WO2014117849A1 - Annulation de brouillage de signaux de référence en collision dans des réseaux hétérogènes - Google Patents

Annulation de brouillage de signaux de référence en collision dans des réseaux hétérogènes Download PDF

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Publication number
WO2014117849A1
WO2014117849A1 PCT/EP2013/051945 EP2013051945W WO2014117849A1 WO 2014117849 A1 WO2014117849 A1 WO 2014117849A1 EP 2013051945 W EP2013051945 W EP 2013051945W WO 2014117849 A1 WO2014117849 A1 WO 2014117849A1
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Prior art keywords
reference signals
receiver
network node
channel
estimation
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PCT/EP2013/051945
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English (en)
Inventor
Shashi Kant
Basuki PRIYANTO
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Huawei Technologies Co., Ltd.
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Application filed by Huawei Technologies Co., Ltd. filed Critical Huawei Technologies Co., Ltd.
Priority to CN201380020178.6A priority Critical patent/CN104247312A/zh
Priority to PCT/EP2013/051945 priority patent/WO2014117849A1/fr
Priority to EP13704036.6A priority patent/EP2951938A1/fr
Publication of WO2014117849A1 publication Critical patent/WO2014117849A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • H04J11/005—Interference mitigation or co-ordination of intercell interference
    • H04J11/0056—Inter-base station aspects

Definitions

  • Implementations described herein relate generally to a receiver and a method in a receiver.
  • a mechanism for interference cancellation of colliding common reference symbols in a wireless communication network is herein described.
  • a receiver also known as User Equipment (UE) , mobile station, wireless terminal and/or mobile terminal is enabled to communicate wirelessly in a wireless communication system, sometimes also referred to as a cellular radio system.
  • the communication may be made, e.g., between two receivers, between a receiver and a wire connected telephone and/or between a receiver and a server via a Radio Access Network (RAN) and possibly one or more core networks.
  • RAN Radio Access Network
  • the wireless communication may comprise various communication services such as voice, messaging, packet data, video, broadcast, etc.
  • the receiver may further be referred to as mobile telephones, cellular telephones, computer tablets or laptops with wireless capability.
  • the receivers in the present context may be, for example, portable, pocket-storable, hand-held, computer- comprised, or vehicle-mounted mobile devices, enabled to communicate voice and/or data, via the radio access network, with another entity, such as another receiver or a server.
  • the wireless communication network covers a geographical area which is divided into cell areas, with each cell area being served by a radio network node, or base station, e.g., a Radio Base Station (RBS) , which in some networks may be referred to as transmitter, "eNB”, “eNodeB”, “NodeB” or “B node”, depending on the technology and terminology used.
  • the network nodes may be of different classes such as e.g. macro eNodeB, home eNodeB or pico base station, based on transmission power and thereby also cell size.
  • the expression "cell” may be used for denoting the radio network node itself.
  • the cell is also, or in normal terminology, the geographical area where radio coverage is provided by the radio network node/ base station at a base station site.
  • One radio network node, situated on the base station site, may serve one or several cells.
  • the radio network nodes communicate over the air interface operating on radio frequencies with the receivers within range of the respective radio network node.
  • radio network nodes may be connected, e.g., by landlines or microwave, to a Radio Network Controller (RNC) , e.g., in Universal Mobile Tele- communications System (UMTS) .
  • RNC Radio Network Controller
  • UMTS Universal Mobile Tele- communications System
  • BSC Base Station Controller
  • GSM Global System for Mobile Communications
  • radio network nodes which may be referred to as eNodeBs or eNBs, may be connected to a gateway, e.g., a radio access gateway, to one or more core networks.
  • a gateway e.g., a radio access gateway
  • the expressions downlink, downstream link or forward link may be used for the transmission path from the radio network node to the receiver.
  • the expression uplink, upstream link or reverse link may be used for the transmission path in the opposite direction, i.e., from the receiver to the radio network node.
  • a transmission from the radio network node in the downlink may encounter interference due to simultaneous transmissions from neighbour radio network nodes, or possibly from other wireless Radio Frequency (RF) transmitters.
  • RF Radio Frequency
  • a receiver before being able to receive downlink data from a serving radio network node, has to make a channel estimation.
  • the channel estimation is based on a reference signal emitted by the radio network node.
  • a number of reference signals have been defined in the LTE downlink, e.g., Cell-specific Reference Signal (CRS) .
  • CRS is transmitted in all subframes and in all resource blocks of the carrier.
  • the CRS serves as a reference signal for several purposes such as, e.g., demodulation, Channel state information measurements, Time- and frequency synchronization, and/or Radio Resource Management (RRM) and/or mobility measurements.
  • RRM Radio Resource Management
  • Heterogeneous networks comprise several radio network nodes, e.g. base stations or eNodeBs, in which the same frequency spectrum is being utilised.
  • a macro cell with larger cell coverage may contain one or more pico-cells, in order to increase the capacity, especially in the dense populated area, wherein the pico-cell may be deployed to provide a hot spot with enhanced network access for receivers within range.
  • CRS Cell-specific Reference Signal
  • a suggested solution to this problem which may be considered optimal in the Linear Minimum Mean Square Error (LMMSE) sense, is to obtain channel estimates jointly, which is named as joint-LMMSE hereby.
  • the joint-LMMSE solution coincide the Maximum A-Posteriori (MAP) solution, if the received signal and the desired signals of interest are jointly Gaussian distributed.
  • MAP Maximum A-Posteriori
  • the low-complexity methods may be categorized into two broad approaches; the non-iterative approach and the iterative/ recursive with CRS interference cancellation but heuristic approach .
  • the non-iterative approach simply comprises employing a single cell channel estimation filtering/smoothing unit to perform channel estimation of a target network node, or desired cell, while other interfering cells are modelled as noise in addition to the additive white Gaussian noise. In general, this approach renders a poor performance in terms of Mean Square Error (MSE) .
  • MSE Mean Square Error
  • CFRs Channel Frequency Responses
  • filtered/smoothed Channel Frequency Responses of the dominating received powered neighbour network node is obtained .
  • a replica of the CRS signal transmitted by the neighbour network node is created by multiplying the locally generated CRSs/pilots with the estimated Channel Frequency Responses.
  • the filtered/smoothed CFRs of the serving network node may be obtained. If required, one also may repeat the above process in order to further refine the channel estimation/CFR of the serving network node.
  • the colliding CRSs may be seen as superimposed CRSs at the receiver side, which is a multi-dimensional optimization problem.
  • the optimal approach joint-LMMSE or MAP is infeasible in the real target.
  • the non-iterative approach for channel estimation is to simply regard the problem as a single dimensional channel estimation problem and employ single cell channel estimation unit since in LTE the CRS signals of the serving network node across transmit antenna are orthogonal by design; and the colliding CRS signals of the neighbouring network node may be regarded as an additional noise.
  • the single cell channel estimation in interference- limited scenario would significantly degrade the performance.
  • the aforementioned iterative approaches are an ad- hoc/heuristic approaches wherein mainly iteration is performed among single cell channel estimation unit and Interference Cancellation (IC) unit.
  • IC Interference Cancellation
  • the object is achieved by a method in a receiver, for interference cancellation of colliding reference signals received from network nodes comprised in a heterogeneous wireless network, especially but not limited to, a macro-pico scenario.
  • the method comprises detecting colliding reference signals of a first network node and a second network node.
  • the method also comprises performing channel estimation by cancelling interference caused by the detected colliding reference signals of the second network node, from the reference signals of the first network node, based on iterative application of a Space Alternating Generalised Expectation and maximisation (SAGE) algorithm.
  • SAGE Space Alternating Generalised Expectation and maximisation
  • the object is achieved by a receiver, configured for interference cancellation of colliding reference signals received from network nodes comprised in a heterogeneous wireless network, especially but not limited to, a macro-pico scenario.
  • the receiver comprises a receiving unit, configured for receiving reference signals from the network nodes.
  • the receiver comprises a processing circuit, configured for detecting colliding reference signals of a first network node and a second network node, and also configured for cancelling interference caused by the detected colliding reference signals of the second network node, from the reference signals of the first network node, based on iterative application of a Space Alternating Generalised Expectation and maximisation (SAGE) algorithm.
  • SAGE Space Alternating Generalised Expectation and maximisation
  • the iterative approaches according to embodiments herein elegantly resolves the multi-dimensional problem into single- dimensional optimization problem, i.e. decompose the super ⁇ imposed CRS signals such that the single cell channel estimation filtering/smoothing can be applied for each de- composed CRS signal.
  • SAGE Space-Alternating Generalised Expectation and maximisation
  • EM Expectation Maximization
  • the throughput performance within the wireless communication system is further improved by increased signal processing technique.
  • Figure 1 is a block diagram illustrating a wireless communication network according to some embodiments.
  • Figure 2 is a block diagram illustrating an embodiment of a generic receiver architecture.
  • Figure 3 is a block diagram illustrating a time-frequency resource grid according to an embodiment of the invention .
  • Figure 4 is a block diagram illustrating a framework of a receiver according to an embodiment of the invention.
  • Figure 5 is a block diagram illustrating a framework of a receiver according to an embodiment of the invention.
  • Figure 6 is a diagram illustrating normalised throughput and noise ratio according to different approaches.
  • Figure 7 is a flow chart illustrating a method in a receiver according to an embodiment of the invention.
  • Figure 8 is a block diagram illustrating a receiver according to an embodiment of the invention.
  • Embodiments of the invention described herein are defined as a receiver and a method in a receiver, which may be put into practice in the embodiments described below. These embodiments may, however, be exemplified and realised in many different forms and are not to be considered as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete .
  • the heterogeneous wireless network 100 may at least partly be based on radio access technologies such as, e.g., 3GPP LTE, LTE-Advanced, Evolved Universal Terrestrial Radio Access Network (E-UTRAN) , Universal Mobile Telecommunications System (UMTS) , Global System for Mobile Communications (originally: Groupe Special Mobile) (GSM) / Enhanced Data rate for GSM Evolution (GSM/EDGE) , Wideband Code Division Multiple Access (WCDMA) , Time Division Multiple Access (TDMA) networks, Frequency Division Multiple Access (FDMA) networks, Orthogonal FDMA (OFDMA) networks, Single- Carrier FDMA (SC-FDMA) networks, Worldwide Interoperability for Microwave Access (WiMax) , or Ultra Mobile Broadband (UMB) , High Speed Packet Access (HSPA) Evolved Universal Terrestrial Radio Access (E-UTRA) , Universal Terrestrial Radio Access (UTRA) , GSM EDGE Radio Access Network (GERAN) , 3
  • the heterogeneous wireless network 100 may be configured to operate according to the Time Division Duplex (TDD) and/or the Frequency Division Duplex (FDD) principle, according to different embodiments.
  • TDD Time Division Duplex
  • FDD Frequency Division Duplex
  • TDD is an application of time-division multiplexing to separate uplink and downlink signals in time, possibly with a Guard Period situated in the time domain between the uplink and downlink signalling.
  • FDD means that the transmitter and receiver operate at different carrier frequencies, as have previously been discussed.
  • FIG. 1 The purpose of the illustration in Figure 1 is to provide a simplified, general overview of the wireless network 100 and the involved methods and nodes, such as the radio network node and receiver herein described, and the functionalities involved.
  • the methods, radio network node and receiver will subsequently, as a non-limiting example, be described in a 3GPP/LTE environment, but the embodiments of the disclosed methods, radio network node and receiver may operate in a heterogeneous wireless network 100 based on another access technology such as, e.g., any of the above enumerated.
  • 3GPP LTE 3GPP LTE
  • the illustrated heterogeneous wireless network 100 comprises a serving pico node 110, serving a receiver 120, and a number of neighbour network nodes, such as a first neighbour macro node 130-a, a second neighbour macro node 130-b, a neighbour pico node 130-c and a third neighbour macro node 130-d.
  • the serving pico node 110 controls the radio resource management within the served cell, such as, e.g., allocating radio resources to the receiver 120 within the cell and ensuring reliable wireless communication between the pico node 110 and the receiver 120.
  • the pico node 110 may typically comprise an eNodeB, e.g., in an LTE-related heterogeneous wireless communication network 100.
  • this set up is merely an illustrating example.
  • a network node such as an eNodeB may provide communication coverage for a macro cell, a pico cell, a femto cell, and/or other types of cell.
  • a macro cell generally covers a relatively large geographic area e.g., several kilometers in radius and may allow unrestricted access by receivers 120 with service subscriptions with the network provider.
  • a pico cell may generally cover a relatively smaller geographic area and may allow unrestricted access by receivers 120 with service subscriptions with the network provider.
  • a femto cell may also generally cover a relatively small geographic area such as e.g., a home and, in addition to unrestricted access, may also provide restricted access by receivers 120 having an association with the femto cell such as e.g., receivers 120 comprised in a closed subscriber group (CSG) , receivers 120 of users in the home, and the like.
  • a network node for a macro cell may be referred to as a macro network node or a macro eNodeB.
  • a network node for a pico cell may be referred to as a pico network node, or pico eNodeB.
  • a network node for a femto cell may be referred to as a femto network node, a femto eNodeB, a home network node or a home eNodeB, according to some terminology.
  • the receiver 120 is configured to receive radio signals comprising information transmitted by the serving pico node 110. Correspondingly, the receiver 120 is configured to transmit radio signals comprising information to be received by the serving pico node 110.
  • the heterogeneous wireless network 100 may comprise any other number and/or combination of radio network nodes 110, 130 and/or receivers 120 and/or macro/pico/micro/femto cells.
  • a plurality of receivers 120 and another configuration of radio network nodes 110, 130 may further be involved in some embodiments of the disclosed invention.
  • receiver 120 and/or radio network node 110, 130 may be involved, according to some embodiments.
  • the receiver 120 may be represented by, e.g., a UE, a wireless communication terminal, a mobile cellular phone, a Personal Digital Assistant (PDA) , a wireless platform, a mobile station, a tablet computer, a portable communication device, a laptop, a computer, a wireless terminal acting as a relay, a relay node, a mobile relay, a Customer Premises Equipment (CPE) , a Fixed Wireless Access (FWA) nodes or any other kind of device configured to communicate wirelessly with the serving pico node 110, according to different embodiments and different vocabulary.
  • PDA Personal Digital Assistant
  • CPE Customer Premises Equipment
  • FWA Fixed Wireless Access
  • the serving pico node 110 and/or the neighbour pico node 130-c may according to some embodiments be referred to, respectively, as e.g., a base station, NodeB, evolved Node Bs (eNB, or eNode B) , base transceiver station, Access Point Base Station, base station router, Radio Base Station (RBS), micro base station, pico base station, femto base station, Home eNodeB, sensor, beacon device, relay node, repeater or any other network node configured for communication with the receiver 120 over a wireless interface, depending, e.g., of the radio access technology and terminology used.
  • a base station NodeB, evolved Node Bs (eNB, or eNode B) , base transceiver station, Access Point Base Station, base station router, Radio Base Station (RBS), micro base station, pico base station, femto base station, Home eNodeB, sensor, beacon device, relay node, repeater or any other network node configured for
  • the neighbour macro nodes 130-a, 130-b, 130-d may according to some embodiments be referred to as, e.g., base stations, NodeBs, evolved Node Bs (eNBs, or eNode Bs) , base transceiver stations, Access Point Base Stations, base station routers, Radio Base Stations (RBSs) , macro base stations, sensors, beacon devices, relay nodes repeaters or any other network nodes configured for communication with the receiver 120 over a wireless interface, depending, e.g., of the radio access technology and terminology used.
  • eNBs evolved Node Bs
  • eNode Bs evolved Node Bs
  • RBSs Radio Base Stations
  • macro base stations sensors, beacon devices, relay nodes repeaters or any other network nodes configured for communication with the receiver 120 over a wireless interface, depending, e.g., of the radio access technology and terminology used.
  • Such enhancement may comprise, according to different embodiments, e.g. Reference Signal Received Power (RSRP) and/or Reference Signal Received Quality (RSRQ) estimation of the serving network node 110 or neighbour network nodes 130.
  • RSRP Reference Signal Received Power
  • RSRQ Reference Signal Received Quality
  • Other embodiments may comprise serving-cell Physical Downlink Shared Channel (PDSCH) and/or Physical Downlink Control Channel (PDCCH) demodulation.
  • Further embodiments may comprise e.g. Channel Quality Indicator (CQI) estimation of the serving-cell 110, cell-search, etc.
  • CQI Channel Quality Indicator
  • CRS- ICs Two embodiments of iterative CRS interference cancellers (CRS- ICs) are presented herein, for colliding CRSs scenario.
  • One important unit comprised in the receiver 120 for CRS-IC is a channel estimator.
  • the proposed embodiments are based on the theory of SAGE-MAP which is guaranteed to converge, unlike heuristic/intuitive approaches.
  • the prior art approach renders inferior performance compared to both the first proposed approach with the same complexity in terms of iterations and smoothing filter of channel frequency responses.
  • a low complexity channel estimator unit utilises only serving cell 110 and neighbour cell 130 CRSs.
  • the quality of serving cell channel estimating may be further enhanced by utilising both the CRSs and the a-posteriori log-likelihood ratios (LLRs) rendered from the MIMO demodulator but with the nature of increased signal processing techniques and thereby complexity, according to some embodiments.
  • LLRs log-likelihood ratios
  • CRS Cell-specific Reference Signals
  • the disclosed framework is not limited to colliding CRS scenario.
  • Other embodiments may be extended for other reference signals such as e.g. synchronisation signals, control-channels e.g., Physical Broadcast Channel (PBCH) cancellation in a HetNet scenario .
  • PBCH Physical Broadcast Channel
  • Figure 2 discloses a generic receiver architecture depicting iterative channel estimator utilising messages from the Multiple-Input and Multiple-Output (MIMO) detector/ demodulator .
  • MIMO Multiple-Input and Multiple-Output
  • SAGE Space-Alternating Generalised Expectation and maximisation
  • one or more antenna ports may be defined for the broadcast channel.
  • An advantage according to some embodiments with having one antenna port may comprise easier and more robust channel estimation as there is no interference between antenna ports.
  • An advantage with having more than one antenna port may comprise the possibility of using transmit diversity.
  • the receiver 120 may comprise, according to some embodiments, a number of receiver amplifier and filter 210, 215. Further, the receiver 120 may comprise units for radio frequency downconvert 220, 225. In addition, a number of Orthogonal Frequency-Division Multiplexing (OFDM) demodulators 230, 235 may be comprised. Furthermore, one or more antenna de-mapping units 240 may be comprised in the receiver 120. In addition, the receiver 120 may comprise one or more resource de-mapping units 250. Furthermore, the receiver 120 may comprise a MIMO detection unit 260 and a channel estimation unit 270, which may operate in an iterative manner in some embodiments, for interference cancellation of colliding reference signals received from network nodes 110, 130. In addition, one or more decoders 280 and/or data sinks 290 may be comprised.
  • OFDM Orthogonal Frequency-Division Multiplexing
  • FIG. 3 An example of the colliding CRS is illustrated in Figure 3 assuming for simplicity that there are two network nodes 110, 130, such as one serving network node 110 and one neighbour network node 130 equipped with single transmit antenna port, and considering only normal cyclic prefix. Further, for the brevity, it is assumed that the neighbour network node 130 is timing- and frequency-wise synchronised with the serving network node 110.
  • Figure 3 shows an example wherein time-frequency resources defined for antenna port 0 are used by the antenna ports for the broadcast channel of the serving network node 110 and the neighbour network node 130, in a subframe 300 comprising a first resource block 310-1 and a second resource block 310-2.
  • a resource block 310 comprises a set of resource elements or a set of time- frequency resources and is of 0.5 ms duration (e.g., 7 Orthogonal Frequency-Division Multiplexing (OFDM) symbols) and 180 kHz bandwidth (e.g., 12 subcarriers with 15 kHz spacing) .
  • OFDM Orthogonal Frequency-Division Multiplexing
  • the LTE standard refers to a Physical Resource Block (PRB) as a resource block 310 where the set of OFDM symbols in the time-domain and the set of subcarriers in the frequency domain are contiguous.
  • PRB Physical Resource Block
  • the transmission bandwidth of the system may be divided into a set of resource blocks 310. Typical LTE carrier bandwidths correspond to 6, 15, 25, 50, 75 and 100 resource blocks 310.
  • Each transmission of user data on the Physical Downlink Shared Channel (PDSCH) is performed over 1 ms duration, which is also referred to as a subframe 300, on one or several resource blocks 310.
  • a radio frame consists of 10 subframes 300, or alternatively 20 slots of 0.5 ms length (enumerated from 0 to 19), according to different embodiments.
  • Figure 4 depicts a block diagram of a receiver 120 according to a first embodiment, illustrating the main constituents of the colliding interference cancellation of cell specific reference signals in a scenario of Pilots-based SAGE-MAP.
  • Figure 4 illustrates a framework of a receiver 120, corresponding to first embodiment, depicting an iterative channel estimation unit for colliding CRSs scenario.
  • the neighbour cell estimated channel state information may be further processed, e.g. for cell measurements, according to some embodiments.
  • each radio network nodes 110, 130 has N CRS (and equivalently transmit antenna) ports, then at the v- th receive antenna of the receiver 120, the post- Fast Fourier Transform (FFT) received (superimposed CRS) signal reads:
  • FFT post- Fast Fourier Transform
  • Equation 1 may equivalently be re-written as:
  • X H is a diagonal matrix of (known) CRS from the corresponding u-th virtual transmit antenna port, i.e., equivalently, n-t transmit antenna of an m-t radio network node 110, 130.
  • N corresponds to a zero-mean circularly-symmetric complex white Gaussian noise vector with a covariance matrix R N .
  • H v a is a CFR vector for v-u rx-tx path, i.e., path corresponding to u-th virtual transmit antenna port at the v- th receive antenna.
  • a pseudo-algorithm for the SAGE-MAP based processing per receive antenna port may be as following.
  • the online matrix inversion is not required since it may be pre-computed and selected from a set of pre-computed matrices for an estimated noise variance accordingly.
  • the complexity of this scheme may be similar as in the previously discussed ad-hoc approach but rendering superior performance.
  • the ad-hoc approach for channel estimation and noise variance estimation have similar steps as in the presented SAGE-MAP based iterative channel estimation unit processing, however as supported via simulations that SAGE-MAP renders better performance than the heuristic approach which may probably be explained the way SAGE estimates/updates one channel frequency response corresponding to each rx-tx path and noise variance per SAGE iteration.
  • the embodiment described above utilises only CRS of both serving network node 110 and neighbour node 130 to estimate channel frequency response and noise variance.
  • the channel frequency response of serving network node 110 may be further improved and thereby the serving network node demodulation performance by utilising not only the CRS of the serving network node 110 but also the (partially) known data of respective codeword in the form of
  • the LLRs available after the MIMO demodulator or Turbo decoder are available after the MIMO demodulator or Turbo decoder.
  • the framework of the second embodiment is illustrated in Figure 5, comprising semi-blind SAGE-MAP CRS interference cancellation .
  • the previously presented SAGE-MAP algorithm may be re-utilised with minor modifications in order to support semi-blind iterative CRS interference cancellation, according to some embodiments.
  • the changes may comprise to update the aforementioned X H matrix for the serving network node 110 which comprises soft-data in addition to the serving cell CRS whereas the soft-data corresponding to the neighbour cells 130 would be set to zeros.
  • the SAGE algorithm at the CRS resource element positions is, in principle, decomposing the superimposed CRS signals; and at the serving cell data carrying resource elements, SAGE is decomposing (intra-cell superimposed data streams) MIMO channels into respective SISO channels.
  • the soft- symbols may be obtained by performing appropriate transformation of soft-bits (LLRs) .
  • the effective noise variance may comprise the soft-symbol variance from all the serving cell transmit antennas in addition to the above estimated noise variance according to some embodiments. Notice that in semi-blind approach, the soft data is updated in every update of LLRs, and hence the online matrix inversion is required in general.
  • the presented method embodiment may not be dealing with the low-complexity version of time-variant MAP filtering herein.
  • the LLRs available after MIMO demodulator may only be utilised with slight or negligible degradation in performance compared to the LLRs available after the Turbo channel decoder.
  • the semi-blind method may improve the quality of estimated channel frequency response and thereby the throughput performance, particularly under highly time and frequency selective channels and relatively high Signal-to-Noise-Ratio (SNR) regime.
  • SNR Signal-to-Noise-Ratio
  • the effect according to some embodiments may comprise improving the receiver performance with considerably low channel estimation unit in colliding CRS Heterogeneous Network scenario.
  • the performance may be further enhanced by increasing complexity as described in the second embodiment, illustrated in Figure 5.
  • Figure 6 illustrates a comparison between normalised throughput versus SNR (Es/Noc2) [dB] for a test scenario, comprising: 2 Cells (one serving cell 110 and one neighbour cell 130), Colliding CRS Scenario, 2x2 Transmit Div. (SFBC) , 10 MHz, 16QAM0.5, EVA70 MED.
  • Es/Noc2 normalised throughput versus SNR
  • the normalised throughput performance versus SNR of the first embodiment i.e., utilising only CRSs
  • SNR the normalised throughput performance versus SNR of the first embodiment
  • the legend "Ideal NC-CRS IC” corresponds to an ideal NC-CRS interference cancellation of CRS from a neighbour cell 130, but with practical serving cell channel estimation in order to have fair comparison with other cancellation scheme.
  • the legend "SAGE (Iter 3)” corresponds to the algorithm according to an embodiment of the invention with 3 iterations, which performs as good as “Ideal NC-CRS IC” over the entire SNR regime .
  • the legend "Ad-hoc Approach (Iter3)” corresponds to the ad-hoc approach according to prior art, which has poor performance compared to the proposed state-of-the-art in relatively mid to high SNR regime.
  • the pilots-based iterative CRS interference cancellation in colliding CRS scenario via a SAGE-MAP algorithm according to some embodiments.
  • a semi-blind iterative CRS interference cancellation approach in a colliding CRS scenario is presented.
  • Figure 7 is a flow chart illustrating embodiments of a method 700 in a receiver 120 for interference cancellation of colliding reference signals received from a first network node 110 and a second network node 130 comprised in a heterogeneous wireless network 100, especially but not limited to, a macro- pico scenario, as previously illustrated in Figure 1.
  • the first network node 110 may be serving the receiver 120, while the second network node 130 may be a neighbour network node, according to some embodiments.
  • the heterogeneous wireless network 100 may be based on 3rd Generation Partnership Project Long Term Evolution (3GPP LTE) system.
  • the reference signals may comprise cell specific reference signals (CRS) .
  • the receiver 120 may be a User Equipment (UE) .
  • the serving radio network node 110, and/or the neighbour network node 130 may be an evolved NodeB, eNodeB.
  • Signals may be received on the downlink data channel and/or a control channel according to some embodiments.
  • the data channel may be a Physical Downlink Shared Channel (PDSCH) .
  • the control channel may be an Enhanced Physical Downlink Control Channel (EPDCCH) according to some embodiments.
  • PDSCH Physical Downlink Shared Channel
  • EPDCCH Enhanced Physical Downlink Control Channel
  • the method 700 may comprise a number of actions 701-703.
  • the method 700 may comprise the following actions:
  • Colliding reference signals of a first network node 110 and a second network node 130 are detected.
  • the receiver 120 may detect interference between the serving network node 110 and one or more neighbour network node/s 130.
  • the colliding reference signals may comprise e.g. Common Reference Signals (CRS), or similar cell specific signals according to some embodiments.
  • CRS Common Reference Signals
  • Channel estimation is performed by cancelling interference caused by the detected 701 colliding reference signals of the second network node 130, from the reference signals of the first network node 110, based on iterative application of a Space Alternating Generalised Expectation and maximisation (SAGE) algorithm.
  • SAGE Space Alternating Generalised Expectation and maximisation
  • the channel estimation may be performed with a Maximum A Posteriori (MAP) criterion, based on the reference signals of the first network node 110 from which interference has been cancelled.
  • MAP Maximum A Posteriori
  • the channel estimation may further comprise, according to some embodiments: noise variance estimation, Channel Frequency Response (CFR) , Received Signal Strength Indicator (RSSI), estimation of received signal power such as e.g. Reference Signal Received Power (RSRP) , estimation of received signal quality such as e.g. Reference Signal Received Quality (RSRQ) , Channel Quality Indicator (CQI) estimation and/or cell-search, according to some embodiments.
  • CFR Channel Frequency Response
  • RSSI Received Signal Strength Indicator
  • estimation of received signal power such as e.g. Reference Signal Received Power (RSRP)
  • RSRPQ Reference Signal Received Quality
  • CQI Channel Quality Indicator
  • the output of the channel estimation may further be processable by demodulation and decoding of the first network node 110, according to some embodiments.
  • Action 703 This action may be performed according to some optional embodiments .
  • the channel estimation may be enhanced, based on a posteriori Log-Likelihood Ratios (LLR) of data transmitted by the first network node 110, which is serving the receiver 120, thereby performing a semi-blind channel estimation.
  • LLR Log-Likelihood Ratios
  • the enhanced channel estimation may further comprise decomposing the interfering reference signals of the network nodes 110, 130, and decomposing data on Multiple-Input and Multiple-Output (MIMO) channel into respective Single-Input Single-Output (SISO) channel, according to some embodiments.
  • MIMO Multiple-Input and Multiple-Output
  • SISO Single-Input Single-Output
  • FIG 8 is a block diagram illustrating a receiver 120 in a heterogeneous wireless network 100.
  • the receiver 120 is configured for receiving wireless signals such as e.g. reference signals from a radio network node 110, 130 within the heterogeneous wireless network 100. Further, the receiver 120 is configured for receiving the above mentioned method 700 according to any, some or all of the actions 701-703 for interference cancellation of colliding reference signals received from network nodes 110, 130 comprised in the heterogeneous wireless network 100, especially but not limited to, a macro-pico scenario, as previously illustrated in Figure 1.
  • the first network node 110 may be serving the receiver 120, while the second network node 130 may be a neighbour network node, according to some embodiments.
  • the heterogeneous wireless network 100 may be based on 3rd Generation Partnership Project Long Term Evolution (3GPP LTE) system.
  • the reference signals may comprise cell specific reference signals (CRS) .
  • the receiver 120 may be a User Equipment (UE) .
  • the serving radio network node 110, and/or the neighbour network node 130 may be an evolved NodeB, eNodeB.
  • Signals may be received on the downlink data channel and/or a control channel according to some embodiments.
  • the data channel may be a Physical Downlink Shared Channel (PDSCH) .
  • the control channel may be an Enhanced Physical Downlink Control Channel (EPDCCH) according to some embodiments.
  • PDSCH Physical Downlink Shared Channel
  • EPDCCH Enhanced Physical Downlink Control Channel
  • the receiver 120 comprises a receiving unit 810, configured for receiving reference signals from the network nodes 110, 130.
  • the receiver 120 comprises a processing circuit 820, configured for detecting colliding reference signals of a first network node 110 and a second network node 130. Further, the processing circuit 820 is further configured for cancelling interference caused by the detected colliding reference signals of the second network node 130, from the reference signals of the first network node 110, based on iterative application of a Space Alternating Generalised Expectation and maximisation (SAGE) algorithm. Furthermore, the processing circuit 820 may be further configured for performing channel estimation with a Maximum A Posteriori (MAP) criterion, based on the reference signals of the first network node 110 from which interference has been cancelled, according to some embodiments. The processing circuit 820 may be further configured for performing: noise variance estimation, Channel Frequency Response (CFR) , estimation of received signal power, estimation of received signal quality, Channel Quality Indicator (CQI) estimation and/or cell-search, according to some embodiments.
  • CFR Channel Frequency Response
  • CQI Channel Quality Indicator
  • the processing circuit 820 may be further configured for enhancing channel estimation based on a posteriori Log-Likelihood Ratios (LLR) of data transmitted by the first network node 110, which is serving the receiver 120. Furthermore, the processing circuit 820 may be further configured for decomposing the interfering reference signals of the network nodes 110, 130, and also configured for decomposing data on Multiple-Input and Multiple-Output, (MIMO) channel into respective Single-Input Single-Output (SISO) channel, according to some embodiments.
  • MIMO Multiple-Input and Multiple-Output
  • SISO Single-Input Single-Output
  • the processing circuit 820 may comprise, e.g., one or more instances of a Central Processing Unit (CPU) , a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC) , a microprocessor, or other processing logic that may interpret and execute instructions.
  • CPU Central Processing Unit
  • ASIC Application Specific Integrated Circuit
  • processing circuit may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones enumerated above.
  • the processing circuit 820 may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as call processing control, user interface control, or the like.
  • the receiver 120 may comprise at least one memory 825, according to some embodiments.
  • the memory 825 may comprise a physical device utilised to store data or programs, i.e., sequences of instructions, on a temporary or permanent basis.
  • the memory 825 may comprise integrated circuits comprising silicon-based transistors. Further, the memory 825 may be volatile or non ⁇ volatile.
  • the receiver 120 may also comprise a transmitting unit 830, configured for transmitting information in the uplink, to be received by the serving network node 110 according to some embodiments.
  • the actions 701-703 to be performed in the receiver 120 may be implemented through the one or more processing circuits 820 in the receiver 120, together with computer program code for performing the functions of the actions 701-703.
  • a computer program product comprising instructions for performing the actions 701-703 in the receiver 120 may perform the method 700 for interference cancellation of colliding reference signals received from network nodes 110, 130 comprised in a heterogeneous wireless network 100, when the computer program product is loaded in a processing circuit 820 of the receiver 120.
  • the computer program product mentioned above may be provided for instance in the form of a data carrier carrying computer program code for performing at least some of the actions 701- 703 according to some embodiments when being loaded into the processing circuit 820.
  • the data carrier may be, e.g., a hard disk, a CD ROM disc, a memory stick, an optical storage device, a magnetic storage device or any other appropriate medium such as a disk or tape that may hold machine readable data in a non transitory manner.
  • the computer program product may furthermore be provided as computer program code on a server and downloaded to the receiver 120 remotely, e.g., over an Internet or an intranet connection.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

L'invention porte sur un récepteur (120) et un procédé (700) dans un récepteur (120) pour annulation de brouillage de signaux de référence en collision reçus en provenance de nœuds de réseau (110, 130) inclus dans un réseau sans fil hétérogène (100), en particulier mais non exclusivement dans un scénario macro-pico. Le procédé (700) consiste à détecter (701) des signaux de référence en collision d'un premier nœud de réseau (110) et d'un second nœud de réseau (130). En outre, le procédé (700) consiste à effectuer (702) une estimation de canal par annulation du brouillage causé par les signaux de référence en collision détectés (701) du second nœud de réseau (130) dans les signaux de référence du premier nœud de réseau (110), sur la base d'une application par itérations d'un algorithme d'espérance-maximisation généralisé à alternance d'espace « SAGE ».
PCT/EP2013/051945 2013-01-31 2013-01-31 Annulation de brouillage de signaux de référence en collision dans des réseaux hétérogènes WO2014117849A1 (fr)

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CN201380020178.6A CN104247312A (zh) 2013-01-31 2013-01-31 无线通信网络中的方法和节点
PCT/EP2013/051945 WO2014117849A1 (fr) 2013-01-31 2013-01-31 Annulation de brouillage de signaux de référence en collision dans des réseaux hétérogènes
EP13704036.6A EP2951938A1 (fr) 2013-01-31 2013-01-31 Annulation de brouillage de signaux de référence en collision dans des réseaux hétérogènes

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