KR101084780B1 - Method for high rate and low complex user scheduling using interference alignment in multi-antenna multi-transmitter multi-receiver wireless network - Google Patents

Abstract

The present invention relates to a low complexity scheduling method using interference alignment in a multi-antenna multiple transceiver wireless network, to obtain a high transmission rate and a maximum degree of freedom (DOF) using an interference alignment preprocessor, and to schedule a receiver with a low complexity calculation amount. It is intended to provide a low complexity scheduling method.

To this end, the present invention provides a method for scheduling a receiver, comprising: estimating each channel value; Calculating an angle between the signal stream and the interference stream using the estimated channel value; A scheduling step of sequentially selecting receivers to be scheduled one by one based on the angle between the obtained signal stream and the interference stream; And calculating a beamforming matrix using an iterative interference alignment algorithm for each of the selected receivers.

Select wireless network, low complexity scheduling, channel value estimation, interference alignment, angle calculation, receiver one by one

Description

Method for high rate and low complex user scheduling using interference alignment in multi-antenna multi-transmitter multi-receiver wireless network

The present invention relates to a scheduling method for scheduling a receiver in a multi-antenna multi-transceiver wireless network environment. More particularly, the present invention relates to a method for guaranteeing maximum spatial multiplexing gain and a throughput gain in a wireless network in which a plurality of transceivers interfere with each other. A low complexity scheduling method.

In general, there are several user assignment schemes for wireless network systems.

In a mobile communication system, frequencies are reused in order not to cause severe interference to cell edge users. If the frequency is used in common, the user is selected to have less interference in consideration of neighboring cells. In this case, the user may be selected by considering only one cell, or the user may be selected by considering a plurality of cells at once.

When the user is selected by considering only one cell, the inter-cell interference model is selected under the assumption that the interference signal is constantly coming in as an average amount, or the amount of the interference signal is selected to be less than the predetermined amount.

When a user is selected in consideration of a plurality of cells, a single cell is processed under the assumption that all necessary information can be exchanged using a wired backhaul between base stations instead of an intercell interference model.

On the other hand, there are also various types of selection algorithms used for user selection. There is a method of selecting one user to have a good performance, or a method of calculating and selecting a combination of all users.

In addition, there are various kinds of scheduling formulas. As a method of selecting a user who maximizes the amount by defining an appropriate function, there is a method of maximizing a transmission amount or maximizing fairness.

However, these transmission maximization methods or fairness maximization schemes do not consider the degree of freedom (DoF), so there is a problem in that the throughput is not increased any more in the high SNR region or the presence of a large capacity backhaul is essential. .

Recently proposed beamforming matrix is designed to use the same vector space between interference signals of different receivers in designing the beamforming matrix in multi-antenna interference channel. In the high SNR region, the transmission amount is continuously increased. Specifically, in an interference channel in which the channel is composed of three transceiver pairs, all of which are exactly known to each transmitter, the received signal of the i-th receiver is given by Equation 1 below.

는 j번째 송신기와 i번째 수신기 사이의 점대점 채널 행렬을 의미하고,

는 i번째 송신기의 빔형성 행렬,

는 i번째 송신기가 보내는 데이터 심볼을 의미한다. 간섭정렬은 수신 신호 중에서 수신 신호와 간섭이 서로 다른 벡터공간을 갖도록 송신 빔형성 행렬을 설계하는 방법으로, 하기의 [수학식 2]로 주어진다.Here, the right side of Equation 1 is composed of a signal, interference, and complex normal distribution noise.

Denotes a point-to-point channel matrix between the j th transmitter and the i th receiver,

Is the beamforming matrix of the i th transmitter,

Denotes a data symbol sent by the i th transmitter. The interference alignment is a method of designing a transmission beamforming matrix such that the received signal and the interference have different vector spaces among the received signals, and are given by Equation 2 below.

은 열 벡터공간을 의미한다. 상기 [수학식 2]를 만족하는 경우에는, 수신기에서 간단한 선형 필터링을 통해 간섭 없는 신호를 복호할 수 있다.At this time,

Means column vector space. If Equation 2 is satisfied, the receiver can decode the signal without interference through simple linear filtering.

However, this conventional method has a problem in that it can not be applied other than the interference channel because of the limitation on the number of receivers.

As described above, such prior arts do not take into account DoF so that the amount of transmission no longer increases in the high SNR region, or the presence of a large amount of backhaul is necessary, or the number of receivers Since there is a limitation, there is a problem that cannot be applied other than an interference channel, and it is a problem of the present invention to solve such a problem.

Accordingly, an object of the present invention is to provide a low complexity scheduling method for obtaining a high transmission amount and a maximum DoF using an interference alignment preprocessor, and scheduling a receiver with a low complexity calculation amount.

That is, an object of the present invention is to provide a low complexity scheduling method that guarantees the maximum DoF while increasing the throughput with low complexity through a simple scheduling method that reduces the complexity of the receiver scheduling scheme for maximizing the total throughput.

The objects of the present invention are not limited to the above-mentioned objects, and other objects and advantages of the present invention which are not mentioned can be understood by the following description, and will be more clearly understood by the embodiments of the present invention. Also, it will be readily appreciated that the objects and advantages of the present invention may be realized by the means and combinations thereof indicated in the claims.

The method of the present invention for achieving the above object comprises the steps of: estimating each channel value; Calculating an angle between the signal stream and the interference stream using the estimated channel value; A scheduling step of sequentially selecting receivers to be scheduled one by one based on the angle between the obtained signal stream and the interference stream; And calculating a beamforming matrix using an iterative interference alignment algorithm for each of the selected receivers.

As described above, the present invention can obtain a high transmission amount and a maximum DoF through linear interference alignment using only channels of the transceivers, and also has the effect of scheduling a receiver with a low complexity calculation amount.

BRIEF DESCRIPTION OF THE DRAWINGS The above and other objects, features and advantages of the present invention will become more apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings, It can be easily carried out. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

In the specification, when a part is "connected" to another part, this includes not only a "directly connected" but also a "electrically connected" between other elements in between. In addition, when a part is said to "include" or "include" a certain component, it means that it may further include or have other components, without excluding other components, unless specifically stated otherwise. .

First, the concept of interference alignment will be described in order to help the understanding of the present invention.

1 is a view for explaining the concept of interference alignment, Figures 2a and 2b is a view showing a projection principle of a linear receiver.

The interference alignment is a transmitter algorithm for reducing the influence of interference in a multi-antenna multi-transceiver interference channel. The interference alignment is a method of decoding a simple linear receiver by inserting an interference signal from another transmitter into the same vector space through transmission beamforming. To this end, all transmitters must share the channel values of all radio links and calculate the beamforming matrix for interference alignment. For the description of the interference alignment, it is assumed that the transmitter and the receiver each have two antennas, and each transmitter transmits one stream toward each receiver.

Each dotted line shown in FIG. 1 represents a wireless point-to-point channel. When each transmitter carries one stream on a beam, the direction and size of the beam change while passing through a radio channel. Accordingly, each receiver receives a total of three beams, one of which is a signal stream, and the other two beams are interference streams. Here, if the transmitter calculates and transmits the interference stream to be aligned when the beam is formed at the transmitter, since the receiver 2 streams 2 and 3 face the same direction as the interference stream when decoding the signal stream 1 received from the transmitter, The linear projection reception method can be used to decode signal stream 1 without the influence of interference.

This interference alignment requires each transmitter to know the channel values of all radio links through feedback, and can transmit up to two signal streams simultaneously for 2 x 2 channels where no interference exists. Therefore, the number of signal streams should be reduced, such as only one stream should be transmitted.

In a wireless network environment where K transceiver pairs and all transceivers have M antennas, the received signal at the i th receiver is expressed by Equation 3 below.

는 j번째 송신기와 i번째 수신기 간의 점대점 채널 행렬이며 그 크기는 M x M이고, 레일리 페이딩 계수를 원소로 갖는다. 여기서,

는 j번째 송신기의 전처리기 행렬(빔형성 행렬)을 나타내며, M x d의 크기를 가진다. 여기서,

는 j번째 송신기가 보내고자 하는 데이터 심볼로서 d x 1 벡터이다. 상기 [수학식 3]의 첫 번째 항은 신호 스트림이고, 두 번째 항은 간섭 스트림이며, 세 번째 항은 원형 대칭 복소 백색 정규 잡음 M x 1 벡터이다.here,

Is a point-to-point channel matrix between the j th transmitter and the i th receiver, the size of which is M × M, and has Rayleigh fading coefficients as elements. here,

Denotes a preprocessor matrix (beamforming matrix) of the j th transmitter and has a size of M xd. here,

Is the data symbol that the j th transmitter wants to send and is a dx 1 vector. The first term of Equation 3 is a signal stream, the second term is an interference stream, and the third term is a circular symmetric complex white normal noise M x 1 vector.

At this time, the condition of the interference alignment can be expressed by Equation 4 below.

는 열 벡터공간을 의미한다. 각 간섭 스트림이 형성하는 열 벡터공간이 일치하기 때문에, 수신 신호

를 도 2a 및 도 2b에 도시된 바와 같이 간섭 스트림과 수직인 방향으로 선형 투영하면, 간섭 스트림의 영향이 전혀 없이 신호 스트림을 복호할 수 있다.here,

Means column vector space. Received signal because the column vector space formed by each interference stream coincides

Is linearly projected in a direction perpendicular to the interference stream as shown in Figs. 2A and 2B, it is possible to decode the signal stream without any influence of the interference stream.

을 계산한다.A beamforming method that satisfies Equation 4 has already been published in the paper [Cadambe and Jafar, Interference alignment and degrees of freedom of the K user interference channel, IEEE Transactions on information theory, Aug 2008]. In the case where the transmitter controller has the channel values of all the links correctly, when K = 3 and M is odd, the unitary beamforming matrix which is a sufficient condition of Equation 5 below instead of Equation 4 above.

.

The beamforming matrix that satisfies Equation 5 is given by Equation 6 below.

는 i번째 정규 기저이다.Of Equation 6 above

Is the i th regular basis.

If K = 3 and M is odd, two time symbols are bundled and used as one symbol. At this time, two channel values are also used as one large matrix below.

는 2M x 2M인 블록 대각행렬이 되어, 짝수개의 안테나를 가진 경우와 동일한 방식으로 2M x M 빔형성 행렬

이 하기의 [수학식 7]로 주어진다.Thus the channel

Becomes a block diagonal matrix of 2M x 2M, and the 2M x M beamforming matrix is performed in the same manner as with an even number of antennas.

This is given by Equation 7 below.

An iterative interference alignment algorithm to guarantee Equation 4 has also been proposed [Gomadam, Cadambe, and Jafar, Approaching the capacity of wireless networks through distributed interference alignment, preprint]. In the case where the transmitter controller has exactly the channel values of all links, the iterative interference alignment algorithm designs the transmit beamforming matrix and the receive beamforming matrix simultaneously. In this case, the requirement of the interference alignment is expressed by Equation 8 below for all transmitters k.

는 k번째 송신기의

유니타리 빔형성 행렬,

는 k번째 수신기의

유니타리 빔형성 행렬,

는 k번째 송신기가 보내는 신호 스트림의 개수,

는 켤레 전치 연산자이다.here,

Is the kth transmitter

Unitary beamforming matrix,

Is the kth receiver

Unitary beamforming matrix,

Is the number of signal streams sent by the kth transmitter,

Is the conjugate transposition operator.

3 is a flow diagram of one embodiment of an iterative interference alignment algorithm.

Here, the iterative interference alignment algorithm determines the beamforming matrix by calculating according to the processing shown in FIG. 3 in the transmitter controller. At this time, since the iterative interference alignment algorithm is a known technique, only the gist will be briefly described.

를 임의로 생성한다.First, in the "301" process, the beamforming matrix at each transmitter j

Generates randomly.

In step 302, an iterative interference alignment algorithm is started.

와 신호 스트림 개수

에 대해서 간섭 분산 행렬을 계산한다. 여기서,

는 j번째 송신기에서 i번째 수신기로의 채널로서, M x M 행렬로 표시한다.Then, in step 303, the power of each transmitter is

And number of signal streams

Compute the interference variance matrix for. here,

Is a channel from the j th transmitter to the i th receiver, denoted by an M x M matrix.

를 결정한다.Subsequently, in the “304” process, the d th eigenvector of the interference variance matrix calculated in the “303” process is used as the d th vector of the reception beamforming matrix of the k th receiver.

.

와

를 다시 정의한 후에 상기 "303" 과정과 "304" 과정에서 수행한 계산을 "306" 과정, "307" 과정, 및 "308" 과정을 통하여 반복 수행한다.After that, in the "305" process

Wow

After redefining, the calculations performed in steps "303" and "304" are repeatedly performed through steps "306", "307", and "308".

와 상기 "302" 과정에서 이미 가지고 있던

의 차이가 거의 없어서 미리 정한 임계치 이내의 오차를 보이면 반복 간섭정렬 알고리즘은 종료한다. 만일, 그렇지 않은 경우

를 갱신하고 상기 "302" 과정으로 진행하여 반복 수행한다.Then, obtained through the "308" process

And the "302" process already had

If there is almost no difference and shows an error within a predetermined threshold, the iterative interference alignment algorithm ends. If not

Is updated and the process proceeds repeatedly to step "302".

A modified iterative interference alignment algorithm (beamforming algorithm), which is a beamforming algorithm similar to the iterative interference alignment algorithm (beamforming algorithm) described with reference to FIG. 3 and shows a higher transmission amount, has also been proposed in the same paper. In the modified beamforming algorithm, the equations of the "303" process and the "304" process shown in FIG. 3 are modified to the following Equations 9 and 10, and the "306" shown in FIG. Modify the formulas in steps "307" and "307" in the same way.

는 j번째 송신 빔형성 행렬의 d번째 벡터이다.In [Equation 9] and [Equation 10]

Is the d-th vector of the j th transmit beamforming matrix.

Next, the present invention will be described in detail with reference to FIGS. 4 to 7.

4 is a diagram illustrating an embodiment of a multi-antenna multiple transceiver wireless network to which the present invention is applied.

As shown in FIG. 4, a multi-antenna multi-user downlink having a frequency reuse factor of 1 is considered.

At this time, the transmitter controller (eg femtocell controller) manages K = 3 transmitters (eg femtocell), and each transmitter manages L receivers (user terminals) in total. At this time, the transmitter controller receives the channel value of each radio link from the receiver and schedules the receiver through a scheduling formula. In this case, the beamforming matrix for the scheduled receiver may be executed by the transmitter controller or the transmitter. The calculation of the beamforming matrix is performed by the iterative interference alignment algorithm (beamforming algorithm) of FIG. 3 described above or the iterative interference alignment algorithm (beamforming algorithm) modified from the iterative interference alignment algorithm (beamforming algorithm) of FIG. 3 to maximize the amount of transmission. ). In this case, one transmitter should select one receiver to transmit data.

Here, it is assumed that the transmitter and the receiver have M = 2 antennas for convenience. Also assume that all transmitters send d = 1 signal streams. Here, the point-to-point channel is assumed to be a 2 x 2 matrix assuming a frequency flat channel, and channel estimation and signal synchronization are assumed to be perfect.

5 is a flowchart illustrating a low complexity scheduling method using interference alignment in a multi-antenna multiple transceiver wireless network according to the present invention.

First, when each receiver feeds back a channel value to each corresponding transmitter (501), each transmitter processes the channel value from the corresponding receiver to estimate the required channel value (502).

번째 송신기가 추정하는 채널은

이다.In case of time division duplex communication, the receiver uses a predefined sounding channel in uplink, so that each transmitter can estimate both the signal and the interference channel coming from each receiver. In the case of frequency division duplex communication, the receiver encodes a channel value through a predefined channel according to a predefined modulation scheme so that the transmitter can decode it. At this time,

Channel estimated by the first transmitter

to be.

의 모든 채널 행렬을 전달받는다.Each transmitter then forwards the estimated channel value to the transmitter controller via a wired backhaul (503). So the transmitter controller

All channel matrices of are passed.

On the other hand, the transmitter controller selects K = 3 receivers among the L receivers that maximize the scheduling formula calculation based on linear interference alignment, using the channel values received from each transmitter. In this case, a receiver that best satisfies a sufficient condition of the interference alignment beamforming matrix is selected to maximize the sum transmission amount. Looking at this in more detail as follows.

For example, since the receiver uses a linear projection scheme, the amount of transmission is related to the size of the signal stream after linear projection. As described above, FIGS. 2A and 2B illustrate a linear projection method after interference alignment. In order to decode the signal stream 1, the linear projection direction considers a vector space in a direction perpendicular to the interference stream 1, and projects the signal stream 1 into the vector space. FIG. 2A shows a case where the size of the signal stream 1 becomes smaller after the linear projection of the signal stream 1, and FIG. 2B shows a case where the size of the signal stream 2 'is almost preserved even after the signal stream 2 is linearly projected. The difference between the two cases is determined by the angle between the signal stream and the interference stream. Therefore, the receiver selection condition for maximizing the total transmission amount of the receiver scheduling requires a condition that the signal stream determined by the beamforming matrix obtained by the interference alignment and the interference stream aligned with the maximum are 90 degrees. In this case, when two or more signal streams are transmitted, an angle between complex vector spaces is calculated as shown in Equation 11 below.

는 d번째로 큰 특이값(여기서 특이값은 선형 투영된 후에 신호 스트림의 크기),

은

을 QR 분해한 후의 유니타리 정방 행렬 부분,

는 켤레 전치 연산자,

는

을 QR 분해한 후의 유니타리 정방 행렬 부분이다. 상기 [수학식 11]을 이용하여 얻은

값이 0에 가까울수록, 간섭정렬 이후에 얻을 전송량이 큰 성질을 가진다.Where d is the number of streams transmitted by each transmitter,

Is the d-th largest singular value (where the singular value is the size of the signal stream after linear projection),

silver

Unitary square matrix portion after QR decomposition,

Is the conjugate transposition operator,

Is

This is the unitary square matrix after QR decomposition. Obtained using Equation 11

The closer the value is to 0, the larger the amount of transmission to be obtained after interference alignment.

의 값, 즉 상기 추정한 채널 값을 이용하여 신호 스트림과 간섭 스트림 간의 각도를 구한다(504). 특히,

는 선형 투영 후에 나타나는 신호 스트림의 크기를 나타내는 척도로 사용한다.

는 k번째 송신기에서 (k)번째 수신기로의 채널 행렬의 l번째 큰 특이값을 나타낸다. 여기서, (i)번째 수신기는 i번째 송신기가 선택한 수신기를 나타낸다.At this time, given by Equation 11

The angle between the signal stream and the interference stream is calculated using the value of, i.e., the estimated channel value (504). Especially,

Is used as a measure of the magnitude of the signal stream appearing after linear projection.

Denotes the l th largest singular value of the channel matrix from the k th transmitter to the (k) th receiver. Here, the (i) th receiver indicates a receiver selected by the ith transmitter.

으로서, 수신기의 수 L이 아주 큰 경우에는 모든 경우의 수에 대해 상기 [수학식 11]을 계산할 수 없다. 그러므로 본 발명에서는, 수신기 L개 중에서 K개의 수신기로 이루어진 하나의 수신기 군을 형성하는 방법 대신에, 상기 구한 신호 스트림과 간섭 스트림 간의 각도를 기반으로 스케줄링할 수신기를 순차적으로 1개씩 선택하는 방식을 사용한다(505). k+1번째 선택하는 수신기는 이미 선택된 (1),(2),...,(k) 수신기들과 최대한 간섭정렬 후 얻는 합전송량이 클 수 있도록 선택한다. 이 선택의 기준은 상기 [수학식 11]에 기반한 하기의 스케쥴링 공식인 [수학식 12]로 정한다.As described above, in order to perform receiver scheduling, Equation 11 needs to be calculated for a receiver group formed by selecting K of L receivers. Where all possible cases are

For example, when the number L of receivers is very large, Equation 11 cannot be calculated for all cases. Therefore, in the present invention, instead of forming a receiver group consisting of K receivers out of L receivers, a method of sequentially selecting one receiver to be scheduled one by one based on the angle between the obtained signal stream and the interference stream is used. (505). The k + 1st selecting receiver selects such that the sum transmission obtained after the maximum interference alignment with the already selected (1), (2), ..., (k) receivers can be large. The selection criteria are defined by Equation 12, which is the following scheduling formula based on Equation 11 above.

로 L에 대해 선형적으로 복잡도가 증가하기 때문에, L의 지수로 복잡도가 증가하는 가능한 모든 경우를 고려하는 방식보다 복잡도가 크게 감소한다.At this time, the number of cases to be considered while selecting one receiver sequentially

Since the complexity increases linearly with respect to L, the complexity is significantly reduced compared to the case where all possible cases of increasing complexity with the exponent of L are considered.

On the other hand, the receiver scheduling formula is, for example, to determine the receivers (1), (2), (K = 3), the following Equation 13 based on Equation 11 and Equation 12 Use

는 k번째 송신기에서 (k)번째 수신기로의 점대점 채널의 특이값 분해 결과의 l번째 값을 나타낸다.

는 k번째 고려하는 수신기에서의 신호 벡터공간과 정렬된 간섭 벡터공간이 이루는 각도를 의미한다.Here, P means power of the transmitter, d means the number of data streams sent by the transmitter.

Denotes the lth value of the singular value decomposition result of the point-to-point channel from the kth transmitter to the (k) th receiver.

Denotes the angle formed by the interference vector space aligned with the signal vector space in the k-th receiver.

After repeating the process "504" and "505" to determine both the transmitter and the receiver to be scheduled by each transmitter (506), the downlink channel can be viewed as an interference channel, and thus the beam for each receiver The formation matrix is calculated using the iterative interference alignment algorithm (beamforming algorithm) of FIG. 3 or the iterative interference alignment algorithm (beamforming algorithm) which is modified from the iterative interference alignment algorithm (beamforming algorithm) of FIG. 3 to maximize the amount of transmission. (507).

As described above, after the transmitter controller schedules the receiver and calculates the beamforming matrix, the transmitter controller transmits the scheduled receiver and data to be transmitted to each transmitter.

Each transmitter then communicates with the scheduled receiver based on the given data and beamforming matrix.

All of the aforementioned scheduling and beamforming matrix calculations may occur at the transmitter controller, or may be calculated at each transmitter when each transmitter receives channel values of another link through the wired backhaul without the transmitter controller. In addition, although the example was given about the case of K = 3, the method of this invention is applicable also to the case of K> 3.

Next, the performance of the present invention will be described with reference to FIGS. 6 and 7 as compared with other methods.

FIG. 6 is a performance comparison graph when receivers are distributed at SNR = 5dB, and FIG. 7 is a performance comparison graph when receivers are distributed at SNR = 10dB.

In order to verify the performance of the receiver selection method according to the present invention, it is assumed a multi-antenna multiple transceiver wireless network as shown in FIG. K = 3 transmitters that reuse frequency select K receivers out of L receivers. In this case, it is assumed that cooperative communication between transmitters is not assumed, and that each transmitter is connected by wired backhaul so that the channel feedback value of the receiver can be shared with different transmitters without errors and delays. Since the receivers all have the same spatial distribution, it is assumed that the average signal-to-noise ratio (SNR) is constant at 5 dB and 10 dB, respectively. It is assumed that both the transmitter and the receiver have two antennas.

The scheme of the present invention follows the scheme described above and compares the sum of transmissions with the two existing systems. The first method is to select a receiver combination that maximizes the sum of transmissions obtained by calculating both interference alignment and beamforming matrix for all receiver combinations. This first method examines all L (L-1) (L-2) types. Second, one receiver combination is randomly selected regardless of the channel value to maximize receiver fairness.

After selecting the receiver combination, the interference alignment beamforming method used the algorithm of FIG. 3 modified based on Equation 9 and Equation 10. FIG.

The x-axis of the graph shows the number of receivers that can be selected by three transmitters, and the y-axis shows the average sum of transmissions in bit / sec / Hz. The curves in FIGS. 5 and 6 are the performance of the first comparison system, and the + curve is the performance of the second comparison system. The scheme of the present invention is represented by o curve.

When the receivers are distributed at SNR = 5 dB (see Fig. 6), the performance of the present invention when the transmitter has three receivers on average is 11.9% compared to the first comparison system, and 30.6% compared to the second comparison system. There was a traffic improvement.

In case the receivers are distributed at SNR = 10dB (see Fig. 7), the performance of the present invention when the transmitter has three receivers on average is 13.5% compared to the first comparison system, and 21.8% compared to the second comparison system. There was a traffic improvement.

In the case of the first system, it can be seen that the optimal combination is found, and thus the maximum multi-user diversification gain as well as the sum transmission amount.

On the other hand, the method of the present invention as described above can be written in a computer program. And the code and code segments constituting the program can be easily inferred by a computer programmer in the art. In addition, the written program is stored in a computer-readable recording medium (information storage medium), and read and executed by a computer to implement the method of the present invention. The recording medium may include any type of computer readable recording medium.

The present invention described above is capable of various substitutions, modifications, and changes without departing from the technical spirit of the present invention for those skilled in the art to which the present invention pertains. It is not limited by the drawings.

The present invention can be used for receiver scheduling in a multi-antenna multi-transceiver wireless network environment.

1 is a view for explaining the concept of interference alignment,

2a and 2b show the projection principle of a linear receiver,

3 is a flow diagram of an embodiment of an iterative interference alignment algorithm;

4 is a configuration diagram of an embodiment of a multi-antenna multiple transceiver wireless network to which the present invention is applied;

5 is a flowchart illustrating a low complexity scheduling method using interference alignment in a multi-antenna multiple transceiver wireless network according to the present invention;

6 is a performance comparison graph when receivers are distributed at SNR = 5 dB,

7 is a performance comparison graph when receivers are distributed at SNR = 10 dB.

Claims (5)

In the method of scheduling a receiver, Estimating each channel value; Calculating an angle between the signal stream and the interference stream using the estimated channel value; A scheduling step of sequentially selecting receivers to be scheduled one by one based on the angle between the obtained signal stream and the interference stream; And Computing a beamforming matrix using an iterative interference alignment algorithm for each of the selected receivers Low complexity scheduling method comprising a. The method of claim 1, The scheduling step, And selecting a receiver having a vertical angle between the obtained signal stream and the interference stream. The method of claim 2, The scheduling step, A low complexity scheduling method for selecting a receiver having the largest size of a signal stream after linear projection. The method according to any one of claims 1 to 3, The scheduling step, Low complexity scheduling method for selecting the receiver to be sequentially selected one by one according to Equation A below. Equation A

(Where P is the power of the transmitter, d is the number of data streams the transmitter sends,

Denotes the l-th value of the singular value decomposition of the point-to-point channel from the kth transmitter to the (k) th receiver,

Denotes the angle formed by the interference vector space aligned with the signal vector space of the receiver under consideration in the kth consideration, and L denotes the number of receivers.) The method of claim 4, wherein The angle calculation step, A low complexity scheduling method for obtaining an angle between a signal stream and an interference stream according to Equation B below. Equation B

(Where d is the number of streams transmitted by each transmitter,

Is the d largest singular value,

silver

Unitary square matrix portion after QR decomposition,

Is the conjugate transposition operator,

Is

Is part of the Unitary square matrix after QR decomposition.)

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