WO2008082226A1

WO2008082226A1 - Systems and method for generating soft decision

Info

Publication number: WO2008082226A1
Application number: PCT/KR2007/006997
Authority: WO
Inventors: Kyung-Whoon Cheun; Chang-Kyu Seol
Original assignee: Posdata Co., Ltd.; Postech Academy Industry Foundation
Priority date: 2006-12-28
Filing date: 2007-12-28
Publication date: 2008-07-10
Also published as: KR20080061690A; KR100855019B1

Abstract

The present invention relates to soft-decision information generation system and method for reducing the number of a candidate symbol vector necessary for calculating a log likelihood ratio (LLR) in an encoded Multi-Input Multi-Output (MIMO) system, in which the method comprising the steps of: rearranging column vectors according to a specific permutation in a given channel matrix and calculating a modified reception vector and calculating a candidate symbol vector of C(l≤C≤M) with a hierarchical decision feedback equalization (HDFE); selecting one candidate symbol vector among the calculated candidate symbol vectors and calculating K bits corresponding to the one candidate symbol vector among bits of the calculated candidate symbol vectors; calculating a candidate symbol vector of J(O≤J≤LK) corresponding to inverted bits for the calculated bits of K(0≤K<Tlog M) with a modified hierarchical decision feedback equalization (MHDFE); and rearranging the location of each element for the calculated symbol vectors of C+J in reverse of a permutation applied to the channel matrix.

Description

Systems and Method for generating soft decision Technical Field

[1] The present invention relates to the encoded Multi-Input Multi-Output (MIMO) system, more particularly, to the soft-decision information generating system and method which is capable of securing the low computational complexity and the high performance by reducing the number of candidate symbol vector required in calculating the Log-Likelihood Ratio (LLR) in an encoded Vertical Bell labs LAyered Space-Time (V-BLAST) system. Background Art

[2] Since the MIMO system using a plurality of transmission/reception antennas can increase the theoretical channel capacity without an additional bandwidth in comparison with the system using a single transmission/reception antenna, it is noticed as a core technology in the next generation wireless communication system. When the encode having a good error correcting capability such as the turbo code and the turbo class code is additionally used in connection with the MIMO system, the approaching to the theoretical channel capacity is possible, so that the systems which connects the MIMO system with the channel encoder has been suggested in various standards.

[3] The process of generating soft-decision information from the V-BLAST system as an input of the channel decoder in order to approach to the theoretical channel capacity by using the system in which the V-BLAST system which is suggested as a practical MIMO system is connected with the channel encode. The soft-decision information as an input of the channel decoder corresponds to the LLR for each transmission bit mapped to the M-ary modified constellation. In case of performing this according to the maximum likelihood (ML) algorithm, the computational complexity is in proportion to the MT, thus, it encounters many obstacles to implement with a real hardware. On the other hand, in the ZF (Zero-Forcing) algorithm suggested for the purpose of lowering the computational complexity, the performance degradation is very large in comparison with the ML algorithm. Therefore, the algorithm which has little performance degradation in comparison with the ML algorithm while the computational complexity is low is required. Disclosure of Invention

Technical Problem

[4] The invention has been designed to solve the above-mentioned problems, and it is an object of the invention to provide the method for calculating the LLR as an input of channel decoder in which the computational complexity is low in comparison with the ML algorithm while the performance is close to the ML algorithm.

[5] It is another object of the present invention to provide the system and method for generating soft-decision information, which is capable of securing the low computational complexity and the high performance by reducing the number of candidate symbol vector which is necessary in calculating the LLR in an encoded V-BLAST system. Technical Solution

[6] In order to achieve the above-mentioned object, according to an aspect of the invention, provided is a soft-decision information generation system comprising first transmission candidate symbol vector calculating means for calculating a first transmission candidate symbol vectors by performing a hierarchical decision feedback equalization (HDFE) according to a channel signal and a reception signal; second transmission candidate symbol vector calculating means for calculating a second transmission candidate symbol vectors by performing the HDFE according to the channel signal and the reception signal for bits of the first transmission candidate symbol; candidate symbol vector element order altering means for rearranging a location of each element in the reverse of a permutation which is applied to a channel matrix for the calculated symbol vectors; and log likelihood ratio (LLR) calculation means for calculating the LLR for all λ by using the calculated symbol vectors to input into a channel decoder.

[7] In order to achieve another object, according to another aspect of the invention, provided is a soft-decision information generation method for rearranging column vectors according to a specific permutation in a given channel matrix and calculating a modified reception vector and calculating a candidate symbol vector of C(l≤C≤M) with a hierarchical decision feedback equalization (HDFE); selecting one candidate symbol vector among the calculated candidate symbol vectors and calculating K bits corresponding to the one candidate symbol vector among bits of the calculated candidate symbol vectors; calculating a candidate symbol vector of J(O≤J≤LK) corresponding to inverted bits for the calculated bits of K(0≤K<Tlog M) with a modified hierarchical decision feedback equalization (MHDFE); and rearranging the location of each element for the calculated symbol vectors of C+J in reverse of a permutation applied to the channel matrix.

[8] The calculating the modified reception vector is performed, when a matrix where the location of the column vectors of a channel matrix H which is given by a determined specific permutation is changed is defined as H' by multiplying a reception signal vector by a Hermitian matrix Q of Q after performing a QR decomposition for the matrix H' into QR. [9] The calculating the candidate symbol vector of C(l≤C≤M) includes selecting points of C(l≤C≤M) among all available points on M-ary constellation which can be received through an element located in the lowest position of the modified reception vector when the modified reception vector is calculated; and performing interference cancellation of the modified reception vector for the selected each point, and calculating a candidate symbol vector

a/

(1=1,...,C) of the C(l≤C≤M) by applying a decision feedback equalization (DFE) detecting scheme.

[10] The calculating the candidate symbol vector of J(O≤J≤LK) includes selecting a candidate symbol vector a₇ = [a[ a~ 4]

(1=1,...,L) of L, according to a specific standard among the calculated candidate symbol vectors

a/

(1=1,...,C) when the candidate symbol vectors

a/

(1=1,...,C) are calculated; and selecting one candidate symbol vector

S, according to a specific standard among the selected candidate symbol vector, performing interference cancellation of the modified reception vector by using

a/

(1=1,...,L) among the selected candidate symbol vector

a L₇, = I a₁ a₂ ' • - a_τ

(1=1,...,L) by each bit location so as to calculate the candidate symbol vectors corresponding to inverted bits for bits of K(0≤K<Tlog M) among corresponding bits, and calculating a candidate symbol vector (1=1,..., J) of J(O≤J≤LK) by applying the DFE detecting scheme.

Advantageous Effects

[11] The soft-decision information generation method in the encoded MIMO system according to the present invention has an effect as follows.

[12] First, the present invention provides a method for calculating the LLR for the input of channel decoder in which the computational complexity is low in comparison with the ML algorithm while the performance is close to the ML algorithm.

[13] Second, it has the effect that the low computational complexity and the high performance are secured by reducing the number of the candidate symbol vector which is necessary in calculating the LLR in an encoded V-BLAST system.

[14] Third, it has the effect that the computational complexity is lowered in comparison with the ML algorithm and the binary tree search based algorithm having a similar performance since the number of candidate symbol vector necessary for the generation of soft-decision information is in proportion to the number of constellation points.

[15] Fourth, in case the soft-decision information cannot be generated for some bit location, the problem of searching for the optimum constant for replacing the soft- decision information for a corresponding bit is solved, thereby, the soft-decision information can be generated for all bit locations. Brief Description of the Drawings

[16] The above and other exemplary features, aspects, and advantages of the present invention will be more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which:

[17] Figure 1 is a configuration block diagram of soft-decision information generation system according to the present invention.

[18] Figure 2 is a flowchart for the generation of soft-decision information in soft- decision information generation system according to the present invention.

[19] Figure 3 is a flowchart showing a hierarchical decision feedback equalization

(HDFE) process for obtaining the candidate symbol vector of C.

[20] Figure 4 is a flowchart showing the modified hierarchical decision feedback equalization (MHDFE) process for obtaining the candidate symbol vector of L.

[21] Figure 5 is an exemplary diagram showing the process of performing the hard decision after dividing constellation based on the bit value corresponding to a specific bit location.

[22] Figure 6 is a characteristic graph in case the algorithm according to the present invention is applied to a 2x2 V-BLAST system in connection with the CTC.

[23] Figure 7 is a characteristic graph in case the algorithm according to the present invention is applied to a 4x4 V-BLAST system in connection with the CTC. Mode for the Invention

[24] Hereinafter, exemplary embodiments of the present invention will be described with reference to the accompanying drawings. The same elements will be designated by the same reference numerals all through the following description and drawings although they are shown in different drawings. Further, in the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

[25] Hereinafter, a preferred embodiment of the system and method for generating soft- decision information which can be applied to the Multi-Input Multi- Output (MIMO) system according to the present invention will be explained in detail. The feature and advantages of the system and method for generating soft-decision information will be clear through the detailed description of each embodiment in the below.

[26] Figure 1 is a configuration block diagram of the soft-decision information generation system according to the present invention.

[27] The present invention relates to the generation of soft-decision information which can be applied to the encoded Vertical Bell labs LAyered Space-Time (V-BLAST) system, and is to provide the algorithm in which the performance is close to the Maximum Likelihood (ML) algorithm while the computational complexity is low in comparison with the ML algorithm. The present invention relates to the method for generating the soft decision information as an input of the channel decoder of a receiver in an encoded V-BLAST system in which the number of transmission antenna is T and the number of reception antenna is N. A plurality of candidate symbol vectors are necessary so as to generate soft-decision information, and the present invention is characterized in that such candidate symbol vectors are efficiently selected.

[28] For this, the soft-decision information generation system for implementing the algorithm for generating the soft decision information according to the present invention includes like the below. For example, the configuration in which the number of transmission antennas produces the Log Likelihood Ratio (LLR) about the transmission bits in the V-BLAST system in which the number of RX-antenna it is Ts is N as the input of the channel decoder will be illustrated.

[29] As shown in Figure 1, the soft-decision information generation system includes first transmission candidate symbol vector calculating means for calculating a first transmission candidate symbol vectors by performing the hierarchical decision feedback equalization method (HDFE) according to a channel signal and a reception signal, second transmission candidate symbol vector calculating means for calculating a second transmission candidate symbol vectors by performing the HDFE according to the channel signal and the reception signal for the bits of the transmission candidate symbol obtained from the first transmission candidate symbol vectors, candidate symbol vector element order altering means 108 for rearranging the location of each element in the reverse of the permutation which is applied to the channel matrix for the calculated symbol vectors, and LLR calculation means 109 for calculating the LLR for all bits by using symbol vectors obtained by the above process to input to the channel decoder.

[30] Here, the first transmission candidate symbol vector calculating means includes a channel estimator for calculating H by determining the order of the column vectors of H to rearrange according to the specific permutation in the reception signal received in the radio signal (RF) receiver and the channel matrix H which is given in the channel signal, H column vector order permutation means 100 for defining the matrix in which the location of column vectors of channel matrix H which is given by the determined specific permutation is changed as H', QR calculation means 101 for performing the QR decomposition for the matrix H into QR, modification reception vector generation means 102 for calculating the reception vector z which is modified by multiplying the reception signal vector by Q that is a Hermitian matrix of Q after performing the QR decomposition, Euclidean distance calculation means 103 for selecting C(l≤C≤M) among all available points on the M-ary constellation which can be received through the element located in the lowest position among the calculated vectors, and HDFE performing means 105 for applying the decision feedback equalization (DFE) detecting scheme after performing the cancellation of the interference from the reception vector z modified for each point selected as a candidate symbol, and calculating the candidate symbol vector

a/

(l=l,...,C) of C(l≤C≤M). [31] The second transmission candidate symbol vector calculating means includes candidate symbol vector arrangement means 104 for selecting the candidate symbol vector

i, = [^Si a,, a_τ ^{ι ~}\

(1=1,...,L) of L according to a specific standard among the candidate symbol vectors

(1=1,...,C) which is calculated in the first transmission candidate symbol vector calculating means, bit calculating means 106 for calculating the bit of K(l≤C≤Tlog M) among corresponding bits after selecting one candidate symbol vector according to a specific standard among the selected candidate symbol vectors, and MHDFE performing means 107 for performing the interference cancellation from z by using

(1=1,...,C) in the candidate symbol vector

(1=1,...,L) selected by each bit location and, calculating the candidate symbol vector

a/

(1=1,..., J) of J(l≤J≤LK) by applying the DFE detecting scheme so as to calculate the candidate symbol vectors corresponding to the inverted bits for the calculated bits.

[32] The method for selecting a candidate symbol vectors efficient for calculating the

LLR for each transmission bits necessary as an input of channel decoder according to the present invention is as follows.

[33] Figure 2 is a flowchart for the generation of soft-decision information in soft- decision information generation system according to the present invention. Figure 3 is a flowchart showing a HDFE process for calculating the candidate symbol vector of C, Figure 4 is a flowchart showing the MHDFE process for obtaining the candidate symbol vector of L.

[34] Firstly, the order (location within matrix) in the column vectors is reset according to a specific permutation for a given channel matrix H.

[35] In case each row is defined as layer when the reception signal model is indicated in the form of the column vectors and matrix format, assuming that the M-ary modulation system is used, the HDFE is performed for the first layer to calculate the candidate symbol vectors of M.

[36] In addition, the symbol vector

minimizing the Euclidean distance with the reception signal among the candidate symbol vectors al ' ^a2 ' ^{" " '} ' ^aM of M is selected. [37] The bits corresponding to the symbol vector a 1 is calculated, and the bits b which are calculated by inverting the corresponding bits. K bits are selected among the remaining bits excepting the bits corresponding to the elements located in the lowest position of the vector z calculated for the bits b

, the additional candidate symbol vectors of L corresponding to each of the selected bit is calculated by performing the MHDFE. The MHDFE is performed with K time since K bit is selected among total bits. The soft-decision information for the channel decoder is generated by using the symbol vectors of C+LK which are calculated through the HDFE and the MHDFE of (T-l)log M time.

[38] Referring to Figure 2, the soft-decision information generation method in the encoded V-BLAST system according to the present invention will be illustrated in detail. In the present invention, the method for efficiently reducing the number of candidate symbol vector which is necessary in calculating the LLR is suggested.

[39] Firstly, in case the reception vector r and the channel matrix H are given (S201), the new matrix H' is calculated by determining and reallocating the order of column vectors of H according to a specific standard for H (S202). The reception signal model of a representative V-BLAST system is identical with Equation 1.

[40] [Equation 1]

[41] y = Ha + n

[42] Here, T, N indicates the number of the transmission antenna and the reception antenna. In case of the channel matrix H, each element is a complex Gaussian probability variable in which the dispersion is 1(

E h = l, i = l,2, - , N, j = l,2,- ,T ), while, in case of the white Gaussian noise vector n, each element is a complex Gaussian probability variable satisfying

2 ^' I 2 |²] = σ_B ², / = l,2,-,tf

. When the i-th column vector of the channel matrix H given in the Equation 1 is defined as h , the location of h and h is mutually exchanged and the permutation between h , (j = l, 2, - , T, j ≠ i) is determined according to a specific standard.

[43] Here, assuming that the j-th column vector of the channel matrix H which is given before the permutation of the column vectors is determined corresponds to σ(j)-th in the matrix after the order is determined, the Ha in the Equation 1 can be rewritten like the H'a' defined in the Equation 2.

[44] [Equation 2] [45]

[46] Additionally, the QR decomposition is performed for the matrix H' and the matrix R, Q(H'=QR) are obtained, while the reception vector r is multiplied by the Q^H that is a conjugate transpose of the matrix Q to calculate the vector z(=Q r) (S203).

[47] That is, in the Equation 2, when N≥T and the rank of H is T, assuming that the result of performance of the QR decomposition for H', the result which is obtained by multiplying both sides of Equation 1 by the Hermitian matrix Q^H of Q matrix can be expressed like the Equation 3.

[48] [Equation 3] z = Ra' + w, z = Cr y, w = Cr n

[50] The HDFE is performed based on the vector z(=Q"r) and the matrix R, so that the candidate symbol vector

(1=1, ...,M) of M is calculated (S204).

[51] The process of calculating the candidate symbol vectors of M by performing such HDFE will be explained in detail with reference to Fig. 3. [52] The process of hierarchical decision feedback equalization (HDFE) is shown in Fig. 3. [53] Firstly, when the initialization step (S301) (S302) is progressed and, assuming that all points on the M-ary constellation are ύl ' ^ύ2 ' ' ^ύM when the modulation index at each transmission antenna is log M, an arbitrary s, is substituted for ά_τ in Equation 4 and y (J=N-I,...,1) of [Equation 4] is calculated (S303). j

[54] Additionally, in case the hard decision is performed for each y (S304), one j candidate symbol vector

~ r ~/ „/ _™/ ^~|T / , \

Si₁ = I a₁ a₂ ^• " a_τ I a₁ = S₁ ) is calculated (S307). This process is repeated and progressed for each y (S305)(S306). τ j

[55] Here, the vector x indicates the transpose matrix of the vector x. In case this process is performed for all possible

^SI

(1=1, ...,M) (S308)(S309), the candidate symbol vectors

(1=1,...,M) of M are calculated. [56] [Equation 4]

[57]

[58] Further, after the HDFE is performed to calculate the candidate symbol vectors of

M, the following process is progressed. That is,

for all M candidate symbol vectors are calculated (S205). The calculated

selects

a/ of L which are smallest, and the selected

a/ which are arranged in ascending order of

are redefined as

a/

(l=l,...,L) (S206). [59] Then, the bits corresponding to the candidate symbol vector

/ n M₂ \

B₁ = arg mm z - RaJ

\ δ/ / are calculated, and it is defined as

' - -b ^υ\^τ

(S207). [60] Expatiating on the steps S205 ~ S207, the candidate symbol vector minimizing

is searched among the obtained candidate symbol vector r ~_/ ~_/ ~_/ ^~\^τ

2L₁ = I a₁ a₂ ^{• •} - a_τ of M. When this symbol vector is

a₁ ( = argmin||z - Ra_/| I

\ S/ /

, the bits corresponding to

is searched. These bits are defined as

and the modulation index is indicated with m=log M.

[61] For convenience, assuming that the bit for generating the soft-decision information is n-th bit from the Least Significant Bit (LSB) among the bits mapped to the modulation symbol transmitted to the k-th antenna, the location of the bit for generating the soft-decision information is defined as (k, n), k=l,...,T-l, n=l,...,m.

[62] When reviewing the a I among the candidate symbol vectors I^~ W ~/ W ^~I^T

of M collected through the HDFE, it can be easily recognized that all symbols are included in the

(1=1,...,M). Therefore, the bit location in which the LLR is not defined does not exist when the soft-decision information corresponding to (T, n), n=l,...,m is generated.

[63] However, since the bit locations in which the LLR is not defined exist among the bit locations (k, n), k=l,...,T-I, n=l,...,m, an additional MHDFE is performed for these bit locations, so that candidate symbol vectors are calculated.

[64] Then, the MHDFE is performed according to the calculated

(1=1, ...,L) and

, so that

(1=1,..., L(T-l)log M) is calculated (S208). [65] That is, after performing the step S207, in order to guarantee that the bit locations in which the LLR is not defined does not exist, the MHDFE is performed for all bit locations (k, n), k=l,...,T-I, n=l,...,m having the possibility that the LLR is not defined.

[66] The progressing of the MHDFE process is shown in Figure 4.

[67] Firstly, if input is performed, an arbitrary bit location having the possibility that the

LLR is not defined is defined as (k¹, n') (S401). Then, the y (J=T-I,...,1) is calculated j as in Equation5 after the initialization steps (S402) (S403), the hard decision is performed for each y to calculate one candidate symbol vector. j [68] That is, assuming the

^Sl ^■> ^S2 ' " ^{* ■}> ^SM that all points on the M-ary constellation when the modulation index is m=log M, the candidate symbols of L are selected among them. [69] [Equation 5]

[70]

[71] The standards for selecting the symbols of L is as follows. The candidate symbol vector of L which minimizes

is chosen among the candidate symbol vectors

a/

(1=1,...,M) of M detected through the initial HDFE performing. [72] When these vectors are

|^~ w ~/ w ^~|^τ a, = O₁ a₂ ' " a_τ

(1=1,... ,L), (1=1,..., L) are selected as the above candidate symbols. The a_τ ^ι

(1=1,...,L) is substituted for a_τ of Equation 5 and y (j=T-l,...,l)of Equation 5 is calculated (S404).

[73] When the hard decision is performed (S406) (S407) for each y (S408) (S409) after j calculating y (J=T-I,...,1), one candidate symbol vector

is calculated (S410). [74] At this time, in case

^' v is 1 when the hard decision is performed for the observation y which is k'-th canceled, k' the symbol which is close to y among the points on the M-ary constellation in which the n'-th bit(n'=l,...,m) corresponds to 0 is selected (S406). [75] On the contrary, in case

is 0, the symbol which is close to y among the points on the M-ary constellation in k' which the n'-th bit(n'=l,...,m) corresponds to 1 is selected (S407). [76] When this process is performed for all possible

a/

(1=1,...,L), the candidate symbol vectors

(1=1,...,J) of J are calculated (S411)(S412). Such MHDFE is performed for all bit locations (k, n), k=l,...,T-I, n=l,...,m having the possibility that the LLR is not defined and calculates the candidate symbol vectors of L for each MHDFE, accordingly, the total L(T-l)log M can be calculated.

[77] In this way, the location of the elements within vector is rearranged in reverse order of the column vector order performed at the step S202 for the candidate symbol vectors of the total M+L(T-l)log M obtained by performing the HDFE and the MHDFE. Finally, the LLR is calculated by using the candidate symbol vectors of M calculated by the HDFE process and the candidate symbol vectors of L(T-l)log M obtained by the MHDFE process. [78] That is, the order of each element of

(1=1,... ,M),

»/

(1=1,...,L(T-I )log M) obtained by the process described above is introduced for the efficient detection, while being different from the order of the elements within the symbol vector transmitted, the order of element of each candidate symbol vector should is rearranged with an original order (S209).

[79] In case the above process is performed, the candidate symbol vectors of the total

M+L(T-l)log M are obtained. The LLR for λ-th bit can be calculated according to Equation 6 or Equation 7 by using the symbol vectors of the M+L(T-l)log M. After the calculation for all λ, inputting to the channel decoder is performed (S210).

[80] [Equation 6]

[81]

llb^λ y,w) - min z - Ra

[82] [Equation 7]

[83]

L

[84] In the soft-decision information generation method in the encoded V-BLAST system according to the present invention,

i An the Equation 5 is a set of candidate symbol vectors in which the λ-th bit corresponds to 1 among the candidate symbol vectors of M+L(T-l)log M calculated by the process described above while

is a set of candidate symbol vectors in which the λ-th bit corresponds to 0. [85] Additionally, Figure 5 indicates an example of the process of performing the hard decision after dividing constellation according to the bit value corresponding to a specific bit location when the location of the bit which is determined the LLR is not defined at the step S407 of Figure 4 correspond to the third from the LSB. [86] In case of

4² =0

, there is a possibility that the candidate symbol vector which has 1 at the corresponding bit location may not included in the set of candidate symbol vectors of M calculated through the initial HDFE process. [87] Therefore, in performing the hard decision in order to calculate the candidate symbol vector having 1 at a corresponding bit location, the tenth symbol having the shortest Euclidean distance is not selected, but the eleventh symbol which is the most close to y among the symbols in which the third bit correspond to 1. k'

[88] Hereinafter, the soft-decision information generation method according to the present invention described in the above which is applied to the V-BLAST system will be illustrated.

[89] Figure 6 is a characteristic graph in case the algorithm according to the present invention is applied to a 2x2 V-BLAST system in connection with the Convolutional Turbo Code (CTC), Figure 7 is a characteristic graph in case the algorithm according to the present invention is applied to a 4x4 V-BLAST system in connection with the CTC.

[90] Figs. 6 and 7 are a graph showing the Frame Error Rate (FER) when the LLR is calculated by using Equation 6 after selecting candidate symbol vectors according to method suggested in the present invention in the system which is CTC connected with the V-BLAST system in which the number of the transmission/reception antenna is 2 and 4 respectively.

[91] Figure 6 indicates the V-BLAST system in which the number of the transmission antenna is 2 and the number of the reception antenna is 2, Figure 7 indicates the V- BLAST system in which the number of the transmission antenna is 4 and the number of the reception antenna is 4.

[92] In addition, L=I, the modulation scheme is Quadrature Phase Shift Key (QPSK), 16

Quadrature Amplitude Modulation (QAM), 64 QAM, the length of frame is 144 bit, and the code rate applies to the parameter of 1/3.

[93] The decoding method applies to Max-log MAP, the scaling factor 0.7. The in- terleaver structure refers to the WiBro standard.

[94] Here, each element of the channel matrix is an i.i.d. (independently and identically distributed) complex Gaussian probability variable in which the average is 0 and the dispersion is 1. Further, it is resulted from the fact that the step S202 is not performed, while, at the step s202, the order of column vectors of H is determined and rearranged to obtain a new matrix H according to a specific standard for the channel matrix in Figure 2.

[95] As shown in Figs. 6 and 7, when the present invention is applied to the V-BLAST system, in case of 2x2, the degradation of performance compared to the performance of ML algorithm hardly exists, while, in case of 4x4, the maximum of it is ID.

[96] According to the present invention, in the encoded V-BLAST system in which the transmission antenna of T and the reception antenna of N are used while the modulation index of the symbol transmitted from each transmission antenna is log M, by reducing the number of candidate symbol vector necessary for the soft-decision information generation from MT to M+L(T-l)log M, the soft-decision information generation method in which the computational complexity is reduced and the degradation of performance compared to the performance of ML algorithm is within the maximum ID can be provided.

[97] While the invention has been shown and described with reference to certain exemplary embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. Therefore, the spirit and scope of the present invention must be defined not by described embodiments thereof but by the appended claims and equivalents of the appended claims.

Claims

[1] A soft-decision information generation method for generating a log likelihood ratio (LLR) for transmission bits to be an input of a channel decoder in a Multi- Input Multi- Output (MIMO) system including transmission T and reception antenna N, the soft-decision information generation method comprising the steps of: rearranging column vectors according to a specific permutation in a given channel matrix and calculating a modified reception vector and calculating a candidate symbol vector of C(l≤C≤M) with a hierarchical decision feedback equalization (HDFE); selecting one candidate symbol vector among the calculated candidate symbol vectors and calculating K bits corresponding to the one candidate symbol vector among bits of the calculated candidate symbol vectors; calculating a candidate symbol vector of J(O≤J≤LK) corresponding to inverted bits for the calculated bits of K(0≤K<Tlog M) with a modified hierarchical decision feedback equalization (MHDFE); and rearranging the location of each element for the calculated symbol vectors of C+J in reverse of a permutation applied to the channel matrix.

[2] The soft-decision information generation method of claim 1, wherein the calculating the modified reception vector is performed, when a matrix where the location of the column vectors of a channel matrix H which is given by a determined specific permutation is changed is defined as H' by multiplying a reception signal vector by a Hermitian matrix Q of Q after performing a QR decomposition for the matrix H' into QR.

[3] The soft-decision information generation method of claim 1, wherein the step of calculating the candidate symbol vector of C(l≤C≤M) includes: selecting points of C(l≤C≤M) among all available points on M-ary constellation which can be received through an element located in the lowest position of the modified reception vector when the modified reception vector is calculated; and performing interference cancellation of the modified reception vector for the selected each point, and calculating a candidate symbol vector

a/

[4] The soft-decision information generation method of claim 3, wherein the step of calculating the candidate symbol vector of J(O≤J≤LK) includes: selecting a candidate symbol vector

2L₁ = \ a_{ a₂ a ^/ 1^T

T_n J

(1=1,...,C) when the candidate symbol vectors

a/

(1=1,..., C) are calculated; and selecting one candidate symbol vector

» 1 according to a specific standard among the selected candidate symbol vector, performing interference cancellation of the modified reception vector by using

a/

(1=1,...,L) among the selected candidate symbol vector

(1=1,...,L) by each bit location so as to calculate the candidate symbol vectors corresponding to inverted bits for bits of K(0≤K<Tlog M) among corresponding bits, and calculating a candidate symbol vector

*ι

(1=1,..., J) of J(O≤J≤LK) by applying the DFE detecting scheme.

[5] The soft-decision information generation method of claim 4, wherein the selecting a candidate symbol vector of L is performed by calculating the Euclidean distance

(1=1,...,C) between the candidate symbol vector

a/

(1=1,...,C) and the modified reception vector Z, and selecting the candidate symbol vector

2L₁ = \ a_{ a₂ a ^/ 1^T

T_n J

(1=1,...,L) corresponding to the Euclidean distance of L having small magnitude among the calculated Euclidean distance

(1=1, ...,C).

[6] The soft-decision information generation method of claim 4, wherein the selecting one candidate symbol vector

is characterized by selecting the one candidate symbol vector

⁵I which has the smallest Euclidean distance

among the selected candidate symbol vectors, and calculates part of or the whole of bits corresponding to the candidate symbol vector

«i

[7] The soft-decision information generation method of claim 4, wherein the step of calculating the candidate symbol vector

a/

(1=1,...,J) of J(O≤J≤LK) is characterized by performing a hard decision is performed within a set of symbols in which a λ mod log M-th bit corresponds to 0 or 1, when the hard decision for the

-th symbol is performed while considering the bit location of λ-th bit, whole symbols are classified into a set of symbols in which the bit which is located in the λ mod log M-th position from Least Significant Bit (LSB) corresponds to 0 and a set of a set of symbols in which the bit which is located in the λ mod log M-th position from LSB corresponds to 1.

[8] The soft-decision information generation method of claim 1, wherein the reception signal model of a Vertical Bell labs LAyered Space-Time (V-BLAST) system is defined as; y = Ha + n

÷Vil \ h "1_u1 hi ^••• y₂ K ^l2,\ h ^'22 y = H =

>Ά K ^lN_n\ k V 2

and, here T, N indicate the number of transmission antenna and reception antenna, and, in case of the channel matrix H, each element is a complex Gaussian probability variable in which a dispersion is 1(

E h = \,i = \,2,---,N,j = \,2,---,T

) , while, in case of a white Gaussian noise vector n, each element is a complex Gaussian probability variable in which each element satisfies

[9] The soft-decision information generation method of claim 1, wherein calculating the candidate symbol vector of C(l≤C≤M) with the HDFE includes: when all points on the M-ary constellation are e e ... e k³l'^k32' ->^M assuming that a modulation index in each transmission antenna is log M, when

calculating a y (J=T-I,...,1) of the Equation by substituting

^Sl for a T

calculating one candidate symbol vector

{^aT=^Sl) by performing the hard decision for each y ; and j performing the above process for all available

^Sl

(1=1, ...,M).

[10] The soft-decision information generation method of claim 1, wherein the

MHDFE for calculating the candidate symbol vector of J(O≤J≤LK) includes: when all points on the M-ary constellation are

while the location of an arbitrary bit having a possibility that a LLR is not defined is defined as (k¹, n') and the modulation index is m=log M, selecting symbol vectors of L which minimizes

among the candidate symbol vectors

a/

(1=1,...,C) of C which is detected by the result of an initial HDFE performance; selecting

a/

(1=1,...,L) for the candidate symbols when the selected symbol vectors when the selected symbol vectors of L is defined as

- r _ / _ ; _^i ^~|T a/ ^: π

y (j=T- 1 , ... , 1 ) by substituting

(1=1,- ..,C) for a_τ ^ι of

calculating one candidate symbol vector

by performing the hard decision for each y ; and j calculating candidate symbol vectors a_τ ^ι

(1=1,...,L) of L by performing the above process for all available a_τ ^ι

(1=1, ...,L).

[11] The soft-decision information generation method of claim 10, wherein the calculating the one candidate symbol vector by performing the hard decision is performed, when the hard decision is characterized by performing for an observation y which is k'-th cancelled, by the symbol which is close to y among the points on the M-ary constellation in which the n'-th(n'=l,...,m) bit corresponds to 0 is selected when

is 1, whereas the symbol which is close to y among the points on the M-ary con- k' stellation in which the n'-th(n'=l,...,m) bit corresponds to 1 is selected when

K k K' n is O.

[12] The soft-decision information generation method of claim 1, further comprising the step of calculating a LLR of λ-th bit by using

L(b^λ y,H) = L(b^; Z,RW

or

L (b^λ y, H) = L (b^λ I z, R) * [ min llz - Ra_A_ f - min llz - Ra_A_ |² )

for the candidate symbol vector of C and the candidate symbol vectors of J to calculate for all λ, and inputting the LLR for all λ into the channel decoder.

[13] A Soft-decision information generation system in a Multi-Input Multi-Output

(MIMO) system including transmission antenna T and a reception antenna N, the soft-decision information generation system comprising: first transmission candidate symbol vector calculating means for calculating a first transmission candidate symbol vectors by performing a hierarchical decision feedback equalization (HDFE) according to a channel signal and a reception signal; second transmission candidate symbol vector calculating means for calculating a second transmission candidate symbol vectors by performing the HDFE accordi ng to the channel signal and the reception signal for bits of the first transmission candidate symbol; candidate symbol vector element order altering means for rearranging a location of each element in the reverse of a permutation which is applied to a channel matrix for the calculated symbol vectors; and log likelihood ratio (LLR) calculation means for calculating the LLR for all λ by using the calculated symbol vectors to input into a channel decoder.

[14] The soft-decision information generated system of claim 13, wherein the first transmission candidate symbol vector calculating means includes: a channel estimator for calculating H by determining and rearranging the order of a column vectors of H according to a specific permutation in the reception signal received in a radio signal (RF) receiver and a channel matrix H which is given in the channel signal;

H column vector order permutation means for defining a matrix in which the location of the column vectors of the channel matrix H which is given by the determined specific permutation is changed as H';

QR calculation means for performing a QR decomposition for the matrix H' into QR; modification reception vector generation means for calculating a reception vector z which is modified by multiplying the reception signal vector by Q^H that is a Hermitian matrix of Q after the performing the QR decomposition; Euclidean distance calculation means for selecting points of C(l≤C≤M) among all available points on the M-ary constellation which can be received through the element located in the lowest position among the calculated vectors; and HDFE performing means for applying a decision feedback equalization (DFE) detecting scheme after performing a cancellation of interference from the reception vector z modified for the selected each point as a candidate symbol, and calculating a candidate symbol vector

(l=l,...,C) of C(l≤C≤M).

[15] The soft-decision information generated system of claim 13, wherein the second transmission candidate symbol vector calculating means includes: candidate symbol vector arrangement means for selecting a candidate symbol vector

(1=1,...,L) of L according to a specific standard among candidate symbol vectors

a/

(1=1,...,C) as the first transmission candidate symbol vector; bit calculating means for selecting one candidate symbol vector

^Sl according to a specific standard among the selected candidate symbol vectors and calculating bit of K(0≤K<Tlog M) among corresponding bits; and modified hierarchical decision feedback equalization (MHDFE) performing means for performing interference cancellation of z by using

a/

(1=1,...,L) in the candidate symbol vector

, -i T SL i,₁ = [5[ Ci₂ a_T \

(1=1,...,L) selected by each bit location, and calculating a candidate symbol vector

(1=1,..., J) of J(O≤J≤LK) by applying the decision feedback equalization (DFE) detecting scheme so as to calculate the candidate symbol vectors corresponding to inverted bits for the calculated bits.

[16] A method for generation a Soft-decision information, the method comprising the steps of: calculating first transmission candidate symbols by performing a hierarchical decision feedback equalization (HDFE) according to a channel signal and a reception signal; calculating second transmission candidate symbols by performing the hierarchical decision feedback equalization method (HDFE) according to the channel signal and the reception signal for bits of the first transmission candidate symbols; and calculating a log likelihood ratio (LLR) for bits of transmission symbol by using the first transmission candidate symbols and the second transmission candidate symbols. [17] The method of claim 16, wherein the bits of the transmission candidate symbol correspond to bits having a possibility that the LLR is not defined. [18] The method of claim 16, wherein the calculating the first transmission candidate symbols further comprises step of selecting candidate symbols of L which minimize a Euclidean distance with the reception signal from a transmission candidate symbols of C.