TWI667905B - Interference cancellation method of user equipment in cellular communication system - Google Patents

Abstract

The invention provides a method and a device for interference cancellation of user equipment in a cellular communication system. The method includes: receiving signals from one or more base stations, the signals including desired signals and interference signals; determining a maximum likelihood (ML) decision metric to determine the value of the rank indicator (RI) of the interference signal "l", Precoding matrix indicator (PMI) value "p" and modulation (MOD) bit value "q"; apply algorithms to the maximum likelihood decision metric, and include in the maximum likelihood decision metric Apply the maximum logarithmic approximation to the servo data vector and the interference data vector of; use the applied maximum likelihood decision metric to determine the value "l", value "p", and value "q"; and use the determined value "l", value "P" and the value "q" eliminate interference signals from the received signal.

Description

Interference cancellation method for user equipment in cellular communication system

The present invention relates generally to an interference cancellation method for user equipment in a cellular communication system, and more specifically, to a network-assisted interference cancellation and suppression (NAICS) system. Interference cancellation method for blindly detected interference parameters.

To meet the stringent requirements of the International Telecommunication Union Radio (ITU-R) communications division, next-generation cellular networks (such as long term evolution advanced (LTE-A)) have been designed, and Carrier aggregation (CA) technology. The next-generation cellular network uses higher-order space for the eight layers in the downlink (DL) and the four layers in the uplink (UL). Multiplex (higher-order spatial multiplexing) and support wide bandwidth up to 100 megahertz.

It is worth noting that spatial frequency reuse using more cells can provide more capacity benefits than a single cell with increased spatial size or increased spectral bandwidth. So in one Heterogeneous networks using small cells in a macro cell environment are increasingly seen as a bright road for next-generation cellular networks.

The heterogeneous networks described above can provide various benefits, but the heterogeneous networks can present cellular networks with unprecedented challenges. Specifically, as the number of base stations (BS) increases, interference management, which becomes a major concern, may increase significantly. In this context, advanced co-channel interference aware signal detection has attracted researchers' attention during the recent development of advanced long-term evolution systems.

The 3rd Generation Partnership Project (3rd Generation Partnership Project, 3GPP) is studying the characteristics of network-assisted interference cancellation and suppression (NAICS). It is assumed that interference parameters including a rank indicator (RI), a precoding matrix indicator (PMI), and a modulation (MOD) level have been transmitted to users through network signaling. Under known conditions of user equipment (UE), the user equipment can perform interference cancellation.

The inclusion of a work item called network-assisted interference cancellation and suppression in Long Term Evolution version 12 is currently being considered. Studies have clearly shown that it is assumed that interference parameters have been broadcasted {eg, upper-layer signaling such as radio resource control (RRC)} or dedicated signaling {eg, newly defined downlink control information (downlink control information information, DCI)} Under conditions known to user equipment, considerable performance benefits can be obtained.

However, due to the back-haul capacity between base stations and the control channel capacity from the base station to the user equipment is usually limited , So the assumptions are not always applicable to real systems. In fact, a similar inter-cell interference cancellation technique called further enhanced inter-cell interference coordination (FeICIC) has been well developed, which is mainly focused on pilot signals, that is, cell-specific reference signals ( cell-specific reference signal (CRS). Because cell-specific reference signal interference cancellation (IC) only requires semi-static interference parameters, such as physical cell identity (CID), cell-specific reference signal antenna port (AP), and multicast broadcast order MBSFN (multicast broadcast single frequency network) sub-frame configuration, so it is worth noting that the signaling overhead for achieving further enhanced inter-cell interference coordination can be managed.

However, unlike further enhanced inter-cell interference coordination, network-assisted interference cancellation and suppression addresses interference in data channels (known as physical downlink shared channels (PDSCH)) and requires knowledge Dynamic interference parameters including rank indicators, precoding matrix indicators, and modulation. The success of messaging-based network-assisted interference cancellation and suppression depends on the use of rank indicators, precoding matrix indicators, and modulation group interference base stations known through messaging, and this can potentially limit Scheduling flexibility in nearby neighborhoods.

In order to overcome defects such as scheduling restrictions and network messaging overhead, the user equipment can perform blind estimation of interference parameters from the received signal. Apply maximum likelihood (ML) estimation to the joint blind detection (BD) of rank indicator, precoding matrix indicator, and modulation, which is included in An exhaustive search is performed among the available combinations of rank indicators, precoding matrix indicators, and modulations specified in the long-term evolution system. In a LTE-orthogonal frequency division multiple access (LTE-OFDMA) system, the assigned rank indicator, precoding matrix indicator, and modulation can be scheduled simultaneously for users The device element changes from one transmission time interval (TTI) to another transmission time interval in the time domain, and changes from one resource block (RB) to another resource block in the frequency domain . This indicates that joint blind detection should be performed for each resource block of all transmission time intervals in the long-term evolution downlink system.

However, since the interference parameter can be dynamically changed from one resource block to another resource block in the frequency domain in each transmission time interval according to the channel status, this assumption may limit the performance of the schedule and may cause the network to Road messaging load increased excessively.

Aspects of the present invention provide network-assisted interference cancellation based on blind detection and interference cancellation that suppresses interference parameters.

Another aspect of the present invention provides a blind detection algorithm with low complexity to estimate an interference rank indicator, a precoding matrix indicator, and modulation.

Yet another aspect of the present invention provides a method for compensating performance degradation caused by low-complexity blind detection.

According to an aspect of the present invention, an interference cancellation method for a user equipment (UE) in a cellular communication system is provided. The method includes receiving from one or more base stations Signal, the signal including the desired signal and the interference signal; determining a maximum likelihood (ML) decision metric to determine the value of the rank indicator (RI) of the interference signal "l", a precoding matrix indicator (PMI ), The value of "p", and the value of the modulation (MOD) level "q"; an algorithm is applied to the maximum likelihood decision metric, and the servo data included in the maximum likelihood decision metric Apply the maximum logarithmic approximation to the vector and the interference data vector; use the applied maximum likelihood decision metric to determine the value "l", the value "p", and the value "q"; and use the determined all The value "l", the value "p", and the value "q" cancel the interference signal from the received signal.

According to another aspect of the present invention, an apparatus for interference cancellation in a cellular communication system is provided. The device includes a controller for receiving signals from one or more base stations, the signals including a desired signal and an interference signal; determining a maximum likelihood (ML) decision metric to determine the interference The value of the rank indicator (RI) of the signal is "l", the value of the precoding matrix indicator (PMI) is "p", and the value of the modulation (MOD) level is "q"; the maximum likelihood is determined An algorithm is applied to the metric, and a maximum logarithmic approximation is applied to the servo data vector and the interference data vector included in the maximum likelihood decision metric; the value "l" is determined using the applied maximum likelihood decision metric , Said value "p" and said value "q"; and using said determined value "l", said value "p" and said value "q" to eliminate said from said received signal Interfering signals.

According to the present invention, the determination of the maximum likelihood of the interference rank indicator, the precoding matrix indicator, and the modulation can greatly reduce the complexity, and it is possible to use a method having a minimum Euclidean metric. One rank indicator, pre-programmed The code matrix indicator and the modulated transmission signal vector are used to implement the user equipment.

In addition, the present invention can approximate the best rank indicator, the precoding matrix indicator, and the modulation detection method by applying a bias item to compensate for performance degradation to the maximum likelihood decision metric. Effect.

According to the present invention, an improved network-assisted interference cancellation and suppression receiver based on blind detection can be used to implement future user equipment components with high efficiency and low complexity.

101, 102‧‧‧ base station

103‧‧‧User Equipment

300, 305, 310, 315, 320, 325‧‧‧ steps

400‧‧‧user equipment components

410‧‧‧ Transceiver

420‧‧‧controller

The above and other aspects, features, and advantages of the present invention will become more apparent after reading the following detailed description in conjunction with the accompanying drawings. In the drawings: FIG. 1 illustrates a multi-input multi-composition consisting of two base stations and one user equipment element. An output orthogonal frequency division multiplexing (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing, MIMO-OFDM) system.

Figure 2 illustrates the astrology (or modulation number distribution) of 4th-order quadrature amplitude modulation (4QAM), 16th-order quadrature amplitude modulation (16QAM), and 64th-order quadrature amplitude modulation (64QAM) used in the LTE downlink Figure).

FIG. 3 is a flowchart of an interference cancellation method performed by a user equipment using blind detection according to the present invention.

Figure 4 is a block diagram of user equipment elements according to the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the present invention In the following description, when it is determined that a detailed description of a conventional configuration or function incorporated herein may make the subject matter of the present invention unclear, the detailed description is omitted. The terms described below are defined in consideration of functions in the embodiments of the present invention, and the meanings of the terms may be different according to the intentions, conventions, etc. of the user or operator. Therefore, the definition of the terms should be determined based on the overall background of the embodiments of the present invention.

In the detailed description of the present invention, clarifiable examples of certain terms used in the present invention are provided. It should be noted, however, that the terms are not limited to the examples of interpretable meaning provided below.

The base station is the main body that communicates with the user equipment (UE), and may be called a BS, a Node B (NB), an eNode B (eNB), an access point (AP), and the like.

The user equipment is an object to communicate with the BS, and may be referred to as a UE, a mobile station (MS), a mobile equipment (ME), an element, a terminal, and the like.

Provides an explanation of the system model, basic long-term evolution receiver, and improved network-assisted interference cancellation and suppression advanced long-term evolution (NAICS LTE-A) receiver. Then, the best maximum likelihood algorithm and the second-best approximation method for estimating the interference rank indicator, the precoding matrix indicator, and the modulation will be explained after the description.

First, the system model and the improved long-term evolution receiver are explained.

In the present invention, in order to compare the performance of a basic long-term evolution receiver, a legacy linear multiple-input multiple-output (MIMO) receiver is generally described.

Figure 1 illustrates a multiple input multiple output orthogonal frequency division multiplexing system including two base stations and a user equipment element.

Referring to FIG. 1, a downlink multiple-input multiple-output orthogonal frequency division multiplexing system is shown in which two base stations 101 and 102 each having Nt transmission antennas transmit messages to a desired user equipment 103 having Nr reception antennas. The transmission channel in the present invention may be, for example, a physical downlink shared channel (PDSCH) or a physical multicast channel (physical multicast channel (PMCH)).

In the case of a normal cyclic prefix (CP) in the study of network-assisted interference cancellation and suppression, it is assumed that a single group of rank indicator, precoding matrix indicator, and modulation is orthogonal to fourteen A period of a single transmission time interval corresponding to the frequency division multiplexing symbol interval is allocated to a pair of resource blocks composed of twelve consecutive subcarriers. Therefore, blind detection and data detection can be performed on a pair of resource blocks composed of 168 resource elements (RE). In this case, it is assumed that the user equipment knows the network-assisted interference cancellation and suppression interference parameters, namely RI, PMI, and MOD.

In this case, the l _i -dimensional complex signal vector transmitted from BSi in the k- _th resource element can be expressed as . In this case, Represents the l- _th spatial layer, and l _i represents the transport layer, that is, the number of rank indicators. [] ^T represents the vector prefix. symbol Wherein the base is selected is expressed as | C ^{i, l} | constellation group C ^{i, l.} The average transmitted power is expressed as , Where E [] represents the expected operand, and || represents the absolute value of a complex number. In general, it is assumed that "BSi = S" is a servo base station and "BSi = I" is an interference base station.

In this case, "r _k " is defined as the signal vector received by the desired user equipment 103 in "REk". Therefore, "r _k " can be expressed as the following equation (1).

among them Refers to the effective channel matrix including the actual channel matrix and the precoding matrix, and the element " _nk " refers to the additive noise vector, which is used as Independent Gaussian distribution of independently and identically distributed (iid). In addition, "K" indicates the number of coding resource elements used in each pair of base stations.

The following explains an interference rejection combiner (IRC) as a basic long-term evolution receiver.

For a basic long-term evolution receiver, the present invention considers a linear receiver called an interference rejection combiner (IRC). The interference rejection combiner can suppress inter-cell interference and inter-stream interference in spatial multiplexing transmission. The weight matrix of the interference rejection combiner can be expressed as the following equation (2).

Where () ⁺ refers to the Hermitian operator, and the covariance matrix “R _k ” including desired / unwanted signals and noise vectors can be expressed as the following equation (3).

The cell-specific reference signal sequence of the servo cell is known to the user equipment, so the interference and noise vector in the servo cell-specific reference signal-resource element (CRS-RE) in the pair of resource blocks can be determined Factor averaging to estimate the interference plus noise (I + N) covariance matrix R ^{I + N.} Therefore, R ^{I + N} can be expressed as the following equation (4).

Where K _crs is the number of dedicated reference signal-resource elements of the servo cell in each pair of resource blocks, and A transmission vector corresponding to a cell-specific reference signal sequence of a servo cell.

The following describes an improved network-assisted interference cancellation and suppression receiver based on an enhanced interference rejection combiner and maximum likelihood.

Unlike the basic long-term evolution receiver, the improved network-assisted interference cancellation and suppression receiver can use the information about the interference (ie, the interference channel matrix and the interference parameters) to improve the performance of multiple input multiple output. Therefore, the present invention summarizes the model of equation (1) into the term of well-known interference information, and describes two improved network-assisted interference cancellation and suppression based on enhanced interference rejection combiner and maximum likelihood demodulation. receiver.

In this case, the channel model from "BSi" to the desired user equipment in "REk" is defined as the N _r × N _t channel matrix . The (m, n) term refers to the path gain from the antenna "n" of "BSi" to the antenna "m" of the user equipment. These terms can be modeled as independent complex Gaussian random variables with zero mean and unit distribution, that is, Rayleigh fading. It is an N _r × l _i precoding matrix (or vector) used by "BSi" in "REk".

User equipment can make the precoding matrix Channel matrix Multiply to calculate effective channel . Therefore, equation (1) can be used Rewritten as the following equation (5).

The enhanced interference rejection combiner defined in network-assisted interference cancellation and suppression studies can be obtained using knowledge about interference rank indicators and precoding matrix indicators , And the corresponding weight matrix can be expressed as the following equation (6).

Compared with the network-assisted interference cancellation and interference rejection combiner, the network-assisted interference cancellation and suppression maximum likelihood can use modulation knowledge and interference rank indicators and precoding matrix indicators to achieve network-assisted interference cancellation and Suppressed properties have advantages. According to the definition of network-assisted interference cancellation and suppression, only the servo data is needed Soft bit information. In this case, the constellation symbol The mth ( m = 1.2, ..., log ₂ | C ^{S , l} |) bit is expressed as . Bit The log likelihood ratio (LLR) can be expressed as the following equation (7).

among them Where random variables Use the probability of the value "b" (b = 0 or 1).

based on and Conditional probability density function (pdf) of "r _k " p ( r _k | , ) Can be expressed as equation (8), and The log-likelihood ratio can be expressed as the following equation (9).

Where χ ⁱ refers to the available symbol vector obtained from the l _i- fold (l _i -fold) Cartesian product of C ^{i, l} Group of, and Refers to a partial group of x ^s , where = b (b = 0 or 1). In addition, the ∥ ∥ operator represents the Euclidean norm. Is the constant in equation (8) above, so it will not be explained below .

The network-assisted interference cancellation and suppression maximum likelihood receiver has the highest complexity among the above long-term evolution receivers. The trade-off between efficiency and complexity can be achieved by applying a maximum log approximation to equation (9) above. The approximation may allow a log-likelihood ratio to be calculated based on a minimum Euclidean distance according to the following equation (10).

Next, the detection of interference rank indicators, precoding matrix indicators, and modulation will be explained below.

The above description shows that the basic principles of network-assisted interference cancellation and suppression are based on It depends on the use of interference information in the user equipment, that is, a rank indicator, a precoding matrix indicator, and modulation. The network-assisted interference cancellation and interference suppression parameters can be obtained while allowing scheduling restrictions and / or network messaging overhead in the interference base station. To overcome the above disadvantages, the present invention provides blind detection of parameters in user equipment.

In the long-term evolution system, it should be noted that the rank indicator, precoding matrix indicator, and modulation for the servo data can be read by the physical downlink control channel (PDCCH) from the servo base station. The downlink control information (DCI) is implicitly discovered. However, there is no information on interference rank indicators, precoding matrix indicators, and modulation that can be used in user equipment.

When the unknown interference is modulated by C ^{I, l} gives the modulation level `` q '' ( q {4,16,64}), the prior probability of each modulation level "q" and each constellation point ( j The ex ante probabilities of {1, ..., q }) can be expressed as P _q and P _q ^{j respectively} .

Table 1 below shows that rank indicators, precoding matrix indicators, and modulation candidate groups for basic transmission mode (TM) are assigned to multiples with two antennas (ie, Nt = 2). Input Multiple Output Long Term Evolution System. In this case, the rank indicator, the precoding matrix indicator, and the modulation are labeled as "l", "p", and "q", respectively.

As shown in Table 1 above, the two precoding matrices assigned to TM 3 will not make the performance of blind detection and MIMO demodulation different, so TM 3 can be regarded as a subgroup of TM 4. Similarly, TM 4 corresponding to l = 1 can be regarded as TM 6. Therefore, in the subsequent MIMO demodulation operation, the interference transmission mode can be detected as one of TM 2 where l = 2, TM 4 where l = 2, or TM 6 where l = 1. By.

The modulation used in the long-term evolution downlink may include 4th-order quadrature amplitude modulation (4QAM), 16th-order quadrature amplitude modulation (16QAM), 64th-order quadrature amplitude modulation (64QAM), and 256th-order quadrature amplitude modulation (256QAM).

FIG. 2 illustrates astral diagrams (or modulation maps) of 4th-order orthogonal amplitude modulation, 16th-order orthogonal amplitude modulation, and 64th-order orthogonal amplitude modulation used in the long-term evolution downlink.

FIG. 2 shows three astrological diagrams for 4th-order quadrature amplitude modulation, 16th-order quadrature amplitude modulation, and 64th-order quadrature amplitude modulation in long-term evolution downlink transmission, which are expressed as Q ₄ , Q ₁₆ And Q ₆₄ (corresponding to ●, ■, and ). The constellation points of each long-term evolution astrological chart are normalized to have unit variance.

The best joint detection method for rank indicator, precoding matrix indicator, and modulation will be described below.

The network-assisted interference cancellation and suppression maximum likelihood receiver can perform symbol-level interference cancellation without preliminary information about the interference rank indicator, precoding matrix indicator, and modulation. Therefore, it can be assumed that the rank indicators, the precoding matrix indicators, and the modulation groups in Table 1 have equal possibility. In addition, the same assumptions can be applied to constellation points. That is, it is assumed that p _q = 1/3 and p _q ^j = 1 / q. In this case, it is well known that blind detection based on maximum likelihood estimation can minimize the probability of errors.

Can be combined with specific The corresponding precoding matrix with "l" and "p" is expressed as The conditional probability density function in the above equation (8) is rewritten as the following equation (11).

Thus, based on the received signal vector r _k K is "l", "p" and "q" maximum likelihood metric can be expressed as the following equation (12).

among them Corresponding to χ ^I with rank indicator "l" and modulation "q", the rank indicator "l" and modulation "q" are obtained by the 1-fold Cartesian product of Q _q obtain.

At this time, the maximum likelihood receiver (or maximum likelihood detector) may perform a search among the available groups of "l", "p", and "q", and may determine that the following equation (13 ) Define l ^opt , p ^opt , and q ^opt .

Where S ^l and S ^p refer to the groups of available values for "l" and "p", respectively, and where S ^l and S ^p are functions of {Nt, TM} and {Nt, TM, l}, respectively, as above Table 1 shows.

As shown in equations (12) and (13) above, where the best maximum likelihood detector will be used to calculate the interference rank indicator, precoding matrix indicator, and modulation along with the servo data constellation points available The combined decision metric, the best joint detection of the rank indicator, the precoding matrix indicator, and the modulation will cause the calculation to be too complicated to be processed in the user equipment.

Therefore, the present invention provides a sub-optimal approach with reduced computational complexity to deal with the best metric of equation (12) above.

To avoid exponents and multiplications across all search spaces, the present invention provides an algorithm for applying maximum likelihood decision metrics and then applying servo data vectors The method of maximum logarithm approximation solves the above-mentioned problem of maximum likelihood detection.

That is, to avoid the exponential sum multiplication in equation (12) above, an algorithm is used to calculate the best metric of equation (12), and then the servo data vector is Apply the maximum log approximation. Therefore, the decision metric M _{l , p , q} can be approximated by the following equation (14).

among them You can find the transfer vector that minimizes the Euclidean metric in equation (15) below and Come to get.

After removing the constant term, the above equation (14) can be rewritten as the following equation (16).

The residual term R ( l , p , q , σ _n ) can be expressed as the following equation (17).

When using and targeting servo data vectors The maximum logarithm of the interference data vector is approximately the same When the maximum logarithmic approximation is applied, the simplest maximum likelihood decision metric can be obtained according to the following equation (18).

The present invention provides a method for calculating an approximate value of a maximum likelihood metric calculated for a minimum distance problem and compensating for performance degradation related to a sub-optimal approximation.

More specifically, compared to servo data vectors that affect the detection of rank indicators, precoding matrix indicators, and modulation of all candidate groups The maximum logarithmic approximation of. Can be obtained by applying the maximum logarithmic approximation to Equation (18) above, which can result in relatively large differences in Euclidean metrics between different candidate groups. The difference indicates a possible performance degradation in the blind detection of the rank indicator, the precoding matrix indicator, and the modulation. Accordingly, the performance degradation may provide motivation for the blind detection taking into account the residual term R (l, p, q, σ n) of the.

Therefore, the present invention provides a method of using a residual term to compensate for a relative difference in the Euclidean metric caused by applying a maximum logarithmic approximation. That is, the present invention provides a method in which a decision metric includes a residual term by estimating a relative difference between a rank group indicator, a precoding matrix indicator, and a modulated single reference group and other remaining groups. For example, based on l = 2, p = 1, and q = 4 in TM 2, the relatively poor partial term (for example, the difference term) can be defined as the following equation (19).

△ ( l , p , q , σ _n ) = E [ R ( l , p , q , σ _n ) -R ( l = 2, p = 1, q = 4, σ _n )] ... (19)

The proposed bias term can compensate for the rank indicator, the precoding matrix indicator, and Modulate the relative difference between different groups to ensure uniform maximum likelihood detection performance. Therefore, only relative bias terms can be stored in a look-up table (LUT), and the relative bias terms stored in the look-up table can simplify blind detection. The lookup table is a common lookup table applied to all servo transmission modes of a group to which a rank indicator, a precoding matrix indicator, and a modulation are applicable.

The following table 2 shows an example of a lookup table. Assume that the interfering user equipment components use 4th-order quadrature amplitude modulation and 16th-order quadrature amplitude modulation as different groups of RI (l), PMI (p), and MOD (q). A lookup table of the relative compensation deviations.

In Table 2 above, 2 (2), 3 (2), 4 (2), 4 (1), and 6 (1) in the first column correspond to the form of "TM (l)" (that is, interference "TM" and "l" of the data). For example, in the first column, 2 (2) corresponds to "TM 2" and "l = 2", and 3 (2) corresponds to "TM 3" and "l = 2". The 4, 16, and {4,4} in the second column refer to the modulated value (q). For example, in the second column, 4 and 16 correspond to 4th-order quadrature amplitude modulation and 16th-order quadrature amplitude modulation, respectively, and {4,4} corresponds to {4QAM, 4QAM}. INR stands for interference-to-noise ratio, and for example INR can be expressed in "dB".

Therefore, the maximum likelihood decision metric can be expressed as the following equation (20) that allows the existence of a blind detector based on the minimum Euclidean distance.

For example, when INR 4dB when, under TM 2 and q = 16, the equation above can be used as compensation deviation 2.02 △ (l, p, q, σ n) of (20) in value.

As described above, to be by "l", "p" and "q" candidate group COMPENSATION deviation △ (l, p, q, σ n) is determined so that the above equations (20) to maximize the metric RI (l), PMI (p), and MOD (q), so that performance can be expected to approximate the best maximum likelihood receiver even at low complexity.

That is, the improved network-assisted interference cancellation and suppression receiver based on the blindly detected interference parameters according to the present invention can greatly enhance the performance of interference with advanced long-term evolution user equipment in a limited cellular environment.

3 is a flowchart illustrating a method for eliminating interference signals by using blind detection by a user equipment according to the present invention.

In step 300, the user equipment may use a transceiver {for example, a radio frequency (RF) integrated circuit} to receive a signal from a base station via a downlink channel, the signal including a desired signal (for example, servo data) and Interfering signals (for example, interference data). The downlink channel may be, for example, a physical downlink shared channel or a physical multicast channel. The transceiver of the user equipment can operate according to a MIMO transmission method, and can transmit and receive signals using multiple antennas.

In step 305, the user equipment may use a controller (e.g., a modem) Integrated circuit) to determine the maximum likelihood decision metric to determine the RI (l), PMI (p), and MOD (q) of the interference signal. For example, the maximum likelihood decision metric can be determined according to the above equation (12).

To reduce the computational complexity of blind detection, in step 310, the user equipment may apply an algorithm to the maximum likelihood decision metric, and may apply the servo data vector and the interference data vector included in the maximum likelihood decision metric. Maximum logarithmic approximation.

Alternatively, the user equipment may comprise terms apply maximum likelihood residue R (l, p, q, σ n) in a probabilistic decision metric to enhance the performance of blind detection. In step 315, the residual term can be included in the maximum likelihood decision metric as a bias term. The maximum likelihood decision metric including the bias term can be expressed, for example, as the above equation (20). The partial term aims to compensate the difference between the reference group of "l", "p", and "q" and a candidate group of "l", "p", and "q". The value to be applied to the bias term can be stored in a lookup table, and the user equipment can obtain the bias value by fetching from the lookup table. For a given INR, the lookup table records the difference between the base group of "l", "p", and "q" and the candidate group of "l", "p", and "q" Partial value. Then, the value of "q" can be named 4th-order quadrature amplitude modulation, 16th-order quadrature amplitude modulation, 64th-order quadrature amplitude modulation, or 256th-order quadrature amplitude modulation.

In step 320, the user equipment may use the metric to detect "l", "p", and "q". For example, the user equipment can blindly detect "l", "p", and "q" that maximize the metric. The value that maximizes the metric may be a value that minimizes the Euclidean metric expressed by the above equation (15).

In step 325, the user equipment can use the detected "l", "p", and "q" to cancel the interference signal from the received signal.

Fig. 4 is a block diagram of a user equipment element 400 according to the present invention.

The user equipment element 400 includes a transceiver 410 that communicates with a base station or other user equipment elements, and a controller 420 that controls the transceiver 410. The transceiver 410 may be implemented by a component (such as a radio frequency integrated circuit), and the controller 420 may be implemented by a component (such as a modem integrated circuit). Alternatively, the transceiver 410 and the controller 420 can also be implemented as a single component (ie, a single integrated circuit).

The controller 420 executes the interference cancellation method of the user equipment according to the present invention. That is, all the operations described above can be understood as being performed by the controller 420. The controller 420 may include a memory for storing a lookup table inside or outside the memory.

The transceiver 410 can transmit and receive signals, and can utilize multiple antennas for spatial multiplexing transmission.

It should be noted that FIGS. 1-4 are not intended to limit the scope of the invention. That is, the operation of the method or the configuration shown in FIGS. 1 to 4 should not be interpreted as an indispensable element of the embodiment of the present invention, but the method or operation can be used without departing from the scope of the present invention. Part of it is to implement the present invention.

The above operation may be implemented by providing a memory element for storing a corresponding code for a specific structural element of the communication system entity, function, base station, load manager, or terminal. That is, the controller of the entity, function, load manager or terminal performs the above operations by reading and executing code stored in the memory element by a processor or a central processing unit (CPU).

This can be accomplished by using hardware circuits (e.g., logic-based complementary metal oxide semiconductor (CMOS)), firmware, software, and / or hardware, firmware embedded in mechanically readable media And / or software to operate entities, functions, base stations, load managers, various structural elements, modules, etc. of terminals. For example, various electronic configurations and methods can be performed by using circuits (such as transistors, logic gates, and application specific integrated circuits (ASICs)).

Although the invention has been shown and described with reference to certain embodiments of the invention, those skilled in the art will understand that various changes in form and details can be made to the invention without departing from the scope and spirit of the invention. Therefore, the present invention is not limited to the embodiments of the present invention, but is defined by the scope of the accompanying patent application and its equivalent scope.

Claims (20)

A method for interference cancellation of user equipment in a cellular communication system, the method comprising: receiving signals from one or more base stations, the signals including required signals and interference signals; determining a maximum likelihood decision metric to determine the The value of the rank indicator of the interfering signal is "l", the value of the precoding matrix indicator is "p", and the value of the modulation level is "q"; an algorithm is applied to the maximum likelihood decision metric, and The maximum logarithmic approximation is applied to the servo data vector and the interference data vector included in the maximum likelihood decision metric; using the applied maximum likelihood decision metric to determine the value "l", the value "p", and The value "q"; and using the determined value "l", the value "p", and the value "q" to eliminate the interference signal from the received signal. The interference cancellation method for user equipment in a cellular communication system according to item 1 of the scope of patent application, wherein the applied maximum likelihood decision metric further includes a method for compensating performance degradation caused by applying the maximum logarithmic approximation. Residual items. The method according to item 2 of the scope of patent application, wherein the residual term is expressed as a partial term corresponding to the residual term of the reference group of "l", "p" and "q" and "l" ", The difference between the residuals of the candidate groups of" p "and" q ". The interference cancellation method for user equipment in a cellular communication system according to item 3 of the scope of patent application, wherein the value of the partial term is stored in a lookup table. The interference cancellation method for user equipment in a cellular communication system according to item 4 of the scope of patent application, wherein the lookup table includes the value of the partial term relative to the interference-to-noise ratio. The interference cancellation method for user equipment in a cellular communication system according to item 4 of the scope of patent application, wherein the lookup table includes 4th-order orthogonal amplitude modulation, 16th-order orthogonal amplitude modulation, 64th-order orthogonal amplitude modulation, and 256-order orthogonality modulation At least one of the amplitude modulations is taken as the value of "q". The interference cancellation method for user equipment in a cellular communication system according to item 1 of the scope of patent application, wherein the transmission mode (TM) of the interference signal is TM of l = 2, TM of l = 2, or l = One of TM 6 of 1. The interference cancellation method for user equipment in a cellular communication system according to item 3 of the scope of the patent application, wherein the maximum likelihood decision metric M is expressed as follows: Where "r _k " is the signal vector received in resource element k, Is the distribution of the noise vector, Is the effective channel matrix of servo data, "K" is the number of resource elements, Is the servo data vector, Is the interference data vector, Is the interference channel matrix, Is the interference precoding matrix, Is "l" and "q" in the group of available interference symbol vector, and △ (l, p, q, σ n) is a bias term. An apparatus for performing interference cancellation in a cellular communication system, the apparatus includes a controller, the controller is configured to: receive signals from one or more base stations, the signals including a desired signal and an interference signal; determine a maximum Likelihood decision metric to determine the value of the rank indicator "l" of the interference signal, the value of the precoding matrix indicator "p", and the value of the modulation level "q"; for the maximum likelihood An algorithm is applied to the performance decision metric, and the maximum logarithmic approximation is applied to the servo data vector and the interference data vector included in the maximum likelihood decision metric; the value is used to determine the value using the applied maximum likelihood decision metric " l ", said value" p "and said value" q "; and using said determined value" l ", said value" p "and said value" q "to be eliminated from said received signal The interference signal. The apparatus for interference cancellation in a cellular communication system according to item 9 of the scope of patent application, wherein the applied maximum likelihood decision metric further includes a function for compensating the performance caused by applying the maximum logarithmic approximation. Degraded residuals. The apparatus for interference cancellation in a cellular communication system as described in claim 10 of the scope of the patent application, wherein the residual term is expressed as a partial term corresponding to "l", "p", and "q" The difference between the residual term of the reference group of "" and the residual term of the candidate group of "l", "p", and "q". The device for eliminating interference in a cellular communication system according to item 11 of the scope of the patent application, further comprising a memory, wherein the value of the partial term is stored in the memory in the form of a lookup table. The apparatus for interference cancellation in a cellular communication system as described in claim 12 of the scope of patent application, wherein the lookup table includes the value of the bias term relative to the interference-to-noise ratio. The apparatus for interference cancellation in a cellular communication system according to item 12 of the scope of patent application, wherein the lookup table includes 4th-order orthogonal amplitude modulation, 16th-order orthogonal amplitude modulation, 64th-order orthogonal amplitude modulation, and 256-order At least one of the quadrature amplitude modulations is taken as the value of "q". The apparatus for performing interference cancellation in a cellular communication system according to item 9 of the scope of the patent application, wherein the transmission mode of the interference signal is TM of l = 2, TM of l = 2, or l = 1 One of TM 6. The apparatus for interference cancellation in a cellular communication system as described in item 11 of the scope of the patent application, wherein the maximum likelihood decision metric M is expressed as follows: Where "r _k " is the signal vector received in the resource element (RE) k, Is the distribution of the noise vector, Is the effective channel matrix of servo data, "K" is the number of resource elements, Is the servo data vector, Is the interference data vector, Is the interference channel matrix, Is the interference precoding matrix, Is "l" and "q" in the group of available interference symbol vector, and △ (l, p, q, σ n) is a bias term. The device for interference cancellation in a cellular communication system as described in item 9 of the scope of patent application, wherein said determined values of "l", "p" and "q" are such that said maximum likelihood The value at which the decision metric is maximized. Apparatus for interference cancellation in a cellular communication system as described in claim 16 of the scope of patent application, wherein versus Are versus , Which minimizes the Euclidean distance expressed as: The device for interference cancellation in a cellular communication system according to item 9 of the scope of patent application, further includes: multiple antennas for transmitting and receiving signals in a multiple-input multiple-output link. A chipset for interference cancellation in a cellular communication system is used to: receive signals from one or more base stations, the signals including required signals and interference signals; determine a maximum likelihood decision metric to determine all The value of the rank indicator "l" of the interference signal, the value "p" of the precoding matrix indicator, and the value "q" of the modulation level; an algorithm is applied to the maximum likelihood decision metric, The maximum logarithmic approximation is applied to the servo data vector and the interference data vector included in the maximum likelihood decision metric; the value "l", the value "p" are determined using the applied maximum likelihood decision metric And the value "q"; and using the determined value "l", the value "p", and the value "q" to eliminate the interference signal from the received signal.