KR102310972B1 - Apparatus and method for beamforming with consideration of interference channel in wireless communication system - Google Patents

Abstract

The present invention relates to beamforming in a wireless communication system, wherein the operation of the base station sets a threshold value for the amount of change in long-term channel information determined from instantaneous channel parameters collected at multiple points in time. If it exceeds, updating a leak coefficient indicating a rate at which a transmission signal to a terminal acts as interference to at least one other terminal, and determining a beamforming vector based on the leak coefficient; and transmitting a beamformed signal using a beamforming vector. In addition, the present invention includes embodiments other than the above-described embodiment.

Description

Beamforming apparatus and method considering interference channel in wireless communication system

The present invention relates to beamforming in a wireless communication system.

The multi-antenna technique is attracting attention as a core technology of next-generation mobile communication that increases system throughput without increasing frequency resources. Multi-node collaboration technology in which network components such as base stations, terminals, relays, and femto-base stations collaborate with each other in order to seamlessly provide large-capacity data services to a large number of stationary and moving users. This has been actively studied recently.

In order to increase the overall transmission rate of the system in a multi-cell multi-antenna system, it is required to reduce the influence of the interference on the system by adjusting the interference from other cells. To this end, various systems have been developed, and as one of them, a CB (Coordinated Beamforming) system has been proposed. The CB system is discussed as one of the multi-cell cooperative communication techniques. The multi-cell cooperative communication is also called 'Coordinated Multiple Point transmission/reception (CoMP)'. The multi-cell cooperative communication may be divided into the CB or the Joint Processing (JP) according to the degree of cooperation of each base station. The JP is a technique for cooperative transmission by sharing data between base stations and sharing data and channel information together, and the CB does not require data sharing between cells and means a cooperative transmission technique through sharing channel information. do.

Through a number of studies, Pareto optimal is achieved by appropriately adjusting the leakage component to the user of another cell of Virtual-Signal to Interference-plus-Noise Ratio (V-SINR) in the CB system. This has been revealed A beamforming technique based on weighted sum rate maximization based on poly block approximation and rate profile technology that uses global channel information and requires high complexity is proposed. has been In addition, a method of iteratively optimizing the leakage coefficient of the VSINR has been proposed. Here, since the calculation of the leakage coefficient has to be performed for every channel realization, the calculation complexity is rather high.

An embodiment of the present invention provides an apparatus and method for performing beamforming in a wireless communication system.

Another embodiment of the present invention provides an apparatus and method for mitigating inter-cell interference in a wireless communication system.

Another embodiment of the present invention provides an apparatus and method for reducing the computational complexity of determining a beamforming vector in a wireless communication system.

Another embodiment of the present invention provides an apparatus and method for determining a leak coefficient used for determining a beamforming vector in a wireless communication system.

Another embodiment of the present invention provides an apparatus and method for determining a leak factor based on long-term channel information in a wireless communication system.

In the method of operating a base station in a wireless communication system according to an embodiment of the present invention, a change amount of long-term channel information determined from instantaneous channel parameters collected at a plurality of points in time exceeds a threshold. then, updating a leak coefficient indicating a rate at which a transmission signal to a terminal acts as interference to at least one other terminal, determining a beamforming vector based on the leak coefficient, and the beam; and transmitting a beamformed signal using a forming vector.

A method of operating a terminal in a wireless communication system according to another embodiment of the present invention includes a process of determining long-term channel information from instantaneous channel parameters collected at a plurality of points in time, and the long-period and transmitting the long-period channel information to the base station when the change amount of the channel information exceeds a threshold.

In a wireless communication system according to another embodiment of the present invention, the base station apparatus, when the amount of change in long-period channel information determined from instantaneous channel parameters collected at multiple points in time exceeds a threshold, the transmission signal to the terminal is A control unit that updates a leak coefficient indicating a rate acting as interference to at least one other terminal, and determines a beamforming vector based on the leak coefficient, and a transmitter configured to transmit a beamformed signal using the beamforming vector. characterized in that

In a wireless communication system according to another embodiment of the present invention, a terminal device includes: a control unit that determines long-period channel information from instantaneous channel parameters collected at a plurality of points in time; and a threshold value of a change amount of the long-period channel information If it exceeds, it characterized in that it comprises a communication unit for transmitting the long-period channel information to the base station.

Efficient beamforming with low computational complexity is possible by performing leakage coefficient only when channel statistic or SNR (Signal-to-Noise Ratio) is changed based on random probability theory in a wireless communication system . In addition, the technique presented in the present invention has high utility because it can be extended to a system in which multiple users exist per cell instead of a single user per cell.

1 illustrates an example of an interference generating environment in a wireless communication system according to an embodiment of the present invention.
2 illustrates another example of an interference generating environment in a wireless communication system according to an embodiment of the present invention.
3 illustrates another example of an interference generating environment in a wireless communication system according to an embodiment of the present invention.
4 illustrates base stations and terminals in a wireless communication system according to an embodiment of the present invention.
5 illustrates an operation procedure of a base station in a wireless communication system according to an embodiment of the present invention.
6 illustrates an operation procedure of a terminal in a wireless communication system according to an embodiment of the present invention.
7 illustrates an operation procedure of a terminal in a wireless communication system according to another embodiment of the present invention.
8 illustrates an operation procedure of a base station in a wireless communication system according to another embodiment of the present invention.
9 illustrates an operation procedure of a terminal in a wireless communication system according to another embodiment of the present invention.
10 illustrates a block configuration of a base station in a wireless communication system according to an embodiment of the present invention.
11 illustrates a block configuration of a terminal in a wireless communication system according to an embodiment of the present invention.
12 to 14 show performance of a beamforming technique according to an embodiment of the present invention.

Hereinafter, the operating principle of the present invention will be described in detail with reference to the accompanying drawings. In the following description of the present invention, if it is determined that a detailed description of a known function or configuration related to the present invention may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted. In addition, the terms described below are terms defined in consideration of functions in the present invention, which may vary according to intentions or customs of users and operators. Therefore, the definition should be made based on the content throughout this specification.

Hereinafter, a description will be given of a technique for beamforming in consideration of an interference channel in a wireless communication system.

A term indicating parameters used to determine a beamforming vector used in the following description, a term indicating network entities, and the like are for convenience of description. Therefore, the present invention is not limited to the terms described below, and other terms referring to objects having equivalent technical meanings may be used.

1 illustrates an example of an interference generating environment in a wireless communication system according to an embodiment of the present invention. 1 illustrates a case in which three base stations 110-1 to 110-3 and three terminals 120-1 to 120-3 perform communication.

1, base station A 110-1 is terminal A 120-1, base station B 110-2 is terminal B 120-2, and base station C 110-3 is terminal Send a signal to C(120-C). Since the terminals 120-1 to 120-3 are all located at the cell boundary, the terminals 120-1 to 120-3 can also receive signals from base stations other than a serving base station. . That is, the signal of the base station A 110-1 is a signal intended for the terminal A 120-1, and an interference signal to the terminal B 120-2 and the terminal C 120-3. acts as Similarly, the signal of the base station B 110-2 is a signal intended for the terminal B 120-2, and acts as an interference signal to the terminal A 120-1 and the terminal C 120-3. do. In addition, the signal of the base station C 110-3 is a signal intended for the terminal C 120-3, and acts as an interference signal to the terminal A 120-1 and the terminal B 120-2. .

2 illustrates another example of an interference generating environment in a wireless communication system according to an embodiment of the present invention. 2 illustrates an environment in which two base stations 210-1 and 210-2 and four terminals 220-1 to 220-4 perform communication.

2, base station A 210-1 is terminal A 220-1 and terminal B 220-2, and base station B 210-2 is terminal C 220-3 and terminal D Send a signal to (220-4). That is, unlike the example of FIG. 1 , the base station A 210 - 1 and the base station B 210 - 2 may transmit different data to different terminals through the same resource. In this case, the terminals 220-1 to 220-4 may also receive signals from base stations other than the serving base station. Accordingly, the signal of the base station A 210-1 is a signal intended for the terminal A 220-1 and the terminal B 220-2, and the terminal C 220-3 and the terminal D ( 220-4) as an interference signal. Similarly, the signal of the base station B 210-2 is a signal intended for the terminal C 220-3 and the terminal D 220-4, and the terminal A 220-1 and the terminal B ( 220-2) as an interference signal.

3 illustrates another example of an interference generating environment in a wireless communication system according to an embodiment of the present invention. 3 illustrates an ad-hoc network environment. The ad-hoc network refers to a network having an autonomous structure that communicates with each other between individually present wireless communication-capable nodes.

Referring to FIG. 3 , a plurality of nodes 301 to 309 including the terminal 301 constitute the ad-hoc network. Since the ad-hoc network is autonomously configured, various types of interference signals may be generated. Accordingly, a node transmitting a signal among the plurality of nodes 301 to 309 may mitigate interference by performing beamforming according to embodiments to be described below.

Various embodiments of the present invention propose an efficient beamforming technique in an environment in which interference exists. The system considered in the present invention may transmit a signal to one user within a specific resource as shown in FIG. 1, and may transmit a signal to multiple users within a specific resource as shown in FIG. 2 . Embodiments of the present invention have the advantage that a plurality of base stations can efficiently perform beamforming without cooperation, and can effectively increase the overall system throughput. Furthermore, the present invention can be easily applied to a cellular system, an ad-hoc network, etc., which are wireless communication environments in which interference exists, and can also be applied to a system of 5G or 4G or higher (Beyond 4G), which is a next-generation wireless communication.

An embodiment of the present invention proposes a method in which each base station calculates a beamforming vector using local CSI (Channel State Information) in an interference channel situation. Unlike conventional techniques, the algorithm according to an embodiment of the present invention uses long-term channel statistic information, and thus has relatively low computational complexity. Here, the long-period channel statistics are short-term statistics represented by instantaneous channel information such as signal to noise ratio (SNR), channel correlation, and path loss. Compared to , it means a channel-related parameter that changes relatively slowly.

Hereinafter, an embodiment of the present invention in consideration of an IFC (Interference Channel) environment in which a plurality of base stations having multiple antennas as shown in FIG. 1 service a plurality of terminals will be described. In this case, base stations and terminals may be modeled as shown in FIG. 4 below.

4 illustrates base stations and terminals in a wireless communication system according to an embodiment of the present invention. Referring to FIG. 4 , M base stations 410-1 to 410-M transmit signals to M terminals 420-1 to 420-M. Each of the M base stations (410-1 to 410-M) transmit data S ₁ to S _M Beamforming is performed using each of the beamforming vectors V ₁ to V _{M, respectively.}

In the case of FIG. 4, terminal-m receives an intended signal from base station-m, and signals received from other base stations all act as interference. The signal received by the terminal-m may be expressed as in Equation 1 below.

은 단말-m의 수신 신호, 상기

은 기지국-m 및 단말-m간 채널 벡터, 상기

은 단말-m을 위한 빔포밍 벡터, 상기

은 단말-m의 데이터, 상기

은 기지국의 개수, 상기

는 기지국-j 및 단말-m간 채널 벡터, 상기

은 단말-j를 위한 빔포밍 벡터, 상기

은 단말-m에 수신되는 잡음을 의미한다. 상기 <수학식 1>에서, 상기

및 상기

이외의 성분은 단말-m에게 셀 간 간섭(inter-cell interference)으로 작용한다.In the <Equation 1>, the

is the received signal of terminal-m, the

is a channel vector between base station-m and terminal-m, wherein

is a beamforming vector for UE-m, wherein

is the data of terminal-m, the above

is the number of base stations,

is a channel vector between base station-j and terminal-m, wherein

is a beamforming vector for UE-j, wherein

denotes noise received by UE-m. In the <Equation 1>, the

and said

Other components act as inter-cell interference to UE-m.

The SINR (Signal to Interference and Noise Ratio) of the terminal-m may be determined as in Equation 4 below.

는 단말-m의 SINR, 상기

는 기지국-m 및 단말-m간 채널 벡터, 상기

은 단말-m을 위한 빔포밍 벡터, 상기

는 잡음 분산, 상기

는 기지국-j 및 단말-m간 채널 벡터, 상기

은 단말-j를 위한 빔포밍 벡터, 상기

은 기지국의 개수를 의미한다.In the <Equation 2>, the

is the SINR of UE-m, where

is a channel vector between base station-m and terminal-m, wherein

is a beamforming vector for UE-m, wherein

is the noise variance, above

is a channel vector between base station-j and terminal-m, wherein

is a beamforming vector for UE-j, wherein

is the number of base stations.

Accordingly, the problem of calculating a beamforming vector that maximizes a weighted sum rate (WSR) may be expressed as Equation 3 below.

은 빔포밍 벡터, 상기

은 기지국의 개수, 상기

은 단말-m을 위한 가중치(weight) 항(term), 상기

은 빔포밍 벡터

을 사용한 경우 단말-m의 성취 가능한 전송률(achievable rate)을 의미한다. 상기 가중치

는 양수로서, 단말-m의 QoS(Quality of Service)를 만족시키기 위해 결정되며, 상기 단말-m의 QoS 및 스케줄링 기법에 의하여 결정될 수 있다.

인 경우, 다시 말해, 기지국의 안테나 개수가 기지국의 개수보다 큰 경우, 최적(optimality) 손해 없이

로 결정된다. In the <Equation 3>, the

is a beamforming vector, said

is the number of base stations,

is a weight term for UE-m, the

Silver Beamforming Vector

In case of using , it means an achievable rate of UE-m. the weight

is a positive number and is determined to satisfy the QoS (Quality of Service) of UE-m, and may be determined according to the QoS and scheduling scheme of UE-m.

In other words, when the number of antennas of the base station is greater than the number of base stations, there is no loss of optimality.

is determined by

In order to determine the solution of the problem as in <Equation 3>, the paper "R. Zhang and S. Cui, “Cooperative interference management with MISO beamforming”, IEEE Transactions on Signal Processing, Oct. 2010, a method of determining a beamforming vector that achieves the Pareto-optimal of the above problem using a leak coefficient as in Equation 4 below has been proposed.

은 단말-m을 위한 빔포밍 벡터, 상기

는 잡음 분산, 상기

은 크기 N의 단위 행렬, 상기

은 기지국-m에서 단말-j로의 신호에 대한 누출 계수, 상기

는 기지국-m 및 단말-j 간 채널 벡터, 상기

은 정규화(normalization) 전의 단말-m을 위한 빔포밍 벡터를 의미한다. In the <Equation 4>, the

is a beamforming vector for UE-m, wherein

is the noise variance, above

is the identity matrix of size N, where

is the leakage coefficient for the signal from base station-m to terminal-j, where

is a channel vector between base station-m and terminal-j, wherein

denotes a beamforming vector for UE-m before normalization.

In addition, the paper "S.-H. Park, H. Park, H. Kong, and I. Lee, "New beamforming techniques based on virtual SINR maximization for coordinated multi-cell transmission," IEEE Transactions on Wireless Communications, Mar. 2012.", a method of determining the leakage coefficient using the relationship between the weight-sum data rate and virtual SINR (VSINR) has been proposed. The VSINR refers to a ratio of a signal to a specific receiving end and an interference in which the signal affects another receiving end. The VSINR may be defined as in Equation 5 below.

은 단말-m에 대한 VSINR, 상기

는 기지국-m 및 단말-m간 채널 벡터, 상기

은 단말-m을 위한 빔포밍 벡터, 상기

는 잡음 분산, 상기

은 기지국-m에서 단말-j로의 신호에 대한 누출 계수, 상기

는 기지국-m 및 단말-j간 채널 벡터를 의미한다. 상기 누출 계수는 단말-m으로의 신호가 다른 단말에게 간섭으로 작용하는 양적 비율을 의미한다.In the <Equation 5>, the

is the VSINR for UE-m, where

is a channel vector between base station-m and terminal-m, wherein

is a beamforming vector for UE-m, wherein

is the noise variance, above

is the leakage coefficient for the signal from base station-m to terminal-j, where

denotes a channel vector between base station-m and terminal-j. The leak coefficient refers to a quantitative ratio at which a signal to terminal-m acts as interference to other terminals.

는 기지국-k에서 단말-j로의 신호에 대한 누출 계수, 상기

는 잡음 분산, 상기

은 기지국의 개수, 상기

는 기지국-k 및 단말-i 간 채널 벡터, 상기

는 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

는 단말-k를 위한 가중치를 의미한다. 상기

는 및 상기

는 순시적(instantaneous) CSI(Channel State Information)에 의해 결정된다.In the <Equation 6>, the

is the leakage coefficient for the signal from base station-k to terminal-j, where

is the noise variance, above

is the number of base stations,

is a channel vector between base station-k and terminal-i, wherein

is a beamforming vector for UE-k before normalization, wherein

denotes a weight for UE-k. remind

is and said

is determined by instantaneous CSI (Channel State Information).

The methods shown in <Equation 4> and <Equation 6> have relatively high algorithm complexity because the leakage coefficient must be re-determined whenever a channel is changed. Therefore, an embodiment of the present invention proposes a new technique for calculating the leakage coefficient using the random matrix theory.

의 비율, 다시 말해, 기지국의 개수 대 기지국의 안테나 개수의 비율이 고정되어있는 상황에서, 상기 안테나 개수가 무한히 커지면, 상기 누출 계수는 하기 <수학식 7>과 같은 결정적 등가물(deterministic equivalent)에 거의 확실하게(almost surely) 수렴할 수 있다.Using the results of the random matrix theory,

In a situation in which the ratio of , that is, the ratio of the number of base stations to the number of antennas of the base station is fixed, when the number of antennas becomes infinitely large, the leakage coefficient is almost to a deterministic equivalent as shown in Equation 7 below. can converge most surely.

는 누출 계수의 결정적 등가물, 상기

는 잡음 분산, 상기

은 기지국의 개수, 상기

는 누출 간섭(leakage interference)의 전력, 상기

는 전력 정규화 항(power normalization term), 상기

는 단말-k를 위한 가중치, 상기

는 단말-k에 대한 의도한 신호 전력을 의미한다.In the <Equation 7>, the

is the deterministic equivalent of the leak coefficient, where

is the noise variance, above

is the number of base stations,

is the power of leakage interference, where

is a power normalization term, wherein

is the weight for terminal-k,

denotes the intended signal power for UE-k.

및 전력 정규화 항

은 하기 <수학식 8>과 같이 얻어질 수 있다.Power of the intended signal

and power normalization term

can be obtained as in the following <Equation 8>.

는 단말-k에 대한 의도한 신호 전력, 상기

은 기지국의 안테나 개수, 상기

는 누출 계수들의 집합, 상기

는 잡음 분산, 상기

는 전력 정규화 항을 의미한다. 상기

는

로 정의될 수 있다. 상기 <수학식 8>에 포함된 함수

및 함수

는 하기 <수학식 9>와 같이 정의된다.In the <Equation 8>, the

is the intended signal power for terminal-k, where

is the number of antennas of the base station,

is the set of leak coefficients, where

is the noise variance, above

is the power normalization term. remind

Is

can be defined as The function included in <Equation 8>

and functions

is defined as in Equation 9 below.

은 기지국의 안테나 개수, 상기

는 임의의 집합, 상기

는 집합

의 i번째 원소, 상기

는 양의 스칼라(scalar) 값, 상기

는 고정 점 방정식(fixed-point equation)

의 유일한(unique) 양의 해(positive solution), 상기

은 크기 N의 단위 행렬, 상기

는

들의 집합을 의미한다.In the <Equation 9>, the

is the number of antennas of the base station,

is any set, said

is set

the i-th element of

is a positive scalar value, where

is a fixed-point equation

The unique positive solution of

is the identity matrix of size N, where

Is

means a set of

, 전력 정규화 항

, 누출 간섭의 전력(leakage interference power)

의 세 가지 변수들로 구성된다. 불규칙 행렬 이론을 이용하여, N이 커짐에 따라 각각의 항이 어떤 형태로 수렴하는지 확인할 수 있다면, 상기 누출 계수의 결정적 등가물이 용이하게 구성될 수 있다. 상기 의도한 신호의 전력을 살펴보면, 누출 계수가 주어진 상황에서 하기 <수학식 10>와 같은 관계식이 얻어질 수 있다.Paper "S.-H. Park, H. Park, H. Kong, and I. Lee, "New beamforming techniques based on virtual SINR maximization for coordinated multi-cell transmission," IEEE Transactions on Wireless Communications, Mar. The leakage coefficient suggested in 2012.” is the power of the intended signal.

, power normalization term

, leakage interference power

It consists of three variables of Using the random matrix theory, if it is possible to check how each term converges as N increases, a deterministic equivalent of the leak coefficient can be easily constructed. Looking at the power of the intended signal, a relation such as Equation 10 below can be obtained in a situation where the leakage coefficient is given.

는 기지국-k 및 단말-k 간 채널 벡터, 상기

은 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

는 잡음 분산, 상기

은 크기 N의 단위 행렬, 상기

은 기지국-k에서 단말-j로의 신호에 대한 누출 계수, 상기

은 기지국의 안테나 개수를 의미한다. 상기

는 N×N 크기의 행렬로서, 하기 <수학식 11>과 같이 정의된다.In the <Equation 10>, the

is a channel vector between base station-k and terminal-k, wherein

is a beamforming vector for UE-k before normalization, the above

is the noise variance, above

is the identity matrix of size N, where

is the leakage coefficient for the signal from base station-k to terminal-j, where

is the number of antennas of the base station. remind

is a matrix of size N×N, and is defined as in Equation 11 below.

는 잡음 분산, 상기

은 기지국의 안테나 개수, 상기

은 크기 N의 단위 행렬, 상기

은 기지국-k에서 단말-j로의 신호에 대한 누출 계수, 상기

는 기지국-k 및 단말-j 간 채널 벡터를 의미한다.In the <Equation 11>, the

is the noise variance, above

is the number of antennas of the base station,

is the identity matrix of size N, where

is the leakage coefficient for the signal from base station-k to terminal-j, where

denotes a channel vector between base station-k and terminal-j.

On the other hand, N×N matrix series A ₁ , A ₂ , ... and random vector series x ₁ , x ₂ , … It has been found that the same result as in <Equation 12> is established for .

은 길이가 N이고 각 원소가 평균이 0, 분산이 1/N 인 랜덤 변수로 이루어진 벡터, 상기

은 임의의 N×N 행렬, 기호

는 N이 무한대로 커질 때 거의 확실하게(almost surely) 하게 수렴함을 의미한다. 불규칙 행렬 이론을 이용한 위 결과에

,

를 대입하면, 하기 <수학식 13>의 관계가 성립할 수 있다.In the <Equation 12>, the

is a vector of random variables of length N, each element having a mean of 0 and a variance of 1/N, wherein

is any N×N matrix, symbol

means that it almost surely converges as N increases to infinity. Based on the above results using the random matrix theory,

,

By substituting , the relationship of the following <Equation 13> may be established.

는 기지국-k 및 단말-k 간 채널 벡터, 상기

은 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

은 기지국의 안테나 개수, 상기

는 N×N 크기의 상기 <수학식 11>과 같이 정의되는 행렬을 의미한다.In the <Equation 13>, the

is a channel vector between base station-k and terminal-k, wherein

is a beamforming vector for UE-k before normalization, the above

is the number of antennas of the base station,

denotes a matrix defined as in Equation 11 above with a size of N×N.

에 대해,

를 열(column)로 갖는 랜덤 행렬

는 하기 <수학식 14>을 만족함을 보였다.A paper based on the random matrix theory 「S. Wagner, R. Couillet, M. Debbah, and DTMSlock, “Large system analysis of linear precoding in correlated MISO broadcast channels under limited feedback”, IEEE Transactions on Information Theory, July 2012」 Random vector with elements with this 0 and variance 1

About,

Random matrix having as a column

showed that the following <Equation 14> was satisfied.

은 랜덤 행렬

의 열 또는 행 개수, 상기

는

을 열로 갖는 랜덤 행렬, 상기

는 양의 스칼라 값, 상기

은 크기

의 단위 행렬을 의미한다. 상기

는 N×N 행렬로서, 하기 <수학식 15>와 같이 정의된다.In the <Equation 14>, the

is a random matrix

number of columns or rows in the above

Is

A random matrix with as columns,

is a positive scalar value, where

silver size

means the identity matrix of remind

is an N×N matrix, and is defined as in Equation 15 below.

은 상기

의 열 또는 행의 개수, 상기

는 단말-k에 대한 채널 공분산(channel covariance), 상기

는 방정식

의 유일한 양의 해, 상기

는 SNR(Signal to Noise Ratio), 상기

은 크기 N의 단위 행렬을 의미한다.In the <Equation 15>, the

is said

number of columns or rows in the above

is the channel covariance for terminal-k, the

is the equation

The only positive year of

is the signal to noise ratio (SNR), the

denotes an identity matrix of size N.

및

를 이용하면, 하기 <수학식 16>와 같은 결과가 도출될 수 있다.the above

and

By using , a result as shown in Equation 16 below can be derived.

는 기지국-k 및 단말-k 간 채널 벡터, 상기

은 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

는 단말-k에 대한 의도한 신호 전력, 상기

은 기지국의 안테나 개수를 의미한다.In the <Equation 16>, the

is a channel vector between base station-k and terminal-k, wherein

is a beamforming vector for UE-k before normalization, the above

is the intended signal power for terminal-k, where

is the number of antennas of the base station.

은 하기 <수학식 17>과 같은 관계식을 만족한다.On the other hand, the paper "S.-H. Park, H. Park, H. Kong, and I. Lee, "New beamforming techniques based on virtual SINR maximization for coordinated multi-cell transmission," IEEE Transactions on Wireless Communications, Mar. 2012.”, the power normalization term

satisfies a relational expression such as <Equation 17> below.

은 전력 정규화 항, 상기

는 기지국-k 및 단말-k 간 채널 벡터, 상기

는 잡음 분산, 상기

은 크기 N의 단위 행렬, 상기

은 기지국의 개수, 상기

은 기지국-k에서 단말-j로의 신호에 대한 누출 계수를 의미한다.In the <Equation 17>, the

is the power normalization term, where

is a channel vector between base station-k and terminal-k, wherein

is the noise variance, above

is the identity matrix of size N, where

is the number of base stations,

denotes a leakage coefficient for a signal from base station-k to terminal-j.

에 대해서 하기 <수학식 18>의 결과를 도출해 낼 수 있다.When the result of the random matrix theory is applied to the <Equation 17>, the power normalization term

For , the result of the following <Equation 18> can be derived.

은 전력 정규화 항, 상기

은 기지국의 안테나 개수, 상기

는 N×N 크기의 상기 <수학식 11>과 같이 정의되는 행렬을 의미한다.In the <Equation 18>, the

is the power normalization term, where

is the number of antennas of the base station,

denotes a matrix defined as in Equation 11 above with a size of N×N.

대해 하기 <수학식 19>와 같은 결과가 성립한다.According to the theorem presented in the paper 「S. Wagner, R. Couillet, M. Debbah, and DTMSlock, “Large system analysis of linear precoding in correlated MISO broadcast channels under limited feedback”, IEEE Transactions on Information Theory, July 2012.」 , random matrix

For the following <Equation 19>, the same result is established.

은 상기 랜덤 행렬

의 행 또는 열 개수, 상기

는 랜덤 행렬, 상기

는 양의 스칼라 값, 상기

은 크기 N의 단위 행렬을 의미한다. 상기

는 N×N 행렬로서, 하기 <수학식 20>과 같이 정의된다.In the <Equation 19>, the

is the random matrix

number of rows or columns in the above

is a random matrix, where

is a positive scalar value, where

denotes an identity matrix of size N. remind

is an N×N matrix, and is defined as in Equation 20 below.

는 상기 <수학식 15>와 같이 정의되는 행렬, 상기

은 상기 랜덤 행렬

의 행 또는 열 개수, 상기

는 방정식

의 유일한 양의 해, 상기

는 크기 K의 단위 행렬, 상기

는 양의 스칼라 값을 의미한다.According to the <Equation 20>, the

is a matrix defined as in Equation 15 above,

is the random matrix

number of rows or columns in the above

is the equation

The only positive year of

is the identity matrix of size K, where

is a positive scalar value.

Accordingly, a conclusion such as the following <Equation 21> can be derived.

은 전력 정규화 항, 상기

는 전력 정규화 항의 결정적 등가물, 상기

은 기지국의 안테나 개수를 의미한다.In the <Equation 21>, the

is the power normalization term, where

is the deterministic equivalent of the power normalization term, where

is the number of antennas of the base station.

Finally, the power of leakage interference can be expressed as Equation 22 below.

는 기지국-k 및 단말-j 간 채널 벡터, 상기

은 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

은 기지국의 안테나 개수, 상기

는 N×N 크기의 상기 <수학식 11>과 같이 정의되는 행렬을 의미한다.In the <Equation 22>, the

is a channel vector between base station-k and terminal-j, wherein

is a beamforming vector for UE-k before normalization, the above

is the number of antennas of the base station,

denotes a matrix defined as in Equation 11 above with a size of N×N.

If the random matrix theory is applied similarly to the case of the power of the intended signal, the power of the leakage interference can almost certainly converge as shown in Equation 23 below.

는 기지국-k 및 단말-j 간 채널 벡터, 상기

은 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

은 기지국의 안테나 개수, 상기

는 N×N 크기의 상기 <수학식 11>과 같이 정의되는 행렬을 의미한다.In the <Equation 23>, the

is a channel vector between base station-k and terminal-j, wherein

is a beamforming vector for UE-k before normalization, the above

is the number of antennas of the base station,

denotes a matrix defined as in Equation 11 above with a size of N×N.

In this case, if the Sherman-Morrison matrix inversion formula is used, a result as shown in Equation 24 may be derived.

은 기지국의 안테나 개수, 상기

는 기지국-k 및 단말-j 간 채널 벡터, 상기

는 N×N 크기의 상기 <수학식 11>과 같이 정의되는 행렬, 상기

은 기지국-k에서 단말-j로의 신호에 대한 누출 계수를 의미한다. 상기

는 N×N 크기의 행렬로서, 하기 <수학식 25>와 같이 정의된다.In the <Equation 25>, the

is the number of antennas of the base station,

is a channel vector between base station-k and terminal-j, wherein

is a matrix defined as in <Equation 11> with a size of N×N, the

denotes a leakage coefficient for a signal from base station-k to terminal-j. remind

is a matrix of size N×N, and is defined as in Equation 25 below.

는 잡음 분산, 상기

은 기지국의 안테나 개수, 상기

은 크기 N의 단위 행렬, 상기

은 기지국의 개수, 상기

은 기지국-k에서 단말-j로의 신호에 대한 누출 계수, 상기

는 기지국-k 및 단말-i 간 채널 벡터를 의미한다.In the <Equation 25>, the

is the noise variance, above

is the number of antennas of the base station,

is the identity matrix of size N, where

is the number of base stations,

is the leakage coefficient for the signal from base station-k to terminal-j, where

denotes a channel vector between base station-k and terminal-i.

Paper 「R. Couillet and M. Debbah, Random Matrix Methods for Wireless Communications, 1st ed. Cambridge University Press, 2011.", the following <Equation 26> can be derived.

은 기지국의 안테나 개수, 상기

는 상기 <수학식 25>와 같이 정의되는 N×N 크기의 행렬, 상기

는 상기 <수학식 9>와 같이 정의되는 함수, 상기

는

로 정의되는 집합, 상기

는 잡음 분산을 의미한다.In the <Equation 26>, the

is the number of antennas of the base station,

is an N×N matrix defined as in Equation 25, wherein

is a function defined as in <Equation 9>, wherein

Is

A set defined by

is the noise dispersion.

는 하기 <수학식 27>과 같이 거의 확실하게(almost surely) 수렴한다.In the above <Equation 26>, the paper "S. Wagner, R. Couillet, M. Debbah, and DTMSlock, "Large system analysis of linear precoding in correlated MISO broadcast channels under limited feedback", IEEE Transactions on Information Theory, July 2012. Using the theorem of S. Wagner, R. Couillet, M. Debbah, and DTMSlock, "Large system analysis of linear precoding in correlated MISO broadcast channels under limited feedback", IEEE Transactions on Information Theory, July 2012., power

converges almost surely as shown in Equation 27 below.

은 기지국의 안테나 개수, 상기

는 상기 <수학식 25>와 같이 정의되는 N×N 크기의 행렬, 상기

는 상기 <수학식 9>와 같이 정의되는 함수, 상기

는

로 정의되는 집합, 상기

는 잡음 분산을 의미한다.In the <Equation 27>, the

is the number of antennas of the base station,

is an N×N matrix defined as in Equation 25, wherein

is a function defined as in <Equation 9>, wherein

Is

A set defined by

is the noise dispersion.

Accordingly, a conclusion such as the following <Equation 28> can be obtained.

는 기지국-k 및 단말-j 간 채널 벡터, 상기

은 정규화 전의 단말-k를 위한 빔포밍 벡터, 상기

는 누출 간섭 항, 상기

은 기지국의 안테나 개수, 상기

는 전력 정규화 항, 상기

은 기지국-k에서 단말-j로의 신호에 대한 누출 계수, 상기

는 <수학식 26>와 같이 정의되는 변수를 의미한다.
In the <Equation 28>, the

is a channel vector between base station-k and terminal-j, wherein

is a beamforming vector for UE-k before normalization, the above

is the leak interference term, said

is the number of antennas of the base station,

is the power normalization term, where

is the leakage coefficient for the signal from base station-k to terminal-j, where

denotes a variable defined as in <Equation 26>.

As described above, the deterministic equivalent of the leak coefficient can be determined. As a result, the algorithm for calculating the deterministic equivalent of the leak coefficient can be summarized as in Table 1 below.

Step 1

인 모든

에 대하여,

초기화

being all

about,

reset Step 2 every

Using a fixed-point algorithm for

and

for

field output Step 3 every

for

based on them,

,

,

Calculation Step 4 every

weight coefficient according to <Equation 7> for

renewal Step 5 Return to step 2 and repeat until convergence

로 정의할 때,

가 임계치(threshold) 이하인 조건이 만족되면, 특정 값으로 수렴했다고 판단하고, 알고리즘을 종료한다. 상기 임계치는 다양한 방법으로 설정될 수 있다. 이하 모의 실험의 경우, 상기 임계치는 10^-6으로 설정되었다.

When defined as

If the condition that is less than or equal to a threshold is satisfied, it is determined that the convergence to a specific value is reached, and the algorithm is terminated. The threshold may be set in various ways. For the following simulation, the threshold was set to ^{10 −6 .}

As described above, in the beamforming technique according to an embodiment of the present invention, the leakage coefficient or the decisive equivalent of the leakage coefficient is determined when the change in long-period channel information (eg, SNR, channel covariance, etc.) exceeds a specific threshold. is calculated For the calculation of the leakage coefficient, a deterministic equivalent based on the random matrix theory is used. In this case, the leakage coefficient may be determined through a simplified process requiring only the long-period channel information, the number of antennas, and the number of terminals, not the instantaneous channel information. Accordingly, base stations can exchange long-period channel information with other base stations only when it is necessary to determine the leakage coefficient. Accordingly, computational complexity and system overhead can be greatly reduced.

(

)를 획득해야 한다. 또한, 빔포밍 벡터를 결정하기 위해 사용되는 누출 계수

를 결정하기 위해, 각 기지국은 모든 사용자로에 대한 SNR

(

) 및 채널 공분산

(

)을 획득해야 한다. 예를 들어, 3개의 기지국들 및 3개의 단말들이 존재하는 경우, 하기 <표 2>와 같은 정보가 요구된다.As described above, in order for each of the plurality of base stations to perform distributed beamforming, each base station transmits all channel information.

(

) should be obtained. Also, the leak factor used to determine the beamforming vector

To determine the SNR for each base station, all users

(

) and channel covariance

(

) should be obtained. For example, when there are three base stations and three terminals, information as shown in Table 2 below is required.

Base Station-A Base Station-B Base Station-C Terminal-A ρ ₁₁ , R ₁₁ ρ ₁₂ , R ₁₂ ρ ₁₃ , R ₁₃ terminal-B ρ ₂₁ , R ₂₁ ρ ₂₃ , R ₂₃ ρ ₂₃ , R ₂₃ terminal-C ρ ₃₁ , R ₃₁ ρ ₃₂ , R ₃₂ ρ ₃₃ , R ₃₃

As shown in Table 2 above, when three base stations and three terminals perform communication, a total of 18 parameters are required. According to the algorithm according to an embodiment of the present invention, the leak coefficient can be calculated only when long-period statistics (eg, SNR, channel covariance, channel correlation, channel distribution, etc.) change.

In an IFBC (Interference Broadcast Channel) environment in which one base station shown in FIG. 2 serves multiple terminals, the above-described technique may be applied. The problem of maximizing the weight-sum data rate can be presented as in Equation 29 below.

는 단말-u를 위해 기지국-l에서 사용하는 빔포밍 벡터, 상기

는 가중치-합 전송률, 상기

는 셀 당 단말의 개수를 의미한다. 상기, 가중치-합 전송률

및 SINR는 하기 <수학식 30>와 같이 정의된다.In the <Equation 29>, the

is a beamforming vector used by base station-l for terminal-u, the

is the weight-sum data rate, where

denotes the number of terminals per cell. Above, weight-sum transmission rate

and SINR is defined as in Equation 30 below.

는 가중치-합 전송률, 상기

는 단말-u를 위해 기지국-l에서 사용하는 빔포밍 벡터, 상기

은 기지국의 개수, 상기

는 셀 당 단말의 개수, 상기

는 단말-k 및 기지국-m에 대한 가중치, 상기

는 단말-k 및 기지국-m 간 전송률, 상기

은 SINR, 상기

은 기지국-m의 셀 내에 위치한 단말-k 및 기지국-m 간 채널 벡터, 상기

는 기지국-m의 셀 내에 위치한 단말-k 및 기지국-j 간 채널 벡터, 상기

는 잡음 분산을 의미한다.In the <Equation 30>, the

is the weight-sum data rate, where

is a beamforming vector used by base station-l for terminal-u, the

is the number of base stations,

is the number of terminals per cell, the

is the weight for terminal-k and base station-m, where

is the data rate between terminal-k and base station-m, where

is SINR, said

is a channel vector between terminal-k and base station-m located in the cell of base station-m, wherein

is a channel vector between terminal-k and base station-j located in the cell of base station-m, wherein

is the noise dispersion.

Unlike the IFC environment, in the IFBC environment, the allocation of transmit power should be further considered. In a method similar to the IFC, the leakage coefficient and each variable may be defined as in Equation 31 below.

는 누출 계수의 결정적 등가물, 상기

는 셀 당 단말 개수, 상기

는 잡음 분산, 상기

는 누출 간섭 항, 상기

는 전력 정규화 항, 상기

는 기지국-m 및 단말-k에 대한 가중치, 상기

는 기지국-m으로부터 단말-k로의 의도한 신호 전력, 상기

는 누출 계수들의 집합, 상기

은 기지국 안테나 개수, 상기

및 상기

는 상기 <수학식 9>와 같이 정의되는 함수, 상기

는 누출 계수를 의미한다.In the <Equation 31>, the

is the deterministic equivalent of the leak coefficient, where

is the number of terminals per cell, the

is the noise variance, above

is the leak interference term, said

is the power normalization term, where

is a weight for base station-m and terminal-k, wherein

is the intended signal power from base station-m to terminal-k, where

is the set of leak coefficients, where

is the number of base station antennas,

and said

is a function defined as in <Equation 9>, wherein

is the leakage coefficient.

The above-mentioned values are determined to be the same as in a system considering equal power in an IFC environment (eg, when there are two users per cell, power of P/2 is allocated to each user). Accordingly, an approximate value of the weight-sum data rate can be obtained as in Equation 32 below.

은 가중치-합 전송률의 근사값, 상기

은 기지국의 개수, 상기 K는 셀 당 단말 개수, 상기

는 단말-k 및 기지국-m에 대한 가중치, 상기

는 SINR, 상기

는 기지국-m이 단말-k에 대하여 할당한 전력, 상기

는 단말-k를 위해 기지국-m에서 사용하는 빔포밍 벡터를 의미한다. 상기

는

로, 상기

는

로 표현될 수 있다.In the <Equation 32>, the

is an approximation of the weight-sum data rate, where

is the number of base stations, K is the number of terminals per cell, the

is the weight for terminal-k and base station-m, where

is the SINR, said

is the power allocated by the base station-m to the terminal-k, the

denotes a beamforming vector used by base station-m for terminal-k. remind

Is

by, said

Is

can be expressed as

에 의해 상기 가중치-합 전송률의 근사값을 최대화하는 전력 할당 결과는 하기 <수학식 33>와 같은 잘 알려진 워터-필링(water-filling) 형태로 얻어질 수 있다.Transmit power limit

The power allocation result maximizing the approximate value of the weight-sum transmission rate by ? can be obtained in a well-known water-filling form as in Equation 33 below.

는 기지국-m이 단말-k에 대하여 할당한 전력,

는 0 또는 x 중 큰 값을 나타내는 함수, 상기

는 단말-k 및 기지국-m에 대한 가중치, 상기

는

을 만족하는 워터 레벨(water level), 상기

는 단말-k를 위해 기지국-m에서 사용하는 빔포밍 벡터, 상기

는 셀 당 단말 개수를 의미한다.In the <Equation 33>, the

is the power allocated by the base station-m to the terminal-k,

is a function representing the greater of 0 or x, where

is the weight for terminal-k and base station-m, where

Is

A water level that satisfies

is a beamforming vector used by base station-m for terminal-k, the

denotes the number of terminals per cell.

Also, in the IFBC environment, the beamforming vector may be determined as in Equation 34 below.

은 단말-k를 위한 기지국-m에서 사용하는 빔포밍 벡터, 상기

는 셀 당 단말의 개수, 상기

은 정규화 전의 단말-k를 위한 기지국-m에서 사용하는 빔포밍 벡터, 상기

는 잡음 분산, 상기

은 크기 N의 단위 행렬, 상기

는 단말-k를 위한 기지국-m에서 사용하는 빔포밍 벡터의 기지국-j에 접속한 단말-u에 대한 누출 계수, 상기

는 기지국-j의 셀 내에 위치한 단말-u 및 기지국-m 간 채널 벡터를 의미한다.
In the <Equation 34>, the

is a beamforming vector used by base station-m for terminal-k, the

is the number of terminals per cell, the

is the beamforming vector used by the base station-m for the terminal-k before normalization, the above

is the noise variance, above

is the identity matrix of size N, where

is the leakage coefficient for the terminal-u connected to the base station-j of the beamforming vector used by the base station-m for the terminal-k, the

denotes a channel vector between the terminal-u and the base station-m located in the cell of the base station-j.

5 illustrates an operation procedure of a base station in a wireless communication system according to an embodiment of the present invention.

Referring to FIG. 5 , the base station sets Th_SNR and Th_Chcov in step 501 . The Th_SNR and the Th_Chcov are thresholds for observing changes in long-period channel statistics. Specifically, Th_SNR denotes a threshold value of SNR variation, and Th_Chcov denotes a threshold value of channel covariance variation. According to another embodiment of the present invention, the threshold of the SNR variation and the threshold of the channel covariance variation may be defined as predetermined system parameters.

Then, the base station proceeds to step 503 to determine the weight of at least one terminal. The weight is determined to satisfy the QoS of the corresponding terminal. Accordingly, the base station may determine the weight based on the QoS request and the scheduling scheme of the at least one terminal.

Next, the base station receives channel-related feedback information from at least one terminal in step 505 . The feedback information includes instantaneous channel information for the at least one terminal.

Next, the base station proceeds to step 507 and measures instantaneous channel information for the at least one terminal. For example, in the case of a Frequency Division Duplex (FDD) system, the base station is instantaneous from feedback information received from the terminal, for example, SNR indicated by Channel Quality Information (CQI), and Precoding Matrix Index (PMI). Channel information can be measured. However, in the case of a time division duplex (TDD) system, the base station directly measures the instantaneous channel information using a sounding reference signal (RS) received from the terminal without feedback from the terminal. can In this case, step 505 may be omitted. However, even in the TDD system, the base station may receive the feedback information.

Thereafter, the base station proceeds to step 509 to determine whether the long-period channel statistics are updated. The long-period channel statistics are channel information determined from instantaneous channel parameters collected at multiple points in time. For example, the long-period channel statistics include at least one of SNR and channel covariance (Chcov). For example, the base station calculates at least one of channel covariance and SNR using instantaneous channel information collected during a period of a relatively longer period than a period for measuring the instantaneous channel information, and calculates at least one of the previous long-period period. The channel change can be determined by comparing it with the long-period channel statistics determined in . For example, the base station may compare the long-period channel statistics by calculating a frobenious norm of the channel covariances of the current section and the previous section. As a result of comparison, if the change amount exceeds a predetermined threshold, for example, if the change amount of the SNR exceeds the Th_SNR or the change amount of the channel covariance exceeds the Th_Chcov, the base station determines that the long-period channel statistics are updated can judge If the long-period channel statistics are not updated, the base station proceeds to step 515 below.

On the other hand, if the long-period channel statistics are updated, the base station proceeds to step 511 and exchanges long-period channel statistics information with at least one other base station of the neighboring cell. The long-period channel statistics information includes at least one of SNR and channel covariance. That is, the base station exchanges information necessary for determining a beamforming vector with at least one other base station through a backhaul network.

Then, in step 513, the base station updates the leak coefficient for the at least one terminal based on the long-period channel statistics information. The leak coefficient refers to a quantitative ratio at which a signal to a corresponding terminal acts as interference to another terminal. For example, the leakage coefficient may be determined according to <Equation 7> or <Equation 31>. According to another embodiment of the present invention, the base station may maintain a table in which leakage coefficients corresponding to input variables are predefined. In this case, the base station may determine the leak coefficient by searching the long-period channel statistics information and the leak coefficient corresponding to the number of antennas of the base station in the table.

Next, the base station determines a beamforming vector for the at least one terminal by using the leak coefficient in step 515 . The beamforming vector may be a VSINR beamforming vector. For example, the beamforming vector may be determined as in Equation 4 above. That is, the base station may determine the beamforming vector based on the leakage coefficient, the instantaneous channel information, SNR, and the like. Specifically, the base station may determine the beamforming vector according to the algorithm shown in Table 1 above.

Thereafter, the base station proceeds to step 517 and transmits data and a reference signal. The data is precoded using the beamforming vector. The reference signal may include a User-Specific RS (URS).

In the embodiment described with reference to FIG. 5, the base station determines whether to update the leak coefficient based on long-period channel statistics. However, according to another embodiment of the present invention, the base station may determine whether to update the leak coefficient according to a notification from the terminal. In this case, the terminal may feed back long-period channel statistics information (eg, SNR, channel covariance, etc.) in an event driven format whenever it is determined that the update of the leak coefficient is necessary.

6 illustrates an operation procedure of a terminal in a wireless communication system according to an embodiment of the present invention.

Referring to FIG. 6 , the terminal sets Th_SNR and Th_Chcov in step 601 . The Th_SNR and the Th_Chcov are system parameters for observing changes in long-period channel statistics. Specifically, Th_SNR denotes a threshold value of SNR variation, and Th_Chcov denotes a threshold value of channel covariance variation. According to another embodiment of the present invention, the terminal may receive from the base station without directly determining the threshold of the SNR variation and the threshold of the channel covariance variation. For example, the threshold of the SNR variation and the threshold of the channel covariance variation may be provided from the base station as system information through a broadcast channel.

Thereafter, the UE proceeds to step 603 to measure CSI and SNR. That is, the terminal may measure the channel state using a signal received from the base station, for example, a reference signal. The channel state may include a channel vector. In addition, the terminal may measure a Received Signal Strength Indicator (RSSI) using the reference signal and calculate an SNR based on the RSSI. As another example, the terminal may measure the channel state and SNR using a synchronization signal.

Next, the terminal proceeds to step 605 to update the channel covariance. That is, the UE determines the channel covariance based on the measured CSI. The channel covariance is a long-period channel statistic and may be calculated using instantaneous channel information collected during a period of relatively longer period than a period in which instantaneous channel information is measured. Here, the channel covariance may be referred to as a sample channel covariance.

Thereafter, the terminal proceeds to step 607 to feed back the CSI. That is, in order to obtain instantaneous channel information in the base station, the terminal provides the CQI to the base station. The CQI may include a PMI. According to another embodiment of the present invention, step 607 may be omitted. For example, when the base station directly measures instantaneous channel information using a signal transmitted from the terminal, the CSI may not be fed back.

Next, the UE proceeds to step 609 to determine whether the SNR variation exceeds the Th_SNR or the channel covariance variation exceeds the Th_Chcov. The amount of change in the channel covariance may be determined by calculating a Provinius norm of the channel covariances of the current section and the previous section.

If the Th_SNR or the change amount of the channel covariance exceeds the Th_Chcov, the terminal feeds back at least one of the channel covariance and the SNR to the base station in step 611 . In this case, the terminal may feed back at least one of the channel covariance and the SNR exceeding a threshold.

7 illustrates an operation procedure of a terminal in a wireless communication system according to another embodiment of the present invention.

Referring to FIG. 7 , the terminal receives a precoded data signal and a reference signal in step 701 . The reference signal may include a user-specified reference signal. The precoding is performed by a beamforming vector determined by the base station.

Next, the terminal proceeds to step 703 to decode the signal intended for the terminal. In other words, the terminal determines an intended signal to the terminal using the reference signal, and decodes the data signal.

8 illustrates an operation procedure of a base station in a wireless communication system according to another embodiment of the present invention.

Referring to FIG. 8 , the base station determines whether the beamforming vector needs to be updated in step 801 . When the amount of change in long-period channel statistics exceeds a threshold, it may be determined that the beamforming vector needs to be updated. To this end, the base station may measure the long-period channel statistics information. Alternatively, when the long-period channel statistics information is fed back from the terminal, the base station may determine that the amount of change in the long-period channel statistics exceeds a threshold.

If the beamforming vector needs to be updated, the base station proceeds to step 803 and exchanges the long-period channel statistics information with at least one other base station. Here, the long-period channel statistics information includes at least one of SNR and channel covariance.

Next, the base station proceeds to step 805 to determine a leak coefficient and a beamforming vector. The base station determines the leakage coefficient based on long-period channel statistics information for a terminal located in a cell of the base station and long-period channel statistics information for a terminal located in another cell. For example, the leakage coefficient may be determined according to <Equation 7> or <Equation 31>. As another example, the base station may determine the leak coefficient using a predefined table. And, the base station determines a beamforming vector for the at least one terminal by using the leak coefficient. For example, the beamforming vector may be determined as in Equation 4 above.

Although not shown in FIG. 8, the base station may beamform a data signal transmitted to the terminal using the beamforming vector, and transmit the beamformed data signal. Furthermore, the base station may transmit a reference signal.

9 illustrates an operation procedure of a terminal in a wireless communication system according to another embodiment of the present invention.

Referring to FIG. 9 , the terminal determines long-period channel statistics information in step 901 . The long-period channel statistics are channel information determined from instantaneous channel parameters collected at multiple points in time. Accordingly, the long-period channel statistics can be determined from instantaneous channel information collected during the long-period. The long-period channel statistics include at least one of SNR and channel covariance.

The terminal proceeds to step 903 and determines whether the beamforming vector needs to be updated. When the amount of change in the long-period channel statistics exceeds a threshold, it may be determined that the beamforming vector needs to be updated. Accordingly, the terminal determines the channel change amount by comparing it with the long-period channel statistics determined in the previous long-period section.

If the beamforming vector needs to be updated, the terminal feeds back the long-period channel statistics information to the base station in step 905 . In this case, the terminal may feed back both the channel covariance and the SNR, or may feed back at least one exceeding a threshold.

Thereafter, although not shown in FIG. 9, the terminal receives a beamformed data signal from the base station. The data signal is beamformed by a beamforming vector determined by the fed back long-period channel statistics information. Also, in addition to the data signal, the terminal may further receive a reference signal.

10 illustrates a block configuration of a base station in a wireless communication system according to an embodiment of the present invention.

10, the base station includes a radio frequency (RF) processing unit 1010, a baseband processing unit 1020, a backhaul communication unit 1030, a storage unit 1040, and a control unit 1050. is composed by

The RF processing unit 1010 performs a function for transmitting and receiving a signal through a wireless channel, such as band conversion and amplification of the signal. That is, the RF processor 1010 up-converts the baseband signal provided from the baseband processor 1020 into an RF band signal, transmits it through an antenna, and converts the RF band signal received through the antenna to a baseband signal. down-convert to For example, the RF processing unit 1010 may include a transmit filter, a receive filter, an amplifier, a mixer, an oscillator, a digital to analog converter (DAC), an analog to digital converter (ADC), and the like. . The RF processing unit 1010 may include a plurality of RF chains.

The baseband processing unit 1020 performs a function of converting between a baseband signal and a bit stream according to a physical layer standard of a system. For example, when transmitting data, the baseband processing unit 1020 generates complex symbols by encoding and modulating a transmitted bit stream. Also, when receiving data, the baseband processing unit 1020 restores a received bit stream by demodulating and decoding the baseband signal provided from the RF processing unit 1010 . For example, in the case of OFDM (Orthgonal Frequency Division Multiplexing), when transmitting data, the baseband processing unit 1020 generates complex symbols by encoding and modulating a transmitted bit stream, and mapping the complex symbols to subcarriers. After that, OFDM symbols are constructed through Inverse Fast Fourier Transform (IFFT) operation and Cyclic Prefix (CP) insertion. In addition, when receiving data, the baseband processing unit 1020 divides the baseband signal provided from the RF processing unit 1010 into OFDM symbol units, and performs a Fast Fourier Transform (FFT) operation on the signals mapped to subcarriers. After restoration, the received bit stream is restored through demodulation and decoding. Also, the baseband processing unit 1020 includes a precoder 1022 that performs beamforming. The precoder 1022 performs precoding by multiplying the transmission data by the beamforming vector determined by the controller 1050 .

The baseband processing unit 1020 and the RF processing unit 1010 transmit and receive signals as described above. Accordingly, the baseband processing unit 1020 and the RF processing unit 1010 may be referred to as a transmitter, a receiver, a transceiver, a communication unit, or a wireless communication unit.

The backhaul communication unit 1030 provides an interface for communicating with other nodes in the network. That is, the backhaul communication unit 1030 converts a bit string transmitted from the base station to another node, for example, another base station into a physical signal, and converts a physical signal received from the other base station into a bit string.

The storage unit 1040 stores data such as basic programs and setting information for the operation of the base station. In particular, according to an embodiment of the present invention, the storage unit 1040 may store a table in which leak coefficients corresponding to input variables are defined in advance. Here, the input variable includes at least one of long-period channel statistics information and the number of antennas of the base station. In addition, the storage unit 1040 provides stored data according to the request of the control unit 1050 .

The controller 1050 controls overall operations of the base station. For example, the control unit 1040 transmits and receives signals through the baseband processing unit 1020 and the RF processing unit 1010 or through the backhaul communication unit 1030 . In addition, the control unit 1040 writes and reads data in the storage unit 1040 . To this end, the controller 1040 may include at least one processor. According to an embodiment of the present invention, the control unit 1050 includes a leak coefficient determiner 1052 that determines a leak coefficient required to determine a beamforming vector, and a beamforming vector that determines a beamforming vector using the leak coefficient. and a decision unit 1054 . For example, the controller 1050 may control the base station to perform the procedure shown in FIG. 5 or FIG. 8 . The operation of the control unit 1050 according to an embodiment of the present invention is as follows.

According to an embodiment of the present invention, the control unit 1050 may control the at least one terminal through feedback information related to a channel received from at least one terminal or through measurement of a signal transmitted from the at least one terminal. Obtain instantaneous channel information for a terminal of Then, the control unit 1050 calculates long-period channel statistics based on the instantaneous channel information collected during the long-period, and determines the channel change amount by comparing the long-period channel statistics determined in the previous long-period channel. do. Here, the long-period channel statistics include at least one of SNR and channel covariance. If the channel change amount exceeds a threshold, the control unit 1050 exchanges long-period channel statistics information with at least one other base station through the backhaul communication unit 1030, and then adds the long-period channel statistics information to the long-period channel statistics information. Based on the update the leak coefficient for the at least one terminal. For example, the leakage coefficient may be determined according to <Equation 7> or <Equation 31>. As another example, the control unit 1050 may determine the leakage coefficient by using a predefined table stored in the storage unit 1040 . In addition, the control unit 1050 determines a beamforming vector for the at least one terminal by using the leakage coefficient. For example, the beamforming vector may be determined as in Equation 4 above. Thereafter, the controller 1050 controls the precoder 1022 to perform beamforming according to the beamforming vector.

According to an embodiment of the present invention, the control unit 1050 may determine whether to update the leak coefficient according to a notification from the terminal. In this case, when the long-period channel statistics information is fed back from the terminal, the controller 1050 determines that the leak coefficient needs to be updated. Accordingly, the controller 1050 may exchange the long-period channel statistics information with the at least one other base station, newly determine the leakage coefficient, and determine the beamforming vector.

11 illustrates a block configuration of a terminal in a wireless communication system according to an embodiment of the present invention.

Referring to FIG. 11 , the terminal includes an RF processing unit 1110 , a baseband processing unit 1120 , a storage unit 1130 , and a control unit 1140 .

The RF processing unit 1110 performs a function for transmitting and receiving a signal through a wireless channel, such as band conversion and amplification of the signal. That is, the RF processor 1110 up-converts the baseband signal provided from the baseband processor 1120 into an RF band signal, transmits it through an antenna, and converts the RF band signal received through the antenna to a baseband signal. down-convert to For example, the RF processing unit 1110 may include a transmit filter, a receive filter, an amplifier, a mixer, an oscillator, a DAC, an ADC, and the like. Although only one antenna is shown in FIG. 11, the terminal may include a plurality of antennas.

The baseband processing unit 1120 performs a function of converting between a baseband signal and a bit stream according to a physical layer standard of the system. For example, when transmitting data, the baseband processing unit 1120 generates complex symbols by encoding and modulating a transmitted bit stream. Also, when receiving data, the baseband processing unit 1120 restores a received bit stream by demodulating and decoding the baseband signal provided from the RF processing unit 1110 . For example, in the case of OFDM, when transmitting data, the baseband processing unit 1120 generates complex symbols by encoding and modulating a transmitted bit stream, maps the complex symbols to subcarriers, and performs IFFT operation and OFDM symbols are configured through CP insertion. Also, upon data reception, the baseband processing unit 1120 divides the baseband signal provided from the RF processing unit 1110 into OFDM symbol units, restores signals mapped to subcarriers through FFT operation, and demodulates them. and decoding the received bit stream. The baseband processing unit 1120 and the RF processing unit 1110 transmit and receive signals as described above. Accordingly, the baseband processing unit 1120 and the RF processing unit 1110 may be referred to as a transmitter, a receiver, a transceiver, or a communication unit.

The storage unit 1130 stores data such as a basic program, an application program, and setting information for the operation of the terminal. In addition, the storage unit 1130 provides stored data according to the request of the control unit 1140 .

The controller 1140 controls overall operations of the terminal. For example, the control unit 1140 transmits and receives signals through the baseband processing unit 1120 and the RF processing unit 1110 . In addition, the control unit 1140 writes and reads data in the storage unit 1140 . To this end, the controller 1140 may include at least one processor. According to an embodiment of the present invention, the control unit 1140 includes a channel information management unit 1142 that determines whether channel information is fed back to the base station and generates channel information to be fed back. For example, the controller 1140 may control the terminal to perform the procedure illustrated in FIG. 6 , FIG. 7 , or FIG. 9 . The operation of the control unit 1140 according to an embodiment of the present invention is as follows.

According to an embodiment of the present invention, the controller 1140 measures long-period channel statistics information. The long-period channel statistics may be determined from instantaneous channel information collected during the long-period. The long-period channel statistics include at least one of SNR and channel covariance. Then, the controller 1140 determines the amount of channel change by comparing it with the long-period channel statistics determined in the previous long-period section. If the channel change amount exceeds a threshold, the controller 1140 feeds back the long-period channel statistics information to the base station. In this case, the controller 1140 may feed back both the channel covariance and the SNR, or feed back at least one exceeding a threshold.

12 to 14 show performance of a beamforming technique according to an embodiment of the present invention. 12 is a weight-sum rate according to the number of iterations, FIG. 13 is a weight-sum rate according to SNR for the conventional technique and the present invention in a single-user environment, and FIG. 14 is a multi-user environment. The weight-sum data rate according to the SNR for the conventional technique and the present invention is shown.

Referring to FIG. 12, the convergence speed of the technique according to an embodiment of the present invention is confirmed. That is, it is confirmed that convergence to the optimal value within two iterations is irrespective of the SNR and the initial leakage coefficient.

Referring to FIG. 13, weight-sum data rates of the scheme according to an embodiment of the present invention and the conventional scheme are compared in a single user environment. As shown in FIG. 13 , the performance degradation of the technique according to an embodiment of the present invention compared to the conventional optimal technique is significantly less than that of other conventional techniques. In other words, the technique according to an embodiment of the present invention shows similar performance to the optimal technique.

Referring to FIG. 14, weight-sum data rates of the scheme according to an embodiment of the present invention and the conventional scheme are compared in a multi-user environment. The technique according to an embodiment of the present invention is divided into a case of equal power allocation and a case of water-filling power allocation. As shown in FIG. 14 , it is confirmed that there is no significant performance degradation compared to the conventional technique.

Methods according to the embodiments described in the claims or specifications of the present invention may be implemented in the form of hardware, software, or a combination of hardware and software.

When implemented in software, a computer-readable storage medium storing one or more programs (software modules) may be provided. One or more programs stored in the computer-readable storage medium are configured to be executable by one or more processors in an electronic device (device). One or more programs include instructions for causing an electronic device to execute methods according to embodiments described in a claim or specification of the present invention.

Such programs (software modules, software) include random access memory, non-volatile memory including flash memory, read only memory (ROM), electrically erasable programmable ROM (EEPROM: Electrically Erasable Programmable Read Only Memory), magnetic disc storage device, Compact Disc-ROM (CD-ROM), Digital Versatile Discs (DVDs), or any other form of It may be stored in an optical storage device or a magnetic cassette. Alternatively, it may be stored in a memory composed of a combination of some or all thereof. In addition, each configuration memory may be included in plurality.

In addition, the program is transmitted through a communication network consisting of a communication network such as the Internet, Intranet, Local Area Network (LAN), Wide LAN (WLAN), or Storage Area Network (SAN), or a combination thereof. It may be stored on an attachable storage device that can be accessed. Such a storage device may be connected to a device implementing an embodiment of the present invention through an external port. In addition, a separate storage device on the communication network may be connected to the device performing the embodiment of the present invention.

In the specific embodiments of the present invention described above, elements included in the invention are expressed in the singular or plural according to the specific embodiments presented. However, the singular or plural expression is appropriately selected for the context presented for convenience of description, and the present invention is not limited to the singular or plural element, and even if the element is expressed in plural, it is composed of the singular or singular. Even an expressed component may be composed of a plurality of components.

Meanwhile, although specific embodiments have been described in the detailed description of the present invention, various modifications are possible without departing from the scope of the present invention. Therefore, the scope of the present invention should not be limited to the described embodiments and should be defined by the claims described below as well as the claims and equivalents.

Claims (28)

A method of operating a base station in a wireless communication system, the method comprising:
A process of measuring instantaneous channel parameters collected at a plurality of time points using a signal received from a terminal;
determining a first signal to noise ratio (SNR) and a first channel covariance, which are first long-term channel information of the terminal, from the instantaneous channel parameters;
transmitting the first long-term channel information for the terminal to another base station;
receiving, from the other base station, a second SNR and a second channel covariance, which are second long-term channel information for a terminal accessing the other base station;
Power of a desired signal determined based on the first SNR, the second SNR, the first channel covariance, and the second channel covariance, a power normalization term, and leakage interference ), a process of determining a leak coefficient indicating a rate at which a transmission signal to the terminal acts as interference to at least one other terminal;
The amount of change in the first SNR exceeds the threshold of the first SNR, the amount of change in the second SNR exceeds the threshold of the second SNR, or the amount of change in the first channel covariance exceeds the threshold of the first channel covariance, or If the amount of change of the second channel covariance exceeds the threshold of the second channel covariance,
updating the determined leak coefficient by selecting a leak coefficient corresponding to the first long-term channel information and the second long-term channel information from a table defining a leak coefficient corresponding to the predefined long-term channel information;
determining a beamforming vector based on the updated leak coefficient;
The process of determining a virtual signal to interference plus noise ratio (VSINR) with the beamforming vector;
and transmitting a beamformed signal based on the VSINR.
delete According to claim 1,
The method further comprising the step of determining the first long-term channel information based on the instantaneous channel information fed back from the terminal.
delete According to claim 1,
When the first long-term channel information is fed back from the terminal, the method further comprising the step of determining that the amount of change in the first SNR and the amount of change in the first channel covariance exceed threshold values.
delete delete delete According to claim 1,
The process of determining the leak coefficient is,
and determining the leakage coefficient based on the first long-term channel information, the number of antennas, and the number of terminals.
delete delete delete delete delete In a base station apparatus in a wireless communication system,
controller; and
including a transmitter;
The controller measures instantaneous channel parameters collected at a plurality of time points using a signal received from the terminal,
Determining a first signal to noise ratio (SNR) and a first channel covariance that are first long-term channel information of the terminal from the instantaneous channel parameters,
Transmitting the first long-term channel information for the terminal to another base station,
receiving, from the other base station, a second SNR and a second channel covariance, which are second long-term channel information for a terminal accessing the other base station,
Power of a desired signal determined based on the first SNR, the second SNR, the first channel covariance, and the second channel covariance, a power normalization term, and leakage interference Based on the power of ), a leak coefficient indicating a rate at which a transmission signal to the terminal acts as interference to at least one other terminal is determined,
The amount of change in the first SNR exceeds the threshold of the first SNR, the amount of change in the second SNR exceeds the threshold of the second SNR, or the amount of change in the first channel covariance exceeds the threshold of the first channel covariance, or When the amount of change of the second channel covariance exceeds the threshold value of the second channel covariance, the first long-term channel information and the second selecting a leak coefficient corresponding to the long-term channel information and updating the determined leak coefficient;
determining a beamforming vector based on the updated leak coefficient;
Determining a virtual signal to interference plus noise ratio (VSINR) with the beamforming vector,
The transmitter is an apparatus for transmitting a beamformed signal based on the VSINR.
delete 16. The method of claim 15,
The controller is
An apparatus for determining the first long-term channel information based on the instantaneous channel information fed back from the terminal.
delete 16. The method of claim 15,
The controller is
When the first long-term channel information is fed back from the terminal, the apparatus for determining that the amount of change in the first SNR and the amount of change in the first channel covariance exceed threshold values.
delete delete delete 16. The method of claim 15,
The controller is
An apparatus for determining the leakage coefficient based on the first long-term channel information, the number of antennas, and the number of terminals. delete delete delete delete delete

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