KR101269683B1 - Method for detecting signal and receiving device - Google Patents

Abstract

The present invention relates to a signal detection method and a receiving apparatus. A signal detection method according to the present invention is a method for detecting a signal by a receiving apparatus of a communication system including a multiple input and output antenna, the method comprising: obtaining a square value of the distance between the received signal vector and the transmission symbol vector considering the channel state; Classifying a squared distance value into a first component and a second component, minimizing the first component to obtain a plurality of soft symbol estimates, and based on the plurality of first flexible solutions, Obtaining a solution set of a first component, minimizing the second component to obtain a plurality of second flexible solutions, obtaining a solution set of the second components based on the plurality of second flexible solutions, and And combining the solution set of the first component and the solution set of the second component to obtain a final solution set.

Detection, decoding, MIMO, likelihood

Description

Signal detection method and receiving device {METHOD FOR DETECTING SIGNAL AND RECEIVING DEVICE}

The present invention relates to a signal detection method and a receiving apparatus.

As wireless communication systems evolve, the demand for speed increases. In order to meet these demands, it is necessary to use a wide frequency band, the frequency resources are limited. Accordingly, a multi input multi output (MIMO) antenna technology is used as a method of transmitting more data while using a limited frequency band.

This multi-input / output antenna technology obtains a diversity gain that corresponds to the product of the number of transmit / receive antennas to improve the transmission reliability, thereby allowing different data streams through different paths and spatial diversity schemes. There is spatial multiplexing (SM) to transmit.

In the case of the dual spatial multiplexing method, mutual interference may occur between different data streams, and the receiver detects and decodes a signal in consideration of such interference. In this case, the optimal method is to obtain the likelihood of each data bit by considering detection and decoding at the same time. However, this method is not easy to implement due to the complexity of the constellation size and the number of antennas. .

Therefore, in each case of detection and decoding, an iterative detection decoding (IDD) method of obtaining a likelihood of each bit and repeatedly swapping each other to obtain a final likelihood of each bit is used. However, this approach is still too complicated, making it difficult to actually implement the system.

An object of the present invention is to perform signal detection with low complexity in a communication system including multiple input / output antennas.

A signal detection method according to an embodiment of the present invention is a method of detecting a signal by a receiving apparatus of a communication system including a multi-input / output antenna, the square value of the distance between the received signal vector and the transmission symbol vector considering the channel state Obtaining, classifying a square value of the distance into a first component and a second component, minimizing the first component to obtain a plurality of soft symbol estimates, and the plurality of first flexible solutions Obtaining a solution set of the first component based on the method, obtaining a plurality of second flexible solutions by minimizing the second component, and obtaining a solution set of the second components based on the plurality of second flexible solutions. And adding the solution set of the first component and the solution set of the second component to obtain a final solution set.

Obtaining a solution set of the first component may include finding a plurality of first points around the plurality of first flexible solutions on a constellation and using the plurality of first points to solve the first component. Obtaining a set may include.

The finding of the plurality of first points may include finding a first closest point by rounding each of the plurality of first flexible solutions.

The finding of the plurality of first points may further include finding a second close point by adding or subtracting 2 to the closest point.

The obtaining of the solution set of the second component may include finding a plurality of second points around the plurality of second flexible solutions on the constellation diagram and obtaining the solution set of the second component using the plurality of second points. It may include a step.

The finding of the plurality of second points may include finding a first closest point by rounding each of the plurality of second flexible solutions.

The finding of the plurality of second points may further include finding a second close point by adding or subtracting 2 to the closest point.

Obtaining a point set on the constellation by adding the plurality of first points and the plurality of second points, and a likelihood value for each bit value of the signal using the point set and the final solution set. It may further comprise the step of obtaining.

The step of obtaining a squared value of the distance may include obtaining an optimum ML solution (QR decomposition).

The step of obtaining a squared value of the distance may include QR decomposition of an augmented channel matrix.

A signal detection method according to another embodiment of the present invention is a method of detecting a signal by a receiving apparatus of a communication system including a multi-input / output antenna, the square value of the distance between the received signal vector and the transmission symbol vector considering the channel state Obtaining, classifying a square value of the distance into a first component and a second component, minimizing the first component to obtain a plurality of first flexible solutions, and based on the plurality of first flexible solutions, Obtaining a solution set of one component, selecting a part of the solution set of the first component, obtaining a plurality of second flexible solutions using the solution set of the selected first component, and the plurality of second flexible Obtaining a solution set of the second component using a solution, selecting a portion of the solution set of the second component, and a solution set of the selected first component and the selected second component Summing the solution sets to obtain the final solution set.

Obtaining a solution set of the first component may include finding a plurality of first points around the plurality of first flexible solutions on a constellation and using the plurality of first points to solve the first component. And obtaining a solution set of the second component, finding a plurality of second points around the plurality of second flexible solutions on constellations, and using the plurality of second points. Obtaining a solution set of the second component.

Selecting the first point corresponding to the solution set of the selected first component, selecting the second point corresponding to the solution set of the selected second component, the selected first point and the selected agent The method may include obtaining a point set on the constellation by adding two points, and obtaining a likelihood value for each bit value of the signal using the point set and the final solution set.

Selecting a part of the solution set of the first component includes selecting the elements forming the solution set of the first component in order of increasing size, and selecting the elements in a smaller order. Selecting a part of the set may include selecting the elements constituting the solution set of the second component in order of increasing size, and selecting them in a smaller order.

The number of the first point and the second point may be 2 or less, respectively.

The finding of the plurality of first points may include finding a first close point by rounding each of the plurality of first flexible solutions, and finding a second close point by adding or subtracting 2 to the closest point. It may include a step.

The finding of the plurality of second points may include finding a first close point by rounding each of the plurality of second flexible solutions, and finding a second close point by adding or subtracting 2 to the closest point. It may include a step.

A receiving apparatus according to another embodiment of the present invention is a receiving apparatus of a communication system including multiple input / output antennas, and includes a plurality of receiving antennas for receiving signals and a likelihood value for each bit of the signal from the receiving antennas. A detection unit for detecting a signal, and a decoding unit for decoding the signal detected by the detection unit, wherein the likelihood value is a square value of a distance between a received signal vector and a transmission symbol vector considering a channel state, the first component and the second component A plurality of first flexible solutions classified into components and minimizing the first component, a plurality of second flexible solutions minimizing the second component, first points around the plurality of first flexible solutions on constellations, and It is calculated using the 2nd point around the said 2nd some soft solution on constellation.

The plurality of first points may include a first closest point obtained by rounding for each of the plurality of first flexible solutions.

The plurality of first points may include a second close point by adding 2 or subtracting 2 to the first close point.

According to the present invention, a receiver of a communication system including multiple input / output antennas can detect and decode a signal with low complexity.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is said to "include" a certain component, it means that it can further include other components, without excluding other components unless specifically stated otherwise. Also, the terms " part, "" module," and " module ", etc. in the specification mean a unit for processing at least one function or operation and may be implemented by hardware or software or a combination of hardware and software have.

In this specification, a mobile station (MS) includes a terminal, a mobile terminal (MT), a subscriber station (SS), a portable subscriber station (PSS), and a user equipment. It may also refer to a user equipment (UE), an access terminal (AT), and the like, and may include all or some functions of a terminal, a mobile terminal, a subscriber station, a portable subscriber station, a user device, an access terminal, and the like.

In this specification, a base station (BS) includes an access point (AP), a radio access station (RAS), a node B, an evolved NodeB (eNodeB) A base station (BTS), a mobile multihop relay (MMR) -BS, or the like, and may perform all or a part of functions of an access point, a radio access station, a Node B, an eNodeB, a base transceiver station, .

Hereinafter, a signal detection apparatus and a signal detection method according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is a diagram illustrating a wireless communication system according to an embodiment of the present invention.

Referring to FIG. 1, a wireless communication system includes a transmitter 100 and a receiver 200.

The transmitter 100 includes a plurality of transmit antennas 110. The transmitter 100 performs scrambling, encoding, and modulation on the transmission data to radiate the air into the air through each of the transmission antennas 110.

The receiver 200 includes a plurality of receive antennas 210, a detector 220, and a decoder 230. Data received through each receiving antenna 210 is signal detected by the detector 220, and the detected signal is decoded by the decoder 230.

Signal detection in the detector 220 calculates a likelihood value for the bits of the received signal.

The received signal vector y may be expressed as Equation 1 below.

은 다음 수학식 2과 같이 표현된다.Here, H represents a channel matrix, s represents a transmission symbol vector, and n represents a white addition noise vector. Here, the likelihood value calculated by the detector 220

Is expressed by Equation 2 below.

는 복호화부(230)으로부터 피드백 받은 각 비트에 대한 우도 값을 사용하여 계산한다. 첫 번째에는 복호화부(230)로부터 받은 정보가 없으므로, 분자 분모에 0.5를 대입하여 얻은 값, 즉 0을 각 비트에 대해서 사용한다. [수학식 2]에서

부분을 정확히 계산하는 것은 매우 높은 복잡도를 요구하므로

을 근사화하여 다음 [수학식 3]으로 표현될 수 있다.In Equation 2, the basic information (priori information),

Is calculated using the likelihood value for each bit fed back from the decoder 230. First, since there is no information received from the decoder 230, a value obtained by substituting 0.5 into the numerator denominator, that is, 0 is used for each bit. In Equation (2)

Accurately calculating parts requires very high complexity

By approximating can be expressed by the following equation (3).

In Equation 3, x is a vector consisting of bits of +1 or -1 obtained from the transmission symbol vector s. Therefore, in the case of binary phase shift keying (BPSK), x and s become the same vector. However, x and s are not the same when other constellations are used. Each element of the vector x has a value of +1 or -1, but the elements of the vector s are given as points of constellation. In addition, the set X _{k, + 1} is a set of vectors including all possible cases for the k-th element of the vector x and +1, and is defined by Equation 4 below.

는 벡터 x의 k번째 원소

를 제거한 벡터로 정의되며, 마찬가지로

는

를 제외한 벡터 x의 모든 원소에 대한

값들로 이루어진 벡터를 나타낸다. 여기서 주어진

를 계산함에 있어서 가장 높은 복잡도를 요구하는 부분은 집합

에 속해 있는 모든 벡터 x(즉, 이에 대응하는 s) 에 대해서

를 계산하는 것이다Also, vector

Is the kth element of vector x

Is defined as the vector from which

The

For all elements of the vector x except

Represents a vector of values. Given here

The part that requires the highest complexity in calculating

For all vectors x (ie corresponding s) belonging to

Will calculate

2 and 3, a signal detection method according to an exemplary embodiment of the present invention, that is, a method of obtaining a likelihood value will be described in detail.

2 is a flowchart illustrating a signal detection method according to an embodiment of the present invention.

(augmented channel matrix)을 QR 분해하여

를 표현한다(S210).Referring to FIG. 2, a signal detection method according to an embodiment of the present invention may first include an optimal ML resolution or an increased channel matrix.

QR decomposition of the augmented channel matrix

Express (S210).

First, the ML solution can be obtained as

The number of transmit antennas 110 is 4, respectively, assuming that the transmission rate is 2, and consider the space time code as shown in [Equation 5].

이라고 가정하면, 수신 신호 r은 다음 [수학식 6]과 같이 쓸 수 있다.The number of receive antennas 210

, The received signal r can be written as Equation 6 below.

here,

는 j번째 수신 안테나(210)에서 t 번째 타임 슬롯(slot)에서의 수신 신호를 나타내며,

는 i번째 송신 안테나로부터 j번째 수신안테나 사이의 채널 이득을 나타낸다. 그리고,

는 j번째 수신안테나에서 t 번째 슬롯에서의 백색 잡음을 나타낸다.to be. Also, () 'and () "represent the real and imaginary parts of complex values, respectively.

Denotes a received signal in a t th time slot in the j th receive antenna 210,

Denotes the channel gain between the i th transmit antenna and the j th receive antenna. And,

Denotes white noise in the t-th slot in the j-th reception antenna.

가 M^2-직교 진폭 변조(quadrature amplitude modulation, 이하 "QAM"라고 한다)으로 주어지는 성상도(constellation)에서 발생된다고 가정하면, 심볼 s_k 는 M-펄스 진폭 변조(pulse amplitude modulation, 이하 "PAM"이라 한다)로 주어지는 성상도에서 발생되며, 이 성상도를 다음 수학식 7과 같이 C로 표기한다.Each transmit symbol

Assuming that is generated in the constellation given by M ² quadrature amplitude modulation (hereinafter referred to as "QAM"), the symbol s _k is the M-pulse amplitude modulation ("PAM"). Is generated in the constellation, which is expressed as C as shown in Equation 7 below.

는 다음 수학식 8과 같이 구해진다.In this case optimal ML solution

Is obtained as in Equation 8 below.

에 QR 분해(QR decomposition)를 하면 수학식 8은 다음 수학식 9와 같이 쓸 수 있다.Channel matrix

When QR decomposition is performed on Equation 8, Equation 8 can be written as Equation 9.

On the other hand, consider an augmented channel matrix (Augmented channel matrix) as shown in the following equation 10, and QR-decomposition it.

은

의 크기를 가지는 단위 행렬(unitary matrix)이고,

은

의 크기를 가지는 상위 삼각 행렬(upper-triangle matrix)이다. 또한,

은

의 크기를 가지는

의 부분 행렬이고,

은

의 크기를 가지는

의 부분 행렬이다. 이 경우에는, 다음 [수학식 11]과 같이 신호 검출이 수행된다.here

silver

Is a unitary matrix having the size of

silver

Is an upper-triangle matrix having the size of. Also,

silver

Having the size of

Is a partial matrix of

silver

Having the size of

Is the partial matrix of. In this case, signal detection is performed as shown in Equation 11 below.

이다.only,

to be.

를 구하기 위해서는 [수학식 9] 및 [수학식 11]과 같은 결과뿐만 아니라 성상도 상에서 그 주위의 여러 점들도 필요하다. 이제 이러한 여러 점들을 구하는 방법에 대하여 설명한다.Udo Rain on the hand

In order to obtain the equation, not only the same results as in [Equation 9] and [Equation 11] but also several points around the constellation are needed. Now we will explain how to obtain these points.

과

을 구할 수 있 으며, 두 경우 모두 다음 수학식 12와 같이 동일한 형태로 표시될 수 있다.First, using the Gram-Schmidt method,

and

In this case, both cases may be expressed in the same form as shown in Equation 12 below.

here,

to be.

가

의 j 번째 열을 나타내면

은

을 나타내며, 만약

가

의 j 번째 열을 나타내면

은

을 나타낸다In Equation 12,

end

Represents the j th column of

silver

, If

end

Represents the j th column of

silver

Indicates

와

를 다음 [수학식 13]과 같이 동일한 형태로 나타낼 수 있다.Also,

Wow

Can be expressed in the same form as shown in [Equation 13].

는 다음과 같이 주어진다. Where each column

Is given as follows.

here, Denotes the (k, j) th element of the matrix R.

Using [Equation 12] and [Equation 13], [Equation 9] and [Equation 11] can be represented by the following [Equation 14], [Equation 15] and [Equation 16].

, k=5, 6, 7, 8 를 구한다(S220).Now, let's minimize the first term of Equation 14, Equation 15, so that the soft symbol estimate

, k = 5, 6, 7, 8 (S220).

에 대해서 M_A 개의 주위의 점들을 구하고, 총 (M_A)⁴ 개의 점들의 집합을 S_A를 구한다. 또한 A 값들의 집합인

를 구한다(S230).Then find the constellation point closest to these values and the constellation points around it. That is, each

For obtaining the M _A of around point, a total of (M _A) is obtained S _A set of ^four dots. Also a set of A values

Obtain (S230).

, k=5, 6, 7, 8 에 대해서 가장 가까운 점을 점을 찾는 것은 올림 (rounding)과 같은 방법으로 찾을 수 있고, 두 번째로 가까운 점을 구할 때는, 성상도가 [수학식 7]로 주어지는 경우, 가장 가까운 점에 2를 더하거나 뺌으로서 구한다.Equation 15 consists of the sum of four independent terms, so each of these four terms can be thought of separately. That is, each

Finding the closest point for, k = 5, 6, 7, 8 can be found in the same way as rounding, and when finding the second closest point, the constellation is If given, add 2 to the nearest point or find it as 뺌.

에 대해서 M_A 개의 주위의 점들을 구한다. 여기서 점

로부터 ik 번째 가까운 점을

, k = 5, 6, 7, 8, 로 나타낸다. 이와 같이 구해진 총 (M_A)⁴ 개의 점들의 집합을 다음 [수학식 18]과 같이 S_A로 나타낸다.In this way, in the present invention,

Find the points around M _A for. Where point

Ik th close from

, k = 5, 6, 7, 8, In this way it shows a set of calculated total (M _A) ⁴ points in S _A, as follows: [Equation 18].

로 나타내다.The set of A values calculated by inserting each point of Equation 18 into Equation 15 is expressed as Equation 19 below.

Denoted by.

를 계산하기 위해서는 복잡도가(M_A)⁴가 된다. 그러나 본 발명에 따르면 A 가 독립된 4개의 항들의 합이기 때문에, 각

를 M_A 번씩 계산한 다음 그 값들을 (M_A)⁴ 번 조합하기만 하면 된다. 그러므로, 복잡도는 4M_A 가 된다.In general, (M _A ) has ^four elements

In order to calculate, the complexity (M _A ) is ⁴ . However, according to the present invention, since A is the sum of four independent terms,

M _A You only need to calculate it once and then combine the values (M _A ) ^four times. Therefore, the complexity is 4M _A.

, k=1, 2, 3, 4를 구한다(S240).Subsequently, the second term of Equation 14, Equation 16, is minimized to give a soft symbol estimate as shown in Equation 20.

, k = 1, 2, 3, 4 are obtained (S240).

이다. here

to be.

에 대해서 M_B 개의 주위의 점들을 구하고, 총 (M_B)⁴ 개의 점집합을 S_B를 구한다. 또한 B 값들의 해집합인

를 구한다(S250).Now each

We obtain M _B points around, and S _B for the total (M _B ) ⁴ point sets. Also, the solution set of B values

Obtain (S250).

를 구한 것과 동일한 방식으로 S_B 와

를 구할 수 있다. 우선,

, k=1, 2, 3, 4 를 수학식 20에 의해서 구해진 점

, k=1, 2, 3, 4으로부터 i_k 번째로 가까운 성상도 점을 나타낸다고 하고 각

, k=1, 2, 3, 4에 대하여 M_B개의 가까운 점들을 구한다. 이 점들은 위에서 구한

, k = 5, 6, 7, 8, 와 동일한 방식으로 구해질 수 있다. 이제 이와 같이 구해진 총 (M_B)⁴ 개의 점들의 집합을 나타내는

은 다음 수학식 21과 같이 표현되며, 그 각 점들을 수학식 16에 삽입하여 계산한 B 값들의 해집합

는 다음 [수학식 21] 및 [수학식 22]과 같이 나타내어 진다.S _A and

S _B and

Can be obtained. first,

, k = 1, 2, 3, 4 obtained by Equation 20

, k = 1, 2, 3, and 4, the i _kth closest constellation point

Find M _B nearest points for, k = 1, 2, 3, 4. These points are obtained from

, k = 5, 6, 7, 8, can be obtained in the same manner. Now, representing the set of thus gun (M _B) ⁴ points obtained

Is expressed as the following Equation 21, and the solution set of B values calculated by inserting each point into Equation 16 is

Is represented by the following [Equation 21] and [Equation 22].

와 점집합

를 합쳐서 성상도들의 최종 점집합 S를 다음 [수학식 23]과 같이 구하고, 해집합

와 해집합

를 합쳐서 메트릭 값들의 최종 해집합

를 다음 [수학식 24]와 같이 구한다(S260).now

And point set

The final point set S of constellations is summed as shown in [Equation 23], and the solution set

And solution set

To sum the final solution of metric values

To obtain as follows [Equation 24] (S260).

을 구한다(S270).Finally, we use these to likelihood values for each bit.

Obtain (S270).

메트릭 값을 구하였다. 이를 이용하여 점집합 S 및 수학식 4의

,

의 교집합을 구하면, 수학식 3을 이용하여 각 비트에 대한

을 구할 수 있다.In front of the gun (M _A M _B ) ^four constellation points and their corresponding

The metric value was obtained. Using this set of points S and Equation 4

,

If we find the intersection of, use Equation 3 for each bit

Can be obtained.

을 계산하게 된다. 하지만, 많은 경우에는 예를 들어, 신호 대 잡음비(signal noise ratio, SNR)가 높은 경우, 혹은 채널 상황이 좋은 경우, 혹은 성상도의 사이즈가 작은 경우(직교 위상 편이 변조(quadrature phase shift keying, QPSK), 16-QAM)에는 256 개의 점들 모두에 대해서

을 계산하는 것은 성능 향상 없이 복잡도만 높아진다. 따라서, 256보다 작은 크기를 가지는 성상도 점들의 집합을 사용하는 것이 성능 하락 없이, 복잡도를 많이 낮출 수 있는 경우에는 다른 방법을 사용하는 바 이하 이에 대하여 eh 3을 참고하여 상세하게 설명한다.On the other hand, the minimum number of constellation points that can be obtained in this way is 256 (M _A = M _B = 2), and for all these points

Will be calculated. However, in many cases, for example, when the signal to noise ratio (SNR) is high, or when the channel conditions are good, or the size of the constellation is small (quadrature phase shift keying, QPSK) , 16-QAM) for all 256 points

Calculations only increase complexity without improving performance. Therefore, when using a set of constellation points having a size smaller than 256 can reduce a lot of complexity without degrading performance, another method is used. This will be described in detail with reference to eh 3 below.

3 is a flowchart illustrating a signal detection method according to another embodiment of the present invention.

(augmented channel matrix)을 QR 분해하여

를 표현한다(S310). 그런 후 도 2의 실시예와 마찬가지로 다음 [수학식 17]과 같은 연성해(soft symbol estimate)

, k=5, 6, 7, 8를 구한다(S320).Referring to FIG. 3, first, as in the embodiment of FIG. 2, an optimal ML solution or augmented channel matrix is obtained.

QR decomposition of the augmented channel matrix

To express (S310). Then, as in the embodiment of FIG. 2, a soft symbol estimate as shown in Equation 17 below.

, k = 5, 6, 7, 8 are obtained (S320).

를 구한다(S330).Then, if M _A is 2 days (M _A) to a set of a set of ^four points _A and A values S

Obtain (S330).

로부터

개의 원소를 택한다(S340).

는 각 각 1과 16 사이의 어떤 값이나 가질 수 있다. 그러므로, 이에 의해서 주어지는 성상도 점들의 집합의 크기는 1에서 256 사이의 아무 값이나 가질 수 있으므로, 성상도의 크기나 채널 상황에 따라 이 값을 적절히 조정하여 신호 검출의 성능 하락 없이 최소의 복잡도만 가질 수 있다. 여기서 중요한 것은 최소의 복잡도로 해집합

의 원소를 크기가 커지는 순서대로 나열하여 상대적으로 작은 값을 선 택한다.The set is then S _A and the solution set

from

Elements are selected (S340).

Can have any value between 1 and 16, respectively. Therefore, the size of the constellation points given by it can have any value between 1 and 256, so adjust this value appropriately according to the size of the constellation or the channel situation so that only minimal complexity is achieved without sacrificing signal detection performance. Can have The important thing here is to solve it with minimal complexity

Select the smaller values by listing the elements of in order of increasing size.

로 주어지게 된다.Each set has 16 elements, so the number of possible listing methods is

.

의 원소 중에서

은 가장 작은 크기를 가지는 원소 임은 쉽게 보일 수 있다. 다음에는 네 개의 원소 {

,

,

,

} 를 크기 순서대로 나열한다. 이 단계에서는 최대 6 번의 값의 크기 비교가 필요하다. 이제

를 위의 네 개의 원소 중에서 n 번째로 작은 원소 스크립트에서 2의 위치를 나타낸다고 한다. 예를 들어, 위에서 주어진 4개의 원소를 크기 순서대로 나열한 결과가

<

<

<

인 경우,

으로 주어진다.) 또한,

은

의 원소

값들 중에서

위치에 있는 스크립트

가 2 의 값을 가지는 원소의 값을 나타낸다고 한다. 예를 들어,

로 주어지는 경우,

는 다음과 같은 값을 가진다:

,

,

,

=

,

). 이 경우,

은 해집합

의 원소 중에서 2번째로 작은 원소이고,

은 해집합

의 원소 중에서 3번째로 작은 원소이다. 또한,

은 해집합

의 원소 중에서 14번째로 작은 원소,

은 해집합

의 원소 중에서 15번째로 작은 원소,

은 해집합

의 원소 중에서 16번째로 작은 원소 (즉, 가장 큰 원소) 이다. 그러므로, 이제 해집합

의 16개의 원소 중에서 나머지 10개의 원소만 크기 순서대로 나열할 수 있다. 이 나열하는 방식은 최소 3번, 최대 6번의 크기 비교로서 구해질 수 있으며 이 방식은 도 4에 나타나 있으며, 나열된 원소는 도 5에 나타나 있다. 이들의 복잡도는, 최소 9, 최대 12로서 상대적으로 낮은 복잡도를 갖는다.First, the solution set of [Equation 19]

Of the elements of

Can easily be seen as the element with the smallest size. Next are four elements {

,

,

,

} Are listed in order of size. This step requires a size comparison of up to six values. now

Is the position of 2 in the nth smallest element script of the above four elements. For example, listing the four elements given above in order of magnitude

<

<

<

Quot;

Is also given by

silver

Element of

Of the values

Script at location

Suppose that represents the value of an element with a value of 2. E.g,

If given by

Has the following values:

,

,

,

=

,

). in this case,

Silver solution set

Is the second smallest element of,

Silver solution set

It is the third smallest element of. Also,

Silver solution set

14th smallest element of,

Silver solution set

15th smallest element of,

Silver solution set

Is the 16th smallest element of the element (ie, the largest element). Therefore, the solution is now

Only the remaining 10 elements of the 16 elements in can be listed in order of magnitude. This enumeration scheme can be obtained as a size comparison of at least three times and at most six times, which scheme is shown in FIG. 4, and the listed elements are shown in FIG. 5. Their complexity is at least 9 and at most 12 and has a relatively low complexity.

개의 원소 값들을 이용하여

를 구한다(S350). 즉

개의 원소들을 [수학식 16]에 대입하여 [수학식 20]과 같은 값을 구한다.Then selected from S _A

Using element values

Obtain (S350). In other words

Substitute elements into [Equation 16] to obtain the same value as [Equation 20].

를 구한다(S360). 이어서 집합을 S_B 및 해집합

로부터

개의 원소를 택한다(S370). 이 때 방법은 앞서 설명한 S_A 및

로부터

개의 원소를 택하는 방법과 동일하다.In addition, M is _B, if two days (M _B) to the set of _B S and B values of the set of ^four points

Obtain (S360). The set is then S _B and the solution set

from

Elements are selected (S370). In this case, the method described above is S _A and

from

Same as selecting elements.

개의 원소와

개의 원소를 합하여 S를 구하고 이에 대응하는 해집합

및 해집합

를 합하여 최종 해집합

를 구한다(S380).Then

Elements and

Sum S elements to find S and corresponding solution set

And solution set

Sum the final solution set

Obtain (S380).

을 구한다(S390).Finally, we use these to likelihood values for each bit.

Obtain (S390).

The embodiments of the present invention described above are not implemented only by the apparatus and method, but may be implemented through a program for realizing the function corresponding to the configuration of the embodiment of the present invention or a recording medium on which the program is recorded.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, It belongs to the scope of right.

1 is a diagram illustrating a wireless communication system according to an embodiment of the present invention.

2 is a flowchart illustrating a signal detection method according to an embodiment of the present invention.

3 is a flowchart illustrating a signal detection method according to another embodiment of the present invention.

4 is a diagram illustrating a method of arranging solution sets in a signal detection method according to another exemplary embodiment of the present invention.

FIG. 5 is a diagram showing elements of solution sets listed according to the method of FIG. 4 in a signal detection method according to another embodiment of the present invention. FIG.

Claims (20)

A method for detecting a signal by a receiving apparatus of a communication system including a multiple input / output antenna, Obtaining a squared value of the distance between the received signal vector and the transmitted symbol vector considering the channel state; Classifying the squared value of the distance into a first component and a second component, Minimizing the first component to obtain a plurality of first soft symbol estimates, Obtaining a solution set of the first component based on the plurality of first flexible solutions, Minimizing the second component to obtain a plurality of second flexible solutions; Obtaining a solution set of the second component based on the plurality of second flexible solutions, and Obtaining a final solution set by adding the solution set of the first component and the solution set of the second component Signal detection method comprising a. In claim 1, Obtaining the solution set of the first component, Finding a plurality of first points around the plurality of first flexible solutions on a constellation and obtaining a solution set of the first component using the plurality of first points. 3. The method of claim 2, Finding the plurality of first points, Finding a first closest point by rounding each of the plurality of first flexible solutions. 4. The method of claim 3, Finding the plurality of first points, And detecting a second close point by adding or subtracting 2 to the first close point. 3. The method of claim 2, Obtaining the solution set of the second component, Finding a plurality of second points around the plurality of second flexible solutions on the constellation, and obtaining a solution set of the second components using the plurality of second points. The method of claim 5, Finding the plurality of second points, Finding a first closest point by rounding for each of the plurality of second flexible solutions. In claim 6, Finding the plurality of second points, And detecting a second close point by adding or subtracting 2 to the first close point. The method of claim 5, Obtaining a point set on the constellation by adding the plurality of first points and the plurality of second points, and Obtaining a likelihood value for each bit value of the signal using the point set and the final solution set Signal detection method further comprising. In claim 1, Obtaining a square value of the distance, A method of detecting a signal comprising: QR decomposition to obtain an optimal likelihood resolution. In claim 1, Obtaining a square value of the distance, And performing QR decomposition on an augmented channel matrix. A method for detecting a signal by a receiving apparatus of a communication system including a multiple input / output antenna, Obtaining a squared value of the distance between the received signal vector and the transmitted symbol vector considering the channel state; Classifying the squared value of the distance into a first component and a second component, Minimizing the first component to obtain a plurality of first flexible solutions; Obtaining a solution set of the first component based on the plurality of first flexible solutions, Selecting a portion of the solution set of the first component, Obtaining a plurality of second flexible solutions using the solution set of the selected first component, Obtaining a solution set of the second component using the plurality of second flexible solutions, Selecting a portion of the solution set of the second component, and Obtaining a final solution set by adding the solution set of the selected first component and the solution set of the selected second component Signal detection method comprising a. 12. The method of claim 11, Obtaining the solution set of the first component, Finding a plurality of first points around the plurality of first flexible solutions on a constellation, and obtaining a solution set of the first component using the plurality of first points, Obtaining the solution set of the second component, Finding a plurality of second points around the plurality of second flexible solutions on a constellation diagram and obtaining a solution set of the second component using the plurality of second points. Signal detection method. The method of claim 12, Selecting the first point corresponding to the solution set of the selected first component, Selecting the second point corresponding to the solution set of the selected second component, Obtaining a point set on the constellation by adding the selected first point and the selected second point, and Obtaining a likelihood value for each bit value of the signal using the point set and the final solution set Signal detection method comprising a. The method of claim 12, Selecting a part of the solution set of the first component, Selecting the elements forming the solution set of the first component in an order of increasing size, and selecting the elements in a smaller order; Selecting a part of the solution set of the second component, Selecting the elements forming the solution set of the second component in an order of increasing size and selecting the elements in a smaller order; Signal detection method. The method of claim 12, And a number of the first point and the second point is 2 or less, respectively. The method of claim 12, Finding the plurality of first points, Finding a first closest point by rounding each of the plurality of first flexible solutions, and Find the second closest point by adding or subtracting 2 to the first closest point. Containing Signal detection method. The method of claim 12, Finding the plurality of second points, Finding a first closest point by rounding each of the plurality of second flexible solutions, and Find the second closest point by adding or subtracting 2 to the first closest point. Containing Signal detection method. A receiving apparatus of a communication system including multiple input / output antennas, A plurality of receiving antennas for receiving signals, A detector for detecting a signal by calculating a likelihood value for each bit of the signal from the receiving antenna; Decoding unit for decoding the signal detected by the detection unit Including, The likelihood value includes a plurality of first soft solutions that classify a square value of a distance between a received signal vector and a transmission symbol vector considering a channel state into a first component and a second component, and minimize the first component. A plurality of second flexible solutions that minimize a second component, calculated using a first point around the plurality of first flexible solutions on the constellation and a second point around the plurality of second flexible solutions on the constellation Receiving device. The method of claim 18, And the plurality of first points comprises a first closest point obtained by rounding for each of the plurality of first flexible solutions. 20. The method of claim 19, The plurality of first points includes a second close point by adding 2 or subtracting 2 to the first close point.

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