KR101769715B1 - Improved tabu search method for receiver's operation reduction in mimo system and mimo receiver using its method - Google Patents

Abstract

The present invention relates to a Tabu search method employing grid reduction. The method, to obtain an optimal value for a MIMO receiver in a MIMO system of a wireless communication network, includes: a step of setting an initial value by applying a grid reduction technique to the Tabu search method; a step of presetting the number of times for repetition; and a step of terminating search algorithm for exploring for a value by assuming that the optimal value is found when exploration for the value is performed as many times as the maximum repeating number. According to the present invention, the method is capable of making efficient the performance of an existing Tabu search type receiver so that the receiver becomes suitable for a large-scale multi-antenna system.

Description

Technical Field [0001] The present invention relates to an improved tone search method for reducing a calculation amount of a receiver in a MIMO system, and a MIMO receiver using the method. [0002]

The present invention relates to a method for searching for a received signal in the field of wireless communication, and more particularly, to a table searching method using grid reduction for reducing a calculation amount of a receiver in a MIMO system and a MIMO receiver using the method.

 Cooperative communication technologies between base stations can be used not only to mitigate the effects of interference signals but also to increase the communication capacity and to increase the communication capacity by using a large number of virtual transmission antennas through cooperation between the base stations while maintaining the number of antennas per existing base station Can be expected.

However, since the conventional cooperative communication method is optimized based on a general cellular network, it is necessary to develop a cooperative communication technology suitable for a railway wireless network environment in which the number of terminals is relatively small, the interval between the base stations is narrow, and intercell interference is low.

Meanwhile, when cooperative communication is used for the downlink of the railway radio network to improve the transmission speed, the antennas of the various base stations form a multi-transmission antenna, and a receiving antenna and a multiple-input multiple-output (MIMO) . Accordingly, a MIMO transmission mode in which a plurality of symbols are simultaneously transmitted using a plurality of transmit antennas to achieve a high transmission rate is used.

The MIMO system collectively refers to any system that receives signals transmitted from one or more antennas at a transmitter to one or more antennas at a receiver.

In the MIMO transmission mode based on the cooperative communication, the number of symbols transmitted at the same time increases by using more transmission antennas as compared with the case of using only a single base station, and the transmission efficiency is greatly influenced by the reception system.

개의 송신안테나와

개의 수신안테나로 구성된 경우를 고려한다면 다음과 같은 수학식 1의 수신 모델을 얻을 수 있다.FIG. 1 is a conceptual diagram of a MIMO system. As shown in FIG. 1, a MIMO system

≪ / RTI >

The reception model of Equation (1) can be obtained as follows.

[Equation 1]

는

복소 페이딩 채널 행렬을 의미하고,

는 평균이 0이고 분산이

인 가우시안 확률변수들로 구성된 잡음 벡터를 의미하며,

와

는 각각

수신 신호 벡터 및

송신 신호 벡터를 나타낸다. In Equation (1)

The

Denotes a complex fading channel matrix,

The average is 0 and the variance is

And a noise vector composed of Gaussian random variables,

Wow

Respectively

The received signal vector and

Represents a transmission signal vector.

When ML (Maximum Likelihood) reception technique is applied to the above reception signal model, it is equivalent to solving the Least-Squares Method problem, and the optimal solution is expressed by the following equation (2).

&Quot; (2) "

 The function minimized on the right side of Equation (2) represents the ML cost function. Since it is necessary to calculate all the candidate vectors for the optimal performance, an excessive amount of calculation is required to obtain an optimal solution. This becomes difficult.

 Such a problem can be solved by a near optimal reception method such as sphere decoding or Tabu Search.

 As shown in FIG. 2, sphere decoding is a method of generating a sphere having the same cost function value in a space made up of symbol vectors and comparing the cost function values of symbol vectors located in the sphere, thereby significantly reducing the average calculation amount of the ML receiver have.

In addition, the Tabu search method is a receiving method capable of achieving performance similar to that of the ML receiver, like the sphere decoding.

The Tabu search calculates the ML cost function value of the adjacent candidate solutions based on the estimated initial solution as shown in FIG. 3, selects the candidate solution corresponding to the smallest of the calculated cost function values, (Tabu List) to prevent the movement of the corresponding year.

If the value of the ML cost function of the selected candidate solution is larger than the cost function value of the optimal solution up to the present time obtained by the previous search process, the movement to this candidate solution Allow.

For the choice of the final solution, the cost function of the candidate solutions included in the table list is compared to select the solution with the most optimal value.

및 반복 수행 횟수

을 고정한 상태에서, 인접한 후보 해들이 모두 타부 리스트에 포함되어 있을 경우 타부 리스트에 가장 오랫동안 포함되었던 후보 해부터 하나씩 해제하는데, 이와 같은 과정을 통해 전체 반복 수행만큼 실행 후 알고리즘을 종료한다.The most basic form of the Tabu search reception method is a fixed Tabu Search method as shown in FIG. 4, and the length of the Tabu list

And the number of iterations

If all of the candidate solutions are included in the target list, one of the candidates included in the target list for the longest time is released one by one.

As described above, the receiver of the conventional fixed search method can improve the reception performance as the number of times of general iteration is increased, but the complexity of the algorithm increases.

It is necessary to find the initial solution to start the search around in the Tabu search, and the performance of the initial solution greatly affects the overall performance and complexity of Tabu search.

 In general, Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) linear receivers are used for acquisition of the initial solution, and are obtained using Equation 3 and Equation 4, respectively .

&Quot; (3) "

&Quot; (4) "

은 Moore-Penrose 의사역행렬(Pseudo-Inverse)을 나타내며,

를 만족하고,

은 행렬의 공액전치(Hermitian)를 의미하며,

는

의 크기를 갖는 단일행렬이며,

,

,

는 다음 수학식 5와 같이 정의될 수 있다.In the above equations (3) and (4)

Represents the Moore-Penrose pseudo-inverse,

Lt; / RTI >

Denotes a conjugate transpose of a matrix,

The

Lt; RTI ID = 0.0 >

,

,

Can be defined by the following equation (5).

&Quot; (5) "

,

,

,

,

와

는 모두 직교 열벡터들로 구성이 되지 않으므로, 제로-포커싱 또는 최소 평균 제곱 오차를 통해서 해를 추정할 경우 변형된 잡음의 성분

또는

가 수신 성능에 영향을 미치며, 따라서 확률적으로 최적 ML 해에서 거리가 먼 초기해가 선택된다.Generally formed channels

Wow

Are not composed of orthogonal column vectors. Therefore, when the solution is estimated through zero-focusing or minimum mean square error, the component of the distorted noise

or

And therefore an initial solution that is far from the optimal ML solution is probabilistically selected.

 For this reason, when starting the search algorithm to find the optimal solution from the initial solution obtained by the linear receiver, a large number of iterations must be performed to reach the optimal solution, which leads to an increase in the calculation amount.

Korean Patent Publication No. 10-2008-0021323 (published on Mar. 07, 2008)

In consideration of the above-described circumstances, the present invention takes into consideration the characteristics of a railway radio network, and efficiently receives signals considering complexity and signal reception performance in cooperative communication between the base stations, and applies a lattice-reduction (LR) And a MIMO receiver using the method. The present invention also provides an improved MIMO receiver for reducing the calculation amount of a receiver in a MIMO system capable of solving the problem of increasing the amount of calculation.

The technical objects of the present invention are not limited to the technical matters mentioned above, and other technical subjects not mentioned can be clearly understood by those skilled in the art from the following description.

Hereinafter, specific means for achieving the object of the present invention will be described.

A method for finding an optimal solution of a MIMO receiver in a MIMO system of a wireless communication network, the method comprising: setting an initial solution by applying a grid reduction technique to a table search method for finding an optimal solution;

The number of iterations is set in advance and the search algorithm is searched for the set number of iterations. If the number of iterations is reached, the search algorithm for searching the solution is terminated assuming that the optimal solution is found. In the MIMO system, This is accomplished by providing an improved method for searching for others.

에 격자 축소 기법을 적용하여 채널의 열벡터들을 직교에 가까운 채널 행렬(

)로 변형하여 초기해를 찾는 계산량을 줄일 수 있도록 한다.In the embodiment, at initialization, the channel matrix

And the column vectors of the channel are multiplied by the orthogonal channel matrix (

) To reduce the amount of computation for finding the initial solution.

)은 수신 신호(

)가

라는 수식을 만족할 때,

인 관계를 이용하여 하기 수학식 6을 만족하는 것을 특징으로 한다.In an embodiment, the modified channel matrix (

) ≪ / RTI >

)end

When the formula is satisfied,

The following equation (6) is satisfied.

&Quot; (6) "

인 양자화된 값을 가지는 벡터를 의미한다.)(Where T is a unimodular matrix and z is

Quot; vector ").

In the embodiment, a solution satisfying the following Equation (7) is obtained in a MIMO receiver to which a lattice reduction technique is applied by using estimated z, and a solution to the obtained solution is defined as an initial solution for applying a band search method .

&Quot; (7) "

)에 도달하기 전에 탐색 알고리즘을 종료하여 탐색 복잡도를 줄이도록 한다.In the embodiment, when performing the search algorithm, the number of repetitions of the repetitive search is set to the maximum repetition frequency

), The search algorithm is terminated to reduce the search complexity.

를 이용하여 채널 상태에 따라 가변적으로 탐색 알고리즘을 종료할 수 있다.In an embodiment, the incomplete Seysen value corresponding to the termination criterion information of the search algorithm

The search algorithm can be varied depending on the channel state.

)는 하기의 수학식 8을 만족하는 값이고,

에 대한

개의 경계값

들을 정하고 이 값들에 대응되는 탐색 알고리즘의 종료 기준에 해당하는 최대 반복 수행 횟수

을 정하여 탐색 알고리즘을 최대 반복 수행 횟수만큼 수행한다.In an embodiment, the channel state (

) Is a value that satisfies the following expression (8)

For

Border values

And the maximum number of iterations that corresponds to the termination criterion of the search algorithm corresponding to these values

And performs a search algorithm for the maximum number of iterations.

&Quot; (8) "

는 듀얼기저(Dual Basis)

의

번째 열을 의미하며,

는

를 만족하는 값이다.)(here,

Dual Base < RTI ID = 0.0 >

of

Column,

The

. ≪ / RTI >

로부터 더 이상의 성능 향상을 보이지 않는 반복 수행 횟수인

에 도달할 경우 최적의 해가 찾아진 것으로 가정하고, 탐색 알고리즘을 종료한다.In one embodiment, the solution that is the lowest cost function value among the solutions found by the search algorithm

The number of iterations that do not show any further performance improvement from

, It is assumed that an optimal solution is found, and the search algorithm is terminated.

에 대한

를 이용한다.In the embodiment, in the incomplete Seysen numerical calculation,

For

.

The MIMO receiver of the present invention is characterized by finding an optimal solution for a received signal by applying the table search method.

The present invention as described above has an effect of improving the performance of a receiver of an existing Tabu search method to be suitable for a large capacity multi-antenna system.

In addition, by improving the initial setting and early termination of the Tabu search receiver, it achieves near-optimal reception error performance compared with the conventional Tabu search method and has low complexity (3.4 dB SNR gain compared to the conventional method, 27% lower complexity ).

 As another effect, the present invention can be applied to inter-base station cooperative communication techniques, thereby achieving the effect of increasing the communication capacity.

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and, together with the description, And shall not be interpreted.
1 is a conceptual diagram of a MIMO system,
2 is a conceptual diagram of a sphere decoding applied to a conventional MIMO receiver,
3 is a conceptual diagram of a band search applied to a conventional MIMO receiver,
FIG. 4 is a flowchart of a fixed tone search applied to a conventional MIMO receiver,
FIG. 5 is a flow chart of a table search according to the initial solution setting and early search termination algorithm applied to the MIMO receiver of the present invention,
FIG. 6 is a graph showing an Empirical Cumulative Distribution Function (ECDF) graph for an 8 × 8 MIMO system according to the Tabu search method of the present invention,
FIG. 7 is a graph illustrating a bit error rate performance for a situation in which 16-QAM is applied in a 16 × 16 MIMO system by the Tabu search method of the present invention;
8 is a graph illustrating a bit error rate performance for a situation in which 16-QAM is applied in an 8x8 MIMO system by the Tabu search method of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following detailed description of the operation principle of the preferred embodiment of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may unnecessarily obscure the subject matter of the present invention.

The same reference numerals are used for portions having similar functions and functions throughout the drawings. Throughout the specification, when a part is connected to another part, it includes not only a case where it is directly connected but also a case where the other part is indirectly connected with another part in between. In addition, the inclusion of an element does not exclude other elements, but may include other elements, unless specifically stated otherwise.

Referring to FIG. 5, the third embodiment of the present invention will now be described.

에 해당하는 초기해를 구한다(S10).First, apply grid reduction

(S10). ≪ / RTI >

를

로 정한다(S12).The tabu list is initialized, the number of iterations (r) is set to 0,

To

(S12).

로 정의하고, 여기에 불완전 Seysen 수치 계산에 격자 축소가 적용된 채널(

)에 대한 채널 상태인

를 구한다(S14).The channel state for the channel matrix

, Where the incomplete Seysen channel is applied to grid scaling (

) ≪ / RTI >

(S14).

를 만족하는 최소값 n을 선택한다(S16).

Is selected (S16).

An adjacent candidate solution of the harm vector which is not included in the likelihood is searched (S18).

The optimal harmonic vector is found by considering the maximum likelihood (ML) cost function among the candidate solutions (S20).

It is determined whether the found solution is optimal (S22).

를 업데이트한다(S24).If the found solution is optimal, the number of iterations (r) is set to O,

(S24).

The current vector is updated (S26).

The previous year is moved from the tablet list (S28).

)에 도달했는지 판단한다(S30).The number of iterations is set to the maximum number of iterations

(S30).

If the maximum degree is reached in step S30, the search algorithm is terminated (S32).

If the maximum degree has not been reached in step S30, the process returns to step S18 and executes the process from the process of finding adjacent candidate solutions again.

)에 도달하였는지 판단한다(S34).On the other hand, if the solution found in step S22 is not optimal, the number of iterations r is incremented by one and the number of iterations is determined as the maximum number of iterations

(Step S34).

If the number of iterations has not reached the maximum number of iterations, the optimum algorithm is continuously searched from step S26, and the search algorithm is performed according to the set maximum number of iterations.

The tabu search method of the present invention will be described in more detail as an initialization setting step and an early search ending algorithm executing step.

< Early years  Configuration steps>

First, before the initial solution is obtained, the column vectors of the channel formed by applying the lattice reduction technique are deformed so as to be orthogonal to each other in order to solve the problem of increase in the calculation amount by the conventional table searching method.

Since the set of basis vectors for an arbitrary matrix is not unique, the grid reduction technique finds a set of different basis vectors that form the same space as the previous matrix.

와 격자 축소 기법을 적용하여 감소된 채널 행렬

의 관계는 다음 [수학식 9]과 같이 표현된다.Channel matrix

And a reduced channel matrix

Is expressed as the following equation (9).

&Quot; (9) &quot;

The received signal can be expressed as Equation (6) using the above Equation (9).

&Quot; (6) &quot;

는 유니모듈러(unimodular) 행렬이고,

인 양자화된 값을 가지는 벡터로 제로 포커싱 또는 최소 평균 제곱 오차 수신기를 통하여 추정될 수 있다. 추정된

를 이용하여 격자 축소 기법이 적용된 수신기의 해

를 다음 [수학식 7]과 같이 구한다.In Equation (6)

Is a unimodular matrix,

Lt; RTI ID = 0.0 &gt; least-squared &lt; / RTI &gt; error receiver. Estimated

Of the receiver with grid reduction technique

Is calculated as shown in the following equation (7).

&Quot; (7) &quot;

대신

의 채널 행렬에 격자 축소 기법을 적용한다.When estimating the solution using the minimum mean square error,

instead

To the channel matrix of the channel matrix.

를 전송되어진 심볼

에 대한 해로 직접 사용하는 다른 격자 축소 수신 알고리즘들과 다르게, 본 발명에서 제안된 수신기에서는

을 타부 서치 기법을 적용하기 위한 초기해로 이용한다.Estimated

Lt; RTI ID = 0.0 &gt; symbol

Unlike other grating reduction algorithms that are directly used as solutions to the above, in the receiver proposed in the present invention,

Is used as an initial solution to apply the Tabu search technique.

을 타부 서치 기법의 초기해로 이용할 경우 비교적 적은 수의 반복 수행으로도 최적의 해를 찾을 수 있게 된다.Since we applied the good channel in terms of orthogonality to find the solution of the lane using the reduction of the gap, it is located at a relatively close distance to the optimal maximum solution with a high probability,

Is used as an initial solution to the other search technique, an optimal solution can be found even with a relatively small number of iterations.

&Lt; Performing early search end algorithm >

The early search termination algorithm is basically the most commonly used termination technique when using a third-party search technique.

)를 정하고, 타부 서치 기법을

만큼 수행하는 방법이 사용된다.The early search termination algorithm uses the maximum iteration order (

), And the Tabu search technique

Is used.

로부터 성능의 향상을 가지지 않는 반복 수행 횟수를 나타내는 파라미터

을 정의하고,

이 에

도달할 경우 최적의 해가 찾아진 것으로 가정하여

이

에 도달한 시점에 알고리즘을 종료하는 방법이 사용된다.Also, the lowest cost function value among the solutions found

Lt; RTI ID = 0.0 &gt; a &lt; / RTI &gt; number of iterations to perform

Lt; / RTI &gt;

Therefore

Assuming that the optimal solution is found,

this

A method of terminating the algorithm is used.

이전에 알고리즘을 종료하여 수신기의 복잡도를 줄이는 기법을 고려한다.In the case of the algorithm proposed in the present invention,

Consider a technique to reduce the complexity of the receiver by terminating the algorithm previously.

 However, performance degradation can be caused by reducing iterative performance, and a way to maintain an optimal balance of complexity and performance is required.

In the present invention, the reference information for the early termination of the algorithm is required in order to reduce unnecessary excessive search while maintaining the performance of the MIMO receiver. To this end, the characteristics of the channel obtained through the grid reduction are used.

If the channel is in a good state (ie, the channel is near orthogonal), the initial solution is expected to be relatively close to the optimal best solution. .

Conversely, the lower the orthogonality of the channel, the lower the reliability of the initial solution, and more iterations are required to obtain the optimal solution.

In the algorithm of the Tabu search method proposed in the present invention, a channel state based on the following Equation (8) can be defined.

&Quot; (8) &quot;

는 듀얼기저(Dual Basis)

의

번째 열을 의미하며,

는 다음 수학식 10과 같이 정의된다.In Equation (8)

Dual Base &lt; RTI ID = 0.0 &gt;

of

Column,

Is defined by the following equation (10).

&Quot; (10) &quot;

를 불완전 Seysen 수치 (Incomplete Seysens Measure)로 정의하며, 실제 Seysen의 수치의 정의는 논문 [D. Wubben, D. Seethaler, J.Jalden, G. Matz, "Lattice Reduction," IEEE Signal Processing Magazine, 2011, 28(3), pp. 70-91]에서 정의된다.

Is defined as an incomplete Seysen measure, and the definition of the actual Seysen value is described in [D. Wubben, D. Seethaler, J. Jalden, G. Matz, "Lattice Reduction," IEEE Signal Processing Magazine, 2011, 28 (3), pp. 70-91.

값을 기반으로 하여 채널 상태에 가변적인 종료 기법을 제안한다.In the signal reception algorithm of the present invention

We propose a termination scheme that is variable in channel state based on the value.

단계 종료기법에서

에 대한

개의 경계값

들을 정하고 이 값들에 대응되는 조기 종료 기준 반복 수행 횟수

을 정해준다.

In the phase termination technique

For

Border values

And the number of repetitions of the early end criterion corresponding to these values

.

과

은

개의 값을 가지며 각 단계별 값들의 크기는

과

를 만족한다.

and

silver

And the size of each step value is

and

.

의 값들은 각 채널에 대한

의 경험누적함수로부터 결정된다.

The values of &lt; RTI ID = 0.0 &gt;

Lt; / RTI &gt;

에 대응되는

은 성능의 향상을 보이지 않는 반복 수행의 최대 횟수를 의미한다.

Corresponding to

Means the maximum number of iterations that do not show improvement in performance.

로부터 더 이상의 성능 향상을 보이지 않는 반복 수행 횟수가

에 도달할 경우 최적의 해가 찾아진 것으로 가정하여 알고리즘을 종료한다.That is, the lowest cost function value among the solutions found

The number of iterations that do not show any further performance improvement from

The algorithm is terminated assuming that an optimal solution is found.

이 고정되어 있지 않고 채널 상태

에 의해 결정되는 특징을 지닌다.Unlike the conventional tabu search method, in the tabu search method of the present invention,

Is not fixed and the channel status

. &Lt; / RTI &gt;

를 이용한다. 즉, 불완전 Seysen 수치 계산에 격자 축소가 적용된 채널

에 대한

를 이용한다.In the early search termination algorithm, the channel after applying the grid reduction method instead of the original channel

. In other words, the channel with grid reduction applied to the incomplete Seysen numerical calculation

For

.

값이 격자 축소 기법을 적용하지 않은 경우 보다 비교적 작은 값을 가지며, 따라서 계산량 감소의 효과를 얻는다.in this case

Value has a relatively smaller value than when the grid reduction technique is not applied, and thus the effect of reducing the calculation amount is obtained.

< Simulation  Evaluation>

To evaluate the performance of the receiver of the present invention, a simulation is performed and the performance and complexity of the receiving error rate are analyzed.

The experimental environment for the performance analysis of the proposed search method of the present invention is as follows.

■ Initial Year: ZF (zero focusing), MMSE (minimum mean square error), LR-MMSE (grid reduction - minimum mean square error)

Modulation method: 16-QAM

MIMO■

MIMO

 - Number of iterations: 300

-

-

(ET1),

(ET2) -

(ET1),

(ET2)

MIMO■

MIMO

 - Number of iterations: 250

-

-

(ET1),

(ET2) -

(ET1),

(ET2)

MIMO에 대한 ECDF의 그래프를 보여주며, 이에 따른

의 값들의 선택을 보여준다.

MIMO에도 유사한 방식으로

값들이 선택된다.6,

A graph of ECDF for MIMO is shown,

Lt; / RTI &gt;

Similar to MIMO

Values are selected.

end. Bit Error Rate ( BER ) Performance

 FIGS. 7 and 8 are graphs illustrating the BER performance of the proposed Tabu Search receiver and the existing Tabu Search technique for 16 × 16 MIMO and 16 × QAM, respectively, in a 16 × 16 MIMO system ', And' -CC 'means that the proposed algorithm uses the channel state for early termination.

또는

를 이용하여 조기 종료를 수행한 경우를 의미한다.'-ET' is a fixed parameter without consideration of channel conditions

or

Which means that the early termination is performed by using the termination.

 It can be seen that the algorithm proposed by the present invention in the low SNR range shows comparatively low performance compared to the conventional tabu search method but shows a considerable performance gain in the high SNR range.

에서 3.4 dB SNR 이득을 보이는 것을 도 7에서 확인 할 수 있다. 또한 도 8은 8×8 MIMO 시스템에서 본 발명이 제안한 알고리즘이 기존의 알고리즘에 비해서 2.5 dB SNR 이득을 동일한 BER에서 가짐을 보인다.Specifically, in the case of the 16 × 16 MIMO system, the proposed algorithm compared to the existing table search method in which the initial solution is estimated using MMSE,

7 shows the SNR gain of 3.4 dB. Also, FIG. 8 shows that the proposed algorithm in the 8x8 MIMO system has 2.5 dB SNR gain at the same BER as the conventional algorithm.

I. Complexity analysis

In order to compare the complexity of the proposed algorithm of the present invention, the number of floating point operations per symbol is analyzed.

Reception method PSC ZF-TS 1.44 MMSE-TS 1.44 LR-MMSE-TS 1.88 LR-MMSE-TS-ET1 1.11 LR-MMSE-TS-ET2 1.51 LR-MMSE-TS-CC 1.13

) 비교, SNR=22 dB][Operation amount

) Comparison, SNR = 22 dB]

Reception method PSC ZF-TS 2.92 MMSE-TS 2.92 LR-MMSE-TS 3.48 LR-MMSE-TS-ET1 1.51 LR-MMSE-TS-ET2 2.50 LR-MMSE-TS-CC 1.62

) 비교, SNR=25 dB][Operation amount

) Comparison, SNR = 25 dB]

Table 1 and Table 2 show the per-symbol complexity (PSC) for the 16 × 16 MIMO system and the 8 × 8 MIMO system when 16-QAM modulation is used, have.

Existing algorithms that do not apply the grid reduction technique show the same PSC value.

의 값에 비례해서 계산량이 증가하는 결과를 보이며, '-TS' 및 '-ET2'의 경우는 격자 축소 기법을 적용하지 않은 알고리즘에 비교해 많은 계산량을 필요로 한다.Algorithms using grid reduction techniques

And '-ET2' in the case of '-TS' and '-ET2', the computational complexity is required compared with the algorithm which does not apply the grid reduction technique.

 However, it can be seen from Table 1 that the '-CC', which is an early termination method based on the proposed channel state, shows a 27% lower complexity than the 'MMSE-TS' in the same experimental environment.

 In Table 2, which is the result of the 8 × 8 MIMO system, it can be seen that the proposed receiving scheme has a gain of about 45% in terms of the amount of computation compared to the conventional scheme 'MMSE-TS'.

As described above, those skilled in the art will appreciate that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. It is therefore to be understood that the above-described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the present invention is defined by the appended claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention.

Claims (10)

A method for finding an optimal solution of a MIMO receiver in a MIMO system of a wireless communication network,
The initial solution is set by applying the grid reduction method to the Tabu search method to find the optimal solution,

And the column vectors of the channel are multiplied by the orthogonal channel matrix (

) To reduce the amount of computation for finding the initial solution,
The number of iterations is set in advance and the search algorithm is searched for a set number of iterations, and when the maximum number of iterations is reached,
When the search algorithm is executed, the maximum number of repetitions of the set repetition times

In order to reduce the search complexity by terminating the search algorithm before reaching the end of the search algorithm, the incomplete Seysen value

Wherein the search algorithm can be terminated variably according to channel conditions.


delete The method according to claim 1,
The modified channel matrix (

) &Lt; / RTI &gt;

)end

When the formula is satisfied,

, And satisfies Equation (6): &lt; EMI ID = 6.0 &gt;
&Quot; (6) &quot;

(Where T is a unimodular matrix and z is

Quot; vector &quot;).
The method of claim 3,
In a MIMO system using the estimated z, a solution satisfying Equation (7) is obtained in a MIMO receiver to which a lattice reduction technique is applied, and the solution is used as an initial solution for applying a band search method as a solution for a symbol x An improved tone search method for reducing the computational complexity of a receiver.
&Quot; (7) &quot;

delete delete The method according to claim 1,
The incomplete Seysen value (

) Is a value that satisfies the following expression (8)

For

Border values

And the maximum number of iterations that corresponds to the termination criterion of the search algorithm corresponding to these values

Wherein the search algorithm is performed for a maximum number of iterations.
&Quot; (8) &quot;

(here,

Dual Base &lt; RTI ID = 0.0 &gt;

of

Column,

The

. &Lt; / RTI &gt;
The method of claim 7,
The lowest cost function value among the solutions found by the search algorithm

The number of iterations that do not show any further performance improvement from

, An optimal solution is found, and the search algorithm is terminated.
The method according to claim 1, wherein in incomplete Seysen numerical calculation,

For

To reduce the computational complexity of the receiver in a MIMO system.
A MIMO receiver according to any one of claims 1, 3, 4, and 7 to 9, wherein an optimal solution for a received signal is found.

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