EP2951938A1

EP2951938A1 - Interference cancellation of colliding reference signals in heterogeneous networks

Info

Publication number: EP2951938A1
Application number: EP13704036.6A
Authority: EP
Inventors: Shashi Kant; Basuki PRIYANTO; Gengshi Wu; Sha HU
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2013-01-31
Filing date: 2013-01-31
Publication date: 2015-12-09
Also published as: CN104247312A; WO2014117849A1

Abstract

Receiver (120) and method (700) in a receiver (120), for interference cancellation of colliding reference signals received from network nodes (110, 130) comprised in a heterogeneous wireless network (100), especially but not limited to, a macro-pico scenario. The method (700) comprises detecting (701) colliding reference signals of a first network node (110) and a second network node (130). Further, the method (700) comprises performing (702) channel estimation 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.

Description

INTERFERENCE CANCELLATION OF COLLIDING REFERENCE SIGNALS IN

HETEROGENEOUS NETWORKS

FIELD OF INVENTION

Implementations described herein relate generally to a receiver and a method in a receiver. In particular is herein described a mechanism for interference cancellation of colliding common reference symbols in a wireless communication network .

BACKGROUND OF INVENTION

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.

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.

Sometimes, the expression "cell" may be used for denoting the radio network node itself. However, 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.

In some radio access networks, several 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) . The RNC, also sometimes termed Base Station Controller (BSC), e.g., in GSM, may supervise and coordinate various activities of the plural radio network nodes connected thereto. GSM is an abbreviation for Global System for Mobile Communications (originally: Groupe Special Mobile) .

In 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) , 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. In the present context, 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. However, 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. On the uplink, a transmission made from the receiver may encounter interference from uplink transmissions of other receivers communicating with the neighbour base stations or from other wireless RF transmitters. This interference may degrade performance on both the downlink and uplink and is therefore undesired . 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.

Heterogeneous networks (HetNets) comprise several radio network nodes, e.g. base stations or eNodeBs, in which the same frequency spectrum is being utilised. Depending on the network deployment, 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.

The number of non-colliding Cell-specific Reference Signal (CRS) in heterogeneous network scenario is quite limited. In case of the CRS of the Serving radio network node (SC) collides with the CRSs of multitude of Neighbour radio network nodes (NCs) , the quality of the SC Channel Estimates (CE) would degrade significantly and thereby the throughput performance - if the interfering CRS signals from neighbouring radio network nodes are either ignored or not properly cancelled/mitigated.

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. Furthermore, 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. However, due to formidably high complexity of multi-dimensional joint-LMMSE optimization problem, particularly due to unavoidable online matrix inversion, the optimal solution is not feasible on the real target implementation.

Hence, a low-complexity solution is sought with negligible performance degradation compared to the optimal joint-LMMSE solution.

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) .

According to the iterative/recursive with CRS interference cancellation but heuristic approach; when the received power of the serving network node is higher compared to the received power of the neighbour network nodes, simply obtain filtered/ smoothed Channel Frequency Responses (CFRs) of the serving network node via single cell channel estimation unit.

However, when the received power of the serving network node is lower than the other neighbour network nodes, the following procedure is performed.

Firstly, 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.

Subsequently subtract the re-created interfering CRS signal from the received signal. Further, if needed, then other dominating interfering signals can also be cancelled accordingly.

Further, after removing all dominating interference signals from the received signal, 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. As mentioned above, 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. However, 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. However, this often used and intuitive approach is not guaranteed to converge and may render poor performance .

SUMMARY OF INVENTION It is therefore an object to obviate at least some of the above mentioned disadvantages and to improve the performance in a wireless communication network. According to a first aspect, 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.

According to a second aspect, 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. Further, 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.

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. Moreover, Space-Alternating Generalised Expectation and maximisation (SAGE) algorithm is also known to have faster convergence compared to well known iterative approach based on Expectation Maximization (EM) algorithm.

Further, according to some embodiments, the throughput performance within the wireless communication system is further improved by increased signal processing technique.

Thereby an improved performance within the wireless communication network is provided.

Other objects, advantages and novel features of the embodiments of the invention will become apparent from the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS Embodiments of the invention are described in more detail with reference to attached drawings illustrating examples of embodiments in which:

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.

DETAILED DESCRIPTION OF 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 .

Still other objects and features may become apparent from the following detailed description considered in conjunction with the accompanying drawings. It is to be understood, however, that the drawings are designed solely for purposes of illustration and not as a definition of the limits of the herein disclosed embodiments, for which reference is to be made to the appended claims. Further, the drawings are not necessarily drawn to scale and, unless otherwise indicated, they are merely intended to conceptually illustrate the structures and procedures described herein. Figure 1 is a schematic illustration over a heterogeneous wireless network 100. 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) , 3GPP2 CDMA technologies, e.g., CDMA2000 lx RTT and High Rate Packet Data (HRPD) , just to mention some few options. The expressions "wireless network" and "wireless system" may within the technological context of this disclosure sometimes be utilised interchangeably .

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 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.

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. Thus, although the embodiments of the invention are described based on, and using the lingo of, 3GPP LTE systems, it is by no means limited to 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. However, 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. In addition, 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.

It is to be noted that the illustrated network setting of one receiver 120, one serving pico node 110 and, three neighbour macro nodes 130-a, 130-b, 130-d and one neighbour pico node 130-c in Figure 1 is to be regarded as a non-limiting example of an embodiment only. 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.

Thus whenever "one" or "a/an" receiver 120 and/or radio network node 110, 130 is referred to in the present context, a plurality of receivers 120 and/or radio network nodes 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.

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.

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.

In a LTE/LTE-Advance HetNet scenario, cancellation of interference from cell specific reference signals from neighbour nodes 130-a, 130-b, 130-c, 130-d is quite important at the receiver side, even though the Almost Blank Subframes (ABSs) are transmitted by the macro-cell, i.e., the neighbour macro node 130-a, in order to enhance the desired signal processing. 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. 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.

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. Furthermore, as corroborated via simulations, 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. In the first embodiment, a low complexity channel estimator unit utilises only serving cell 110 and neighbour cell 130 CRSs. In the second embodiment, 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.

In particular are herein disclosed two approaches of interference cancellation of Cell-specific Reference Signals (CRS) , for colliding/overlapping CRSs with a particular focus on an iterative channel estimation unit. However, 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 .

Figure 2 discloses a generic receiver architecture depicting iterative channel estimator utilising messages from the Multiple-Input and Multiple-Output (MIMO) detector/ demodulator .

Herein, two embodiments for serving cell 110 and neighbour cell 130 iterative channel estimation apparatus are disclosed for colliding CRSs scenario based on Space-Alternating Generalised Expectation and maximisation (SAGE) algorithm with a MAP criterion, whereby the proposed iterative channel estimation unit within receiver architecture is depicted in Figure 2. The SAGE method comprises updating parameters sequentially by alternating between several small hidden-data spaces defined by the algorithm designer, according to some embodiments, as will be further explained herein. The SAGE algorithm easily accommodate smoothness penalties and converge faster than the algorithms used in prior art.

According to some embodiments, 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.

Thus, according to some embodiments, 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.

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.

In LTE, the smallest time-frequency entity that can be used for transmission is referred to as a Resource Element (RE) , which may convey a complex-valued modulation symbol on a subcarrier. In this context, the resource element may be referred to as time-frequency resources. 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) .

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. 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.

Thus 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.

The colliding CRS scenario with M radio network nodes 110, 130 and, for simplicity, 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:

Since CRSs are orthogonal across transmit ports for each radio network node 110, 130, then every channel path may be seen as a Single Input Single Output (SISO) link at the receiver 120, and further other radio network node transmit ports may be seen as a virtual transmit antenna ports at the receiver 120. Hence Equation 1 may equivalently be re-written as:

MN

r_v =∑X_aH_V;a + N.

u^=l Eqn. 2 Wherein: 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. Further, N corresponds to a zero-mean circularly-symmetric complex white Gaussian noise vector with a covariance matrix R_N . Also, 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.

Initializa tion ( 1≤ u < MN_T )

(0) X H (0)

u v.u

At the gth iteration (g = 0,1,2,... G) :

{ For i= 1 + mod(g,MN_T),

r (g+l) ^g] V ; 1≤ j<MN but j≠ i.

} ·

It may be noticed that 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. Hence, the complexity of this scheme may be similar as in the previously discussed ad-hoc approach but rendering superior performance. Although, one could argue that 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. However, in a second embodiment, 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

LLRs 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 . In principle, 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. In particular, 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. It is worth to highlight that 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. Notice that the soft- symbols may be obtained by performing appropriate transformation of soft-bits (LLRs) . Furthermore, 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. However, one may perform low-rank approximations to the channel correlation matrix and thereby reduce the complexity significantly, according to some embodiments. However, the presented method embodiment may not be dealing with the low-complexity version of time-variant MAP filtering herein. Furthermore, it is worth to highlight that in order to keep the latency low, 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. Note that 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.

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. As expected, the proposed state- of-the-art based on SAGE algorithm outperforms the ad-hoc approach.

As example, the normalised throughput performance versus SNR of the first embodiment (i.e., utilising only CRSs) may be presented below, for one test scenario.

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 legend "No cancellation" corresponds to single-cell channel estimation performance but the CRS interference of the neighbour cell 130 is ignored.

Thus, according to embodiments herein, the pilots-based iterative CRS interference cancellation in colliding CRS scenario, via a SAGE-MAP algorithm according to some embodiments. Further, a semi-blind iterative CRS interference cancellation approach in a colliding CRS scenario according to some embodiments 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.

To appropriately perform the transmission, the method 700 may comprise a number of actions 701-703.

It is however to be noted that any, some or all of the described actions 701-703, may be performed in a somewhat different chronological order than the enumeration indicates, or even be performed simultaneously. Further, it is to be noted that some actions such as e.g. action 703 is optional and only performed according to some embodiments. The method 700 may comprise the following actions:

Action 701

Colliding reference signals of a first network node 110 and a second network node 130 are detected.

Thereby for example, 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.

Action 702

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.

Further, according to some embodiments, 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.

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.

Further, 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.

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.

Figure 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.

For enhanced clarity, any internal electronics or other components of the receiver 120, not completely indispensable for understanding the herein described embodiments have been omitted from Figure 8.

The receiver 120 comprises a receiving unit 810, configured for receiving reference signals from the network nodes 110, 130.

Further, 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.

According to some embodiments, 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.

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. The herein utilised expression "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.

Furthermore, 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. According to some embodiments, the memory 825 may comprise integrated circuits comprising silicon-based transistors. Further, the memory 825 may be volatile or non^¬ volatile.

Further, 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. Thus 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.

The terminology used in the detailed description of the invention as illustrated in the accompanying drawings is not intended to be limiting of the described method 700, radio network nodes 110, 130 and receiver 120, which instead are limited by the enclosed claims. As used herein, the term "and/or" comprises any and all combinations of one or more of the associated listed items. In addition, the singular forms "a", "an" and "the" are to be interpreted as "at least one", thus also comprising a plurality, unless expressly stated otherwise. It will be further understood that the terms "includes", "comprises", "including" and/or "comprising", specifies the presence of stated features, actions, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, actions, integers, steps, operations, elements, components, and/or groups thereof .

Claims

1. A method (700) in a receiver (120), for interference cancellation of colliding reference signals received from network nodes (110, 130) comprised in a heterogeneous wireless network (100), especially but not limited to, a macro-pico scenario, the method (700) comprising: detecting (701) colliding reference signals of a first network node (110) and a second network node (130); performing (702) channel estimation 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.

2. The method (700) according to claim 1, further comprising : performing (702) 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 .

3. The method (700) according to claim 2, wherein the action of performing (702) channel estimation further comprises: 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; and wherein the output of the channel estimation is further processable by demodulation and decoding of the first network node (110) .

4. The method (700) according to claim 1, further comprising : enhancing (703) the 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), thereby performing a semi-blind channel estimation.

5. The method (700) according to claim 4, wherein the action of enhancing (703) the channel estimation further comprising: 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.

6. The method (700) according to claim 1, wherein the reference signals are cell specific reference signals "CRS", the heterogeneous wireless network (100) is based on 3rd Generation Partnership Project Long Term Evolution "3GPP LTE"; the receiver (120) is a User Equipment, "UE"; the network nodes (110, 130) comprise evolved NodeBs, "eNodeBs".

7. A receiver (120), configured for interference cancellation of colliding reference signals received from network nodes (110, 130) comprised in a heterogeneous wireless network (100), especially but not limited to, a macro-pico scenario, comprising: a receiving unit (810), configured for receiving reference signals from the network nodes (110, 130); a processing circuit (820), configured for detecting colliding reference signals of a first network node (110) and a second network node (130), and also 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.

8. The receiver (120) according to claim 7, wherein the processing circuit (820) is 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.

9. The receiver (120) according to claim 8, wherein the processing circuit (820) is 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.

10. The receiver (120) according to claim 7, wherein the processing circuit (820) is 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) .

11. The receiver (120) according to claim 10, wherein the processing circuit (820) is 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.

12. The receiver (120) according to claim 7, wherein the reference signals are cell specific reference signals "CRS", the heterogeneous wireless network (100) is based on 3rd Generation Partnership Project Long Term Evolution "3GPP LTE"; the receiver (120) is a User Equipment, "UE"; the network nodes (110, 130) comprise evolved NodeBs, "eNodeBs".

13. A computer program product in a receiver (120), according to claim 7, configured for performing the method (700) for interference cancellation of colliding reference signals received from network nodes (110, 130) comprised in a heterogeneous wireless network (100) according to claim 1, when the computer program product is loaded in a processing circuit (820) of the receiver (120) .