassembling using band grouping, or band reassembling using partitioning of bands. Band reassembling may be achieved by bandpass sampling.

[0083] Within each group, the spectrum bands may be pre-filtered, bandpass sampled and translated down to lower frequencies using a common sampling rate, 1010. Through the use of appropriate sampling rates, the bandpass signals of multiple bands may be bandpass sampled and translated down, through aliasing, to lower center frequencies and resulting signals may be filtered, for example, using a LPF. The entire group of bandpass signals may be sampled with a common and appropriately chosen sampling rate. The common sampling rate may be chosen, for example, such that the bandpass signals of multiple bands translate down via use of appropriate and unique Nyquist zones, and the bandpass signals of multiple bands may end up closer to each other at a lower center frequency. Each sampled and translated group of spectrum bands may be processed by a single corresponding compressed sampling receiver, 1015.

[0084] Figure 11 shows an example of band reassembling of bandpass signals where sparsity is present. Figure 11 shows bandpass signals 1,...,K where each of the K bandpass signals may have sparsity within. Through the use of appropriate sampling rates, the bandpass signals may be bandpass sampled and translated down, through aliasing, to lower center frequencies, as shown in Figure 11. The entire group of K bandpass signals may be sampled with a common and appropriately chosen sampling rate, and the translated group may then be processed by a single compressed sampling receiver.

[0085] As shown in Figure 11, all bands of interest Ι,.,.,Κ may be shifted to a lower frequency or DC and may be pre-filtered and may be processed by a single compressed sensing receiver. For example, by doing so, not only the "bad" sparsity from DC or lower frequency to the lowest frequency of the lowest band (band 1) may be removed, but also the additional "bad" sparsity between bands may be removed.

[0086] The signals in Figure 11 may be processed by a receiver such as, for example, the receiver shown in Figure 7. With reference to Figure 7, the original signal of all bands may be pre-processed and pre-filtered by spectrum shift and reassembly block 702 to down convert and shift the spectrum at high frequency to low frequency or DC. The resulting signal may then be processed by one or multiple RF branches 703i... _m , which each may include a mixer 704i...m, a LPF 706i... _m , and a 708i... _m . The sampled signal yl, y2, ym may then be fed to compressed sensing recovery engine 710 to detect or recover the original signal X(f). The detected or recovered signal X(f) may be, for example, the spectrum profiles, power spectrum density (PSD), spectrum whitespaces, or detected original signals.

[0087] Assume the i-th band is located between ^ ^Li and ^ ^Hi Hz, where is the lowest frequency and ^ ^Hi is the highest frequency of the i-th band.

The sampling rate for the i-th band is ⁿ ' ¹ for some integer

where For two bands, the common sampling rate may be the sampling rate determined by ^Hl and " ² . The common sampling rate may be chosen according to and . For K bands the common sampling rate may be the sampling rate determined by "i , ⁿ i and ^η κ . The common sampling rate may be chosen according to , and ^ ^sK . The common sampling rate may be chosen according to design needs and implementation. The approach may be extended to an arbitrary number of bands using the same principle.

[0088] When using bandpass sampling for multiple signals, it may be challenging to find a common sampling frequency that may result in no overlap after frequency translation. Conditions may be such that the bands' translated images have overlaps that may not be avoided no matter what single common sampling frequency is chosen or, if a common sampling frequency is found, that common sampling frequency may be too high to be of practical value.

[0089] Figure 12 shows an example of band reassembling of bandpass signals with band grouping. In some case, translating groups of bandpass signals may be easier or may be the only way to perform the bandpass sampling. As shown in Figure 12, bands may be arranged into groups 1 through L. In this example, each group includes two subbands of interest, such that group 1 includes bands 1 and 2 and group L includes bands K-l and K. However, any number of bands may be included in each group, where the number of bands within a group may determine the number of RF branches used in a CS receiver. Each group of bands 1...L may be bandpass sampled using a corresponding sampling frequency for input into a corresponding CS receiver 1...L. The sampling frequencies used for each group may be different.

[0090] Translating smaller groups of bandpass signals may be easier or may be the only way to perform the bandpass sampling. A subset of the bands may be bandpass sampled and re-assembled using one common sampling frequency that is common for that subset of bands, for input into a corresponding compressive receiver. Another subset of the bands may be bandpass sampled and re-assembled using a different sampling frequency, common to that second subset of bands, for input into the another compressive sampling receiver.

[0091] With reference to the example of Figure 12, the bands may be first grouped into groups 1...L. Each group containing bands of interest may be pre-filtered and shifted to lower frequency or DC and resulting signals may be filtered and may be processed by a CS receiver. For example, group 1 containing bands 1 and 2 may be pre-filtered and shifted and down converted to lower frequency or DC, resulting signals may be filtered and processed by CS receiver 1; group L containing bands K-l and K may be pre-filtered and shifted and down converted to lower frequency or DC, resulting signals may be filtered and processed by CS receiver L. By doing so, not only the "bad" sparsity from DC or lower frequency to the lowest frequency of the lowest group may be removed, but also the additional "bad" sparsity between groups may be removed. For example, group 1 may have bandwidth W3 MHz, and group L may have bandwidth W4 MHz. In many cases, the total bandwidth of all groups combined (e.g. W3+W4+...) after spectrum shift and reassembly may be much smaller than W2 GHz after removing the gaps between groups, and much smaller than the original bandwidth Wl GHz after removing the "bad" sparsity. This may result in improved performance for compressed sensing.

[0092] The signals in Figure 12 may be processed by a receiver such as, for example, the receiver shown in Figure 9. With reference to Figure 9, group 1 containing bands 1 and 2 may be pre-processed and pre-filtered by first spectrum shift and band reassembly block 9021. Similarly, band group L containing bands K-1 and K may be pre-processed and pre-filtered by spectrum shift and band reassembly block 902L. The spectrum shift and assembly block 9021 may result in bands 1 and 2 being shifted to lower frequency. The spectrum shift and assembly block 902L may result in bands K-1 and K being shifted to lower frequency. The gaps between bands 1 and 2 may not be removed. Similarly, gaps between bands K-1 and K may not be removed. The output of spectrum shift and reassembly block 9021...L may go through one or multiple RF branches 9021...m, which each may include a mixer 9041...m, filtered by a LPF 9061...m and a sampling device 9081...m.

[0093] In this example, the output of sampling devices 9081... m may be fed pair-wise to recovery engines 9101...L to detect or recover the original signal X(f). In the example of Figure 9, for each spectrum shift and reassembly block 9021...L, there may be two RF branches associated with it. The detected or recovered signal may be the spectrum profiles, power spectrum density (PSD), spectrum whitespaces, or detected original signals.

[0094] Assume the i-th band group is located between ^ ^Li and ^ ^Hi Hz where ^ ^Li is the lowest frequency and ^ ^Hi is the highest frequency of the i-th band group. The sampling rate for the ii--tthh bbaanndd ggrroouupp mmaayy bbee

for some integer ' where For each band group, the common sampling rate may be the sampling rate determined by its corresponding parameter n. For example, the common sampling rate for band group containing bands 1 and 2 is determined by ^Ul . The common sampling rate for band group containing bands K-1 and K is determined by ^η κ . The common sampling rate for the band group containing bands 1 and 2 may be chosen according to the range of ^ ^sl , the common sampling rate for the band group containing bands K-1 and K may be chosen according to the range of ^ ^sl , and so on. The common sampling rates may be chosen according to the design needs and implementation.

[0095] Figure 13 shows an example of band reassembling of bandpass signals using band partitioning. Figure 13 shows bandpass signals 1...K where each of the K bandpass signals may have sparsity within. Through the use of appropriate sampling rates, subsets of bandpass signals may be sampled and translated down, through aliasing, to lower center frequencies. Subsets of the K bandpass signals may be sampled with L unique sampling rates and may then be forwarded for further processing by L different CS receivers 1...L. The common sample rate for each subset of the K bandpass signals may be chosen such that the K bandpass signals translate down via the use of appropriate and unique Nyquist zones, and the K bandpass signals may end up close to each other within each subset, at a lower center frequency.

[0096] As shown in Figure 13, the bands may be assigned to partitions.

Each partition may contain one or more bands of interest. The bands in each partition may be shifted to lower frequency or DC and may be processed by a corresponding CS receiver. For the example shown in Figure 13, a first partition may contain bands 1 and K, which are pre-filtered, shifted and down converted to lower frequency or DC, resulting signals are filtered and processed by CS receiver 1. A second partition may contain, for example, bands 2 and K-1, which are pre-filtered, shifted and down converted to lower frequency or DC, resulting signals are filtered and processed by CS receiver L. By doing so, not only the "bad" sparsity from DC or lower frequency to the lowest frequency of the lowest band may be removed, but also the additional "bad" sparsity between bands may be removed. For example, as shown in Figure 13, the CS receiver 1 may have signal bandwidth W3 MHz, and CS receiver L may have signal bandwidth W4 MHz. In many cases after spectrum shift and reassembly, a sampling bandwidth of W3 MHz or W4 MHz may be much smaller than W2 GHz after removing the spectrum gaps or sparsity between groups, and the spectrum gaps or sparsity between bands (for example, removing gaps or sparsity between bands 1 and K, and removing gaps or sparsity between bands 2 and K-1). Bandwidths W3 MHz and W4 MHz is also much smaller than the original bandwidth Wl GHz after removing the "bad" sparsity. This may result in better performance for compressed sensing.

[0097] As shown in Figure 13, the bands belonging to the partition containing bands 1 and K may have bandwidth of W3 MHz, and the bands belonging to the partition containing bands 2 and K-1 may have bandwidth of W4 MHz.

[0098] The signals in Figure 13 may be processed by a receiver such as, for example, the receiver shown in Figure 9. With reference to Figure 9, the first partition containing bands 1 and K may be pre-processed and pre-filtered by first spectrum shift and band reassembly block 9021. Similarly, the Lth partition containing bands 2 and K-1 may be pre-processed and pre-filtered by spectrum shift and band reassembly block 902L. The spectrum shift and assembly block 9021 may result in bands 1 and K being shifted and reassembled to be adjacent to each other. The spectrum shift and assembly block 902L may result in bands 2 and K-1 being shifted and reassembled to be adjacent to each other. The gaps between bands 1 and K may be removed. Similarly, gaps between bands 2 and K-1 may be removed. The output of spectrum shift and reassembly block 9021...L may go through one or multiple RF branches 9021...m, which each may include a mixer 9041...m, filtered by a LPF 9061...m and a sampling device 9081...m. The outputs rl...L of recovery engines 9101...L may be combined or aggregated using an aggregation engine 912 to form a complete set of detected or recovered signals X(f). The detected or recovered signal X(f) may be, for example, the spectrum profiles, power spectrum density (PSD), spectrum whitespaces, or detected original signals.

[0099] Assume the i-th band is located between ^ ^Li and ^ ^Hi Hz where is the lowest frequency and ^ ^Hi is the highest frequency of the i-th band.

The sampling rate for the i-th band is for some integer ^η '

where For each partition the common sampling rate may be the sampling rate determined by the parameters n of the corresponding bands. For example, the common sampling rate for partition containing bands 1 and

K may be determined by "i and ^η κ . The common sampling rate for partition containing bands 2 and K-l may be determined by "2 . and ^sK - ¹ . The common sampling rate for the partition containing bands 1 and K may be chosen according to and ^ ^sK , the common sampling rate for the partition containing bands 2 and K-l may be chosen according to and ^ ¹ , and so on. The common sampling rates may be chosen according to the design needs and implementation. In a scenario where there are many bands of interest, a band partitioning approach may be used. The number of bands belonging to the same partition may be limited to two or three to enable a simpler implementation of bandpass sampling in terms of determining the common sampling rate.

[0100] By using the above described methods, the sampling bandwidth in the example of Figure 13 may be reduced to W2, W3 or W4 MHz which may be much smaller than original sampling bandwidth Wl GHz. For example, Wl may be 6 GHz, W2 may be 1 to 2 GMz and W3 or W4 may be 50 to 300 MHz.

[0101] A spectrum gap of Z Hz may be created when band reassembling is performed. The spectrum gap of Z Hz may be predesigned such that additional spectrum sparsity is created. The spectrum gap of Z Hz may also be predesigned such that common sampling rate(s) for performing bandpass sampling may be easily found. The spectrum utilization may be defined as the occupied spectrum X Hz divided by total spectrum for sensing, for example, W3 Hz or Bl+B2+...+Bn+Z Hz. By properly increasing the value of Z, it may be possible to decrease spectrum utilization and thus increase spectrum sparsity. In order not to waste spectrum and sampling power, trade-off between spectrum gaps, sparsity and sampling reduction may be made.

[0102] Figure 14 shows an example of a sparse wideband signal. In this example, the spectral support of the signal may not extend below a frequency value fMIN Hz or above a frequency value fMAX Hz. In other words, the support of the signal may be limited to a frequency band ranging from fMIN to fMAX, where ^f MiD ^{= f} MiN + ( ^f MAx - ^f MiN )/ ² . Figure 15 shows an example of a receiver structure 1500 employing in-phase/quadrature (IQ) vector demodulation, which may be suitable for receiving the signal in Figure 14. The example receiver 1500 of Figure 15 may employ an IQ vector demodulator 1502 to shift the signal band of interest of input signal x(t) down to DC. The IQ vector demodulator 1502 local oscillator frequency, or Radio Frequency/Local Oscillator (RF/LO) frequency, may be set to, for example, fMID Hz as described in Figure 14. With reference to Figure 15, two modulated wideband converter (MWC) structures 1504 and 1506 may then be employed at baseband. Each MWC structure 1504 and 1506 may respectively include mixers 15081,1...I,m and 1508Q,l...Q,m, LPFs 15101,1...I,m and 1510Q,l...Q,m, and samplers 15121,1...I,m and 1512Q,l...Q,m (for example, A/D converters). The outputs of the I-path MWC yl,l[n] ...yl,m[n] and Q-path MWC yQ,l[n] ...yQ,m[n] may be pair- wise combined with a complex combiner 1514. The outputs yl[n] ...ym[n] of the complex combiner 1514 may then be sent to the information recovery engine 1516 to generate a recovered signal X(f). Figure 16 shows an example of down-converted complex baseband spectrum, which may be generated by the receiver 1500 of Figure 15.

[0103] Figure 17 shows another example of a sparse wideband signal. In this example, the spectral support of the signal may be limited to two distinct bands. The first band may extend from RfMINl Hz to RfMAXl Hz and the second band may extend from RfMIN2 Hz to RfMAX2 Hz.

[0104] Figure 18 shows another example of a receiver structure 1800, which may be suitable for receiving the signal shown in Figure 17. The example receiver 1800 of Figure 18 may employ a bandpass sampler 1801 to re-assemble the signal bands of interest of the input signal x(t) from RF to an intermediate frequency that may extend from DC to IfMAX. The bandpass sampler 1801 may include a mixer 1802 and a single tone local oscillator (LO) 1804. The LO frequency may be determined by algorithms in bandpass sampling. The output of the bandpass sampler 1801 may be sent to a single MWC structure 1806, which may include mixers 18081... n, LPFs 18101... m, and samplers 18121...m. The mixers 18081...n may use, for example, pseudo- noise signals pl(t)...pm(t) and the samplers 18121...m may be for example A/D converters. The outputs yl[n]...ym[n] of the MWC 1806 may then be sent to the information recovery engine 1814 to generate a recovered signal X(f). Figure 19 shows an example sparse-wideband signal spectrum re-assembled at baseband, as may result from the re-assembly performed in the receiver in Figure 18.

[0105] A method for use in wireless communications may include receiving a signal. The method may further include converting the signal to the frequency domain to generate a signal spectrum. The method may further include filtering the signal spectrum to generate at least one portion of the signal spectrum. The at least one portion of the signal spectrum may include at least one frequency band of interest. The method may further include shifting the at least one portion of the signal spectrum to a lower center frequency. The method may further include applying compressed sensing to the shifted at least one portion of the signal spectrum to generate a recovered signal. The at least one portion of the signal spectrum may include a spectrum chunk including the at least one frequency band of interest. The shifting of the at least one portion of the signal spectrum may include shifting the spectrum chunk.

[0106] The method may include segmenting the signal spectrum into a plurality of spectrum segments including the at least one frequency band of interest. The at least one portion of the signal spectrum may include the plurality of spectrum segments. The shifting of the at least one portion of the signal spectrum may include segment-wise shifting each of the plurality of spectrum segments. The applying compressed sensing may include applying compressed sensing separately to each of the plurality of spectrum segments. The shifting of the at least one portion of the signal spectrum may include bandpass sampling the at least one portion of the signal spectrum. The bandpass sampling may use a common sampling rate to shift the plurality of spectrum segments. The shifting of the at least one portion of the signal spectrum may include down converting the at least one portion of the signal spectrum. The recovered signal may be any one of the following: a spectrum profile, a power spectrum density (PSD), a spectrum whitespace, or a detected original signal. The filtering the signal spectrum and the shifting the at least one portion of the signal spectrum may use prior knowledge of the signal spectrum.

[0107] A method for use in a wireless communication system may include receiving a signal. The method may include converting the signal to the frequency domain to generate a signal spectrum. The method may include processing the signal spectrum to generate at least one group of spectrum bands. The at least one group of spectrum bands may be generated using band grouping. The at least one group of spectrum bands may be generated using band partitioning. For each group, the spectrum bands may be pre-filtered. For each group, the spectrum bands may be bandpass sampled. For each group, the spectrum bands may be translated to lower frequencies. For each group, a common sampling rate may be used. For each group, the pre-filtered, sampled and/or translated spectrum bands may be processed using a corresponding compressed sampling receiver and/or a corresponding recovery engine. For each group, the corresponding compressed sampling receiver may have a number of radio frequency (RF) branches corresponding to a number of spectrum bands in the group.

[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 can 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, UE, terminal, base station, RNC, or any host computer.

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