WO2019127934A1 - 一种qr分解—并行干扰抵消检测方法和装置 - Google Patents

一种qr分解—并行干扰抵消检测方法和装置 Download PDF

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WO2019127934A1
WO2019127934A1 PCT/CN2018/079742 CN2018079742W WO2019127934A1 WO 2019127934 A1 WO2019127934 A1 WO 2019127934A1 CN 2018079742 W CN2018079742 W CN 2018079742W WO 2019127934 A1 WO2019127934 A1 WO 2019127934A1
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matrix
sequence
decomposition
input signal
estimated value
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French (fr)
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刘若鹏
季春霖
尤琳
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深圳超级数据链技术有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/02—Amplitude-modulated carrier systems, e.g. using on-off keying; Single sideband or vestigial sideband modulation
    • H04L27/06—Demodulator circuits; Receiver circuits

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  • the present invention relates to the field of communications, and in particular to a QR decomposition-parallel interference cancellation detection method and apparatus.
  • An overlapping multiplexing system (OvXDM system, where X can represent time T, frequency F, code division C, space S, or hybrid H, etc.) commonly used decoding methods include Viterbi decoding, etc., and the decoding method is based on graphics Decoding, complexity is affected by the number of states. Therefore, for the overlap multiplexing system, when the number of overlapping multiplexing times K is large, the decoding complexity increases exponentially and requires a large storage capacity, which makes it difficult to implement in actual engineering.
  • the present invention proposes a QR decomposition-parallel interference cancellation detection method for an overlap multiplexing system.
  • a QR decomposition-parallel interference cancellation detection method is provided.
  • the QR decomposition-parallel interference cancellation detection method includes: Step S1, acquiring a reception sequence, wherein the reception sequence is a sequence obtained by encoding and modulating an input signal according to a multiplexed waveform matrix and passing through a Gaussian channel; and step S2, adopting a QR decomposition algorithm and The parallel interference cancellation algorithm detects the received sequence, wherein step S2 includes: step S21, estimating the input signal according to the QR decomposition algorithm and the received sequence, to obtain a first estimated value; and step S22, according to the predicted multiplexing waveform matrix and a first estimated value, removing the interference signal on the received sequence, leaving only the received signal corresponding to the input signal to be detected; and step S23, re-estimating the input signal to be detected according to the received signal and the predicted multiplexed waveform matrix, To obtain the second estimated value; step S22 to step 23 are performed cyclically until all the input signals are estimated, and then the loop is stopped.
  • the reception sequence is:
  • H is the predicted multiplexed waveform matrix
  • X is the input signal
  • n is the Gaussian white noise sequence.
  • the input signal is estimated according to the QR decomposition algorithm and the received sequence, and the first estimated value is obtained:
  • y is a data sequence
  • R is an upper triangular matrix
  • ⁇ is a Gaussian white noise sequence
  • a first estimated value is obtained, wherein the first estimated value is:
  • a first estimated value corresponding to the kth element x k in the input signal R k,k is an element of the kth row and the kth column in the upper triangular matrix
  • Is the conjugate of R k,k , L is the length of the sequence to be transmitted
  • R k,p is the element of the kth row and the pth column in the upper triangular matrix
  • x' p is the hard corresponding to the element x p in the input signal Judgment value.
  • the interference signal on the received sequence is removed according to the predicted multiplexing waveform matrix and the first estimated value, and only the received signal corresponding to the input signal to be detected includes:
  • the received signal is:
  • (H) j is the jth column of the predicted multiplexing waveform matrix H.
  • re-estimating the input signal to be detected according to the received signal and the predicted multiplexed waveform matrix to obtain the second estimated value includes:
  • the zeroing matrix corresponding to the input signal to be detected is calculated by a zero-forcing algorithm or a minimum mean square error algorithm, wherein the zero-setting matrix is:
  • G k is a zeroing matrix
  • H k is the kth column of the predicted multiplexed waveform matrix H
  • ⁇ 2 is the noise power
  • the method further includes:
  • the second estimated value corresponding to the kth element x k of the input signal to be detected is the second estimated value corresponding to the kth element x k of the input signal to be detected.
  • a QR decomposition-parallel interference cancellation detecting apparatus is provided.
  • the QR decomposition-parallel interference cancellation detection apparatus includes: an acquisition module, configured to acquire a reception sequence, wherein the reception sequence is a sequence obtained by encoding and modulating an input signal according to a multiplexed waveform matrix through a Gaussian channel; and the detection module adopts QR decomposition The algorithm and the parallel interference cancellation algorithm detect the received sequence, wherein the detecting module comprises: a first estimating module, configured to estimate the input signal according to the QR decomposition algorithm and the receiving sequence to obtain a first estimated value; and the removing module is configured to: And removing the interference signal on the received sequence according to the predicted multiplexing waveform matrix and the first estimated value, leaving only the received signal corresponding to the input signal to be detected; and the second estimating module, according to the received signal and the predicted multiplexing waveform matrix, The input signal to be detected is re-estimated to obtain a second estimated value; a loop module is used to recycle the removal module and the second estimation module until all the input signals are estimated, and then the loop is stopped.
  • the receiving sequence is:
  • H is the predicted multiplexed waveform matrix
  • X is the input signal
  • n is the Gaussian white noise sequence.
  • the first estimating module comprises:
  • the decomposition obtaining module is configured to decompose the predicted multiplexed waveform matrix into an emirate matrix and an upper triangular matrix, and perform matrix multiplication processing on the received sequence according to the characteristics of the emirate matrix to obtain a data sequence, wherein the data sequence is:
  • y is a data sequence
  • R is an upper triangular matrix
  • ⁇ is a Gaussian white noise sequence
  • a first estimation submodule configured to obtain a first estimated value according to the data sequence and the upper triangular matrix, wherein the first estimated value is:
  • a first estimated value corresponding to the kth element x k in the input signal R k,k is an element of the kth row and the kth column in the upper triangular matrix
  • Is the conjugate of R k,k , L is the length of the sequence to be transmitted
  • R k,p is the element of the kth row and the pth column in the upper triangular matrix
  • x' p is the hard corresponding to the element x p in the input signal Judgment value.
  • the removing module comprises:
  • (H) j is the jth column of the predicted multiplexing waveform matrix H.
  • the second estimating module comprises:
  • the calculating module is configured to calculate, according to the predicted multiplexing waveform matrix, a zero-setting matrix corresponding to the input signal to be detected by using a zero-forcing algorithm or a minimum mean square error algorithm, wherein the zero-setting matrix is:
  • G k is a zeroing matrix
  • H k is the kth column of the predicted multiplexed waveform matrix H
  • ⁇ 2 is the noise power
  • the method further includes:
  • the second estimated value corresponding to the kth element x k of the input signal to be detected is the second estimated value corresponding to the kth element x k of the input signal to be detected.
  • the invention solves the traditional decoding method, such as Viterbi, by utilizing the coding characteristics of the overlapping multiplexing system, combined with the QR decomposition detection method and the parallel interference cancellation detection method in the multi-antenna system, and correspondingly decoding the transmission data.
  • the decoding, MAP, and Log-MAP methods have large computational complexity and high complexity, and require large storage capacity, which is difficult to implement in engineering, thereby reducing the decoding complexity of the overlapping multiplexing system.
  • FIG. 1 is a flow chart of an optional QR decomposition-parallel interference cancellation detection method according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram of a convolutional coding equivalent model of an alternative overlapping multiplexing system in accordance with an embodiment of the present invention
  • FIG. 3 is a flow chart of an alternative QR decomposition-parallel interference cancellation detection method in accordance with an embodiment of the present invention
  • FIG. 4 is a block diagram of a coding end of a feasible overlapping time division multiplexing system according to an embodiment of the present invention
  • FIG. 5 is a K-way multiplexed waveform arrangement of an optional overlapping time division multiplexing system according to an embodiment of the present invention
  • FIG. 6 is a block diagram of an optional transmit-frequency multiplexing system of an overlapping frequency division multiplexing system according to an embodiment of the present invention.
  • FIG. 8 is a block diagram of a receiving end of an optional overlapping time division multiplexing system in accordance with an embodiment of the present invention.
  • FIG. 9 is a block diagram of a receiving end of an optional overlapping frequency division multiplexing system according to an embodiment of the present invention.
  • FIG. 10 is a block diagram of an alternative QR decomposition-parallel interference cancellation detection apparatus in accordance with an embodiment of the present invention.
  • a QR decomposition-parallel interference cancellation detection method is provided, which is used for an overlapping multiplexing system.
  • a QR decomposition-parallel interference cancellation detection method includes: Step S101: Acquire a reception sequence, wherein the reception sequence is obtained by encoding and modulating an input signal according to a multiplexed waveform matrix, and then obtaining a Gaussian channel.
  • Step S103 detecting the received sequence by using a QR decomposition algorithm and a parallel interference cancellation algorithm, wherein step S103 includes: Step S105, estimating the input signal according to the QR decomposition algorithm and the received sequence, to obtain a first estimated value; Step S107, according to the predicted multiplexing waveform matrix and the first estimated value, removing the interference signal on the received sequence, leaving only the received signal corresponding to the input signal to be detected; and step S109, according to the received signal and the predicted multiplexing waveform matrix.
  • the input signal to be detected is re-estimated to obtain a second estimated value; in step S111, steps S107 to 109 are performed cyclically until all the input signals are estimated, and then the loop is stopped.
  • the transmission data is correspondingly decoded, thereby solving the conventional decoding.
  • Methods such as Viterbi decoding, MAP, Log-MAP methods, which have large computational complexity and high complexity, require large storage capacity, and are difficult to implement in engineering, thereby reducing the decoding of overlapping multiplexing systems. the complexity.
  • the technical solution of the present invention is applicable to an overlapping multiplexing system, which can be represented as an Overlapped Time Division Multiplexing (OvTDM) system, an Overlapped Frequency Division Multiplexing (OvFDM) system, and an overlap.
  • Overlapped Code Division Multiplexing (OvCDM) system Overlapped Space Division Multiplexing (OvSDM) system, Overlapped Hybrid Division Multiplexing (OvHDM) system, etc.
  • Figure 2 shows.
  • an overlapping multiplexing system will be described below as an example.
  • the overlap multiplexing coefficient is K
  • the tap coefficients of the multiplexed waveform are defined as [h 0 , h 1 , ..., h K-1 ], respectively.
  • the waveform is multiplexed. H can be expressed in matrix form as:
  • the receiving sequence r can be expressed as:
  • the receiving end performs corresponding decoding according to the known multiplexed waveform matrix H and the received sequence r.
  • H represents a channel parameter matrix
  • a multiplexed waveform matrix is represented.
  • the multi-antenna detection algorithm includes traditional detection algorithms, such as least squares detection algorithm, minimum mean square error detection, maximum likelihood detection, serial interference cancellation detection, and QR decomposition. Since the two structures are similar, the detection algorithm can be used. It is used to correspondingly decode the data of the overlapping multiplexed system.
  • the present invention mainly introduces the QR decomposition-parallel interference cancellation detection algorithm for the data detection of the overlapping multiplexing system, and the rest is not described herein.
  • QR decomposition is the product of decomposing a matrix into a unitary matrix and an upper triangular matrix.
  • the QR algorithm simplifies the linear zero-forcing algorithm and on the other hand enhances the stability of the algorithm.
  • the QR decomposition algorithm performs QR decomposition on the multiplexed waveform matrix H compared to the conventional detection algorithm, such as zero-forcing detection, which can reduce the detection complexity accordingly.
  • the conventional detection algorithm such as zero-forcing detection
  • the kth element y k of the reception vector is:
  • the soft decision estimate for x k is:
  • R k,p represents the (k,p) elements of the matrix R
  • x' p is a hard decision of x p
  • Soft judgment for x k Is the conjugate of R k,k .
  • the x L is detected first, and finally x 1 is detected.
  • the parallel interference cancellation algorithm uses parallel processing to perform interference cancellation between symbols. On the basis of the initial estimated value of the input signal X, each input signal is restored. In the process of determining the signal, no sorting is required, but directly A decision signal is made.
  • the specific method is: constructing the interference signal estimation of the transmitted symbol by using the detection result (initial estimation value), and recovering the influence of the remaining input signals as interference when restoring an input signal, that is, when recovering the kth signal , the first, second, Across k-1th, k+1th, .... the Lth signal is cancelled as interference, a new reception vector is obtained, and then the output is judged k signals.
  • the detection algorithm combines QR decomposition detection, namely QR decomposition and parallel interference cancellation algorithm, and the specific detection steps are as follows:
  • Step 1 According to the received signal r, the waveform matrix H is multiplexed, and the input signal X is initially estimated, that is, the QR decomposition detection and estimation (as described above) is performed first, and the corresponding estimate is obtained. among them Is the estimated value of the input signal x k .
  • Step 2 The expression of the received signal after interference suppression is:
  • Step 3 Calculate the zeroing matrix G k , which can be the zero-setting matrix corresponding to the zero-forcing detection, or the zero-setting matrix corresponding to the minimum mean square error detection, namely:
  • H k represents the kth column of the matrix H
  • ⁇ 2 is the noise power
  • the detection algorithm replaces the decoding method in the existing overlapping multiplexing system, and the corresponding overlapping multiplexing system encoding processing process is as follows:
  • the waveform is shifted at a predetermined shift interval in the modulation domain to obtain respective shifted envelope waveforms in the modulation domain;
  • the shifted envelope waveform is written in a matrix form and multiplied by the symbols in the sequence to be modulated to obtain a complex modulation envelope waveform in the modulation domain.
  • the OvTDM system transmitting end encoding processing block diagram is shown in FIG. 4, and the overlapping multiplexing method follows the parallelogram rule, as shown in FIG. 5.
  • the OvFDM system transmitting end encoding processing block diagram is shown in FIG. 6, and the overlapping multiplexing method follows the parallelogram rule, as shown in FIG.
  • the preprocessing process includes: performing synchronization, channel estimation, equalization processing, and the like on the signal received by the receiving end;
  • the receiving end processing process is as shown in FIG. 8, and the specific steps are as follows:
  • the received signal is synchronized, including carrier synchronization, frame synchronization, symbol time synchronization, etc.;
  • the receiving end processing process is as shown in FIG. 9, and the specific steps are as follows:
  • a QR decomposition-parallel interference cancellation detecting apparatus is also provided.
  • the QR decomposition-parallel interference cancellation detecting apparatus includes: an obtaining module 101, configured to acquire a receiving sequence, wherein the receiving sequence encodes and modulates an input signal according to a multiplexed waveform matrix.
  • the detection module 103 detects the received sequence by using a QR decomposition algorithm and a parallel interference cancellation algorithm, wherein the detection module 103 includes: a first estimation module 105, configured to input the input according to the QR decomposition algorithm and the received sequence The signal is estimated to obtain a first estimated value; the removing module 107 is configured to remove the interference signal on the received sequence according to the predicted multiplexed waveform matrix and the first estimated value, leaving only the received signal corresponding to the input signal to be detected; The second estimating module 109, according to the received signal and the predicted multiplexed waveform matrix, re-estimating the input signal to be detected to obtain a second estimated value; the looping module 111 is configured to recycle the removing module and the second estimating module, The cycle is stopped until all input signals are estimated.
  • the receiving sequence is:
  • H is the predicted multiplexed waveform matrix
  • X is the input signal
  • n is the Gaussian white noise sequence.
  • the first estimating module 105 comprises:
  • a decomposition obtaining module (not shown) for decomposing the predicted multiplexed waveform matrix into an emirate matrix and an upper triangular matrix, and performing matrix multiplication processing on the received sequence according to the characteristics of the emirate matrix to obtain a data sequence, wherein
  • the data sequence is:
  • y is a data sequence
  • R is an upper triangular matrix
  • ⁇ is a Gaussian white noise sequence
  • a first estimation sub-module for obtaining a first estimated value according to the data sequence and the upper triangular matrix, wherein the first estimated value is:
  • a first estimated value corresponding to the kth element x k in the input signal R k,k is an element of the kth row and the kth column in the upper triangular matrix
  • Is the conjugate of R k,k , L is the length of the sequence to be transmitted
  • R k,p is the element of the kth row and the pth column in the upper triangular matrix
  • x' p is the hard corresponding to the element x p in the input signal Judgment value.
  • the removal module 107 comprises:
  • (H) j is the jth column of the predicted multiplexing waveform matrix H.
  • the second estimating module 109 comprises:
  • a calculation module (not shown) is configured to calculate a zeroing matrix corresponding to the input signal to be detected by a zero-forcing algorithm or a minimum mean square error algorithm according to the predicted multiplexing waveform matrix, wherein the zeroing matrix is:
  • G k is a zeroing matrix
  • H k is the kth column of the predicted multiplexed waveform matrix H
  • ⁇ 2 is the noise power
  • the method further includes:
  • the second estimated value corresponding to the kth element x k of the input signal to be detected is the second estimated value corresponding to the kth element x k of the input signal to be detected.
  • the coding characteristics of the overlapping multiplexing system are utilized, and the QR decomposition detection method and the parallel interference cancellation detection method in the multi-antenna system are used to decode the transmission data accordingly, thereby
  • the traditional decoding method is solved, such as Viterbi decoding, MAP, Log-MAP method, which has large computational complexity and high complexity, and requires large storage capacity, which is difficult to implement in engineering, thereby reducing overlap.
  • the decoding complexity of the multiplexing system is solved, such as Viterbi decoding, MAP, Log-MAP method, which has large computational complexity and high complexity, and requires large storage capacity, which is difficult to implement in engineering, thereby reducing overlap.

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Abstract

本发明公开了一种基于重叠复用的QR分解—并行干扰抵消检测方法和装置，该QR分解—并行干扰抵消检测方法包括：步骤S1，获取接收序列，其中，接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；步骤S2，采用QR分解算法和并行干扰抵消算法对接收序列进行检测。本发明通过上述技术方案，降低了重叠复用系统的译码复杂度。

Description

一种QR分解—并行干扰抵消检测方法和装置 技术领域
本发明涉及通信领域，具体来说，涉及一种QR分解—并行干扰抵消检测方法和装置。
背景技术
重叠复用系统(OvXDM系统，其中，X可代表时间T、频率F、码分C、空间S或混合H等)中常用的译码方法包括维特比译码等，其译码方法是基于图形译码，复杂度受状态数影响。因此，对于重叠复用系统而言，当重叠复用次数K较大时，其译码复杂度呈指数率增长，且需要较大的存储容量，使得实际工程中较难实现。
针对相关技术中的问题，目前尚未提出有效的解决方案。
发明内容
针对相关技术中的问题，本发明提出一种QR分解—并行干扰抵消检测方法，该QR分解—并行干扰抵消检测方法用于重叠复用系统。
本发明的技术方案是这样实现的：
根据本发明的一个方面，提供了一种QR分解—并行干扰抵消检测方法。
该QR分解—并行干扰抵消检测方法包括：步骤S1，获取接收序列，其中，接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；步骤S2，采用QR分解算法和并行干扰抵消算法对接收序列进行检测，其中，步骤S2包括：步骤S21，根据QR分解算法和接收序列，对输入信号进行估计，得到第一估计值；步骤S22，根据预知的复用波形矩阵和第一估计值，去除接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号；步骤S23，根据接收信号和预知的复用波形矩 阵，对需检测的输入信号进行再次估计，以得到第二估计值；循环执行步骤S22至步骤23，直至所有的输入信号均被估计出，则停止循环。
根据本发明的一个实施例，QR分解—并行干扰抵消检测方法中，接收序列为：
r＝HX+n
其中，r为接收序列，H为预知的复用波形矩阵，X为输入信号，n为高斯白噪声序列。
根据本发明的一个实施例，根据QR分解算法和接收序列，对输入信号进行估计，得到第一估计值包括：
将预知的复用波形矩阵分解为一个酋矩阵和一个上三角矩阵，以及根据酋矩阵特性，对接收序列进行矩阵相乘处理，获得数据序列，其中，数据序列为：
y＝RX+η
其中，y为数据序列，R为上三角矩阵，η为高斯白噪声序列；
根据数据序列和上三角矩阵，得到第一估计值，其中，第一估计值为：
Figure PCTCN2018079742-appb-000001
其中，
Figure PCTCN2018079742-appb-000002
为输入信号中的第k个元素x k对应的第一估计值，R k,k为上三角矩阵中的第k行第k列的元素，
Figure PCTCN2018079742-appb-000003
为R k,k的共轭，L为待发送序列的长度，R k,p为上三角矩阵中的第k行第p列的元素，x' p为输入信号中的元素x p对应的硬判决值。
根据本发明的一个实施例，根据预知的复用波形矩阵和第一估计值，去除接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号包括：
根据预知的复用波形矩阵和第一估计值，将除了需检测的输入信号以外的其他信号去除，从而去除接收序列上的干扰信号，从而得到只留下需检测的输入信号对应的接收信号，其中，接收信号为：
Figure PCTCN2018079742-appb-000004
其中，r k为接收信号，r为接收序列，
Figure PCTCN2018079742-appb-000005
为第一估计值中的第j个元素，(H) j为预知的复用波形矩阵H的第j列。
根据本发明的一个实施例，根据接收信号和预知的复用波形矩阵，对需检测的输入信号进行再次估计，以得到第二估计值包括：
根据预知的复用波形矩阵，通过迫零算法或最小均方误差算法，计算需检测的输入信号对应的置零矩阵，其中，置零矩阵为：
G k＝(H k HH k) -1H k H，或G k＝(H k HH k+σ 2) -1H k H，
其中，G k为置零矩阵，H k为预知的复用波形矩阵H的第k列，σ 2为噪声功率。
根据本发明的一个实施例，还包括：
Figure PCTCN2018079742-appb-000006
Figure PCTCN2018079742-appb-000007
为需检测的输入信号第k个元素x k对应的第二估计值。
根据本发明的另一方面，提供了一种QR分解—并行干扰抵消检测装置。
该QR分解—并行干扰抵消检测装置包括：获取模块，用于获取接收序列，其中，接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；检测模块，采用QR分解算法和并行干扰抵消算法对接收序列进行检测，其中，检测模块包括：第一估计模块，用于根据QR分解算法和接收序列，对输入信号进行估计，得到第一估计值；去除模块，用于根据预知的复用波形矩阵和第一估计值，去除接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号；第二估计模块，根据接收信号和预知的复用波形矩阵，对需检测的输入信号进行再次估计，以得到第二估计值；循环模块，用于循环利用去除模块和第二估计模块，直至所有的输入信号均被估计出，则停止循环。
根据本发明的一个实施例，接收序列为：
r＝HX+n
其中，r为接收序列，H为预知的复用波形矩阵，X为输入信号，n为高斯白噪声序列。
根据本发明的一个实施例，第一估计模块包括：
分解获得模块，用于将预知的复用波形矩阵分解为一个酋矩阵和一个上三角矩阵，以及根据酋矩阵特性，对接收序列进行矩阵相乘处理，获得数据序列，其中，数据序列为：
y＝RX+η
其中，y为数据序列，R为上三角矩阵，η为高斯白噪声序列；
第一估计子模块，用于根据数据序列和上三角矩阵，得到第一估计值，其中，第一估计值为：
Figure PCTCN2018079742-appb-000008
其中，
Figure PCTCN2018079742-appb-000009
为输入信号中的第k个元素x k对应的第一估计值，R k,k为上三角矩阵中的第k行第k列的元素，
Figure PCTCN2018079742-appb-000010
为R k,k的共轭，L为待发送序列的长度，R k,p为上三角矩阵中的第k行第p列的元素，x' p为输入信号中的元素x p对应的硬判决值。
根据本发明的一个实施例，去除模块包括：
去除子模块，用于根据预知的复用波形矩阵和第一估计值，将除了需检测的输入信号以外的其他信号去除，从而去除接收序列上的干扰信号，从而得到只留下需检测的输入信号对应的接收信号，其中，接收信号为：
Figure PCTCN2018079742-appb-000011
其中，r k为接收信号，r为接收序列，
Figure PCTCN2018079742-appb-000012
为第一估计值中的第j个元素，(H) j为预知的复用波形矩阵H的第j列。
根据本发明的一个实施例，第二估计模块包括：
计算模块，用于根据预知的复用波形矩阵，通过迫零算法或最小均方误差算法，计算需检测的输入信号对应的置零矩阵，其中，置零矩阵为：
G k＝(H k HH k) -1H k H，或G k＝(H k HH k+σ 2) -1H k H，
其中，G k为置零矩阵，H k为预知的复用波形矩阵H的第k列，σ 2为噪声功率。
根据本发明的一个实施例，还包括：
Figure PCTCN2018079742-appb-000013
Figure PCTCN2018079742-appb-000014
为需检测的输入信号第k个元素x k对应的第二估计值。
本发明的有益技术效果在于：
本发明通过利用重叠复用系统的编码特性，并结合多天线系统中的QR分解检测方法和并行干扰抵消检测方法，对传输数据进行相应译码，从而解决了传统的译码方法，如维特比等译码、MAP、Log-MAP方法，其计算量较大和复杂度较高，且需要较大的存储容量，工程难以实现的问题，从而降低了重叠复用系统的译码复杂度。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是根据本发明实施例的一种可选的QR分解—并行干扰抵消检测方法的流程图；
图2是根据本发明实施例的一种可选的重叠复用系统的卷积编码等效模型的示意图；
图3是根据本发明具体实施例的一种可选的QR分解—并行干扰抵消检测方法的流程图；
图4是根据本发明实施例的一种可行的重叠时分复用系统的发送端编码框图；
图5是根据本发明实施例的一种可选的重叠时分复用系统的K路复用波形排列；
图6是根据本发明实施例的一种可选的重叠频分复用系统发送端编码框图
图7是根据本发明实施例的一种可选的重叠频分复用系统的K路复用波形排列；
图8是根据本发明实施例的一种可选的重叠时分复用系统的接收端框图；
图9是根据本发明实施例的一种可选的重叠频分复用系统的接收端框图；
图10是根据本发明实施例的一种可选的QR分解—并行干扰抵消检测装置的框图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员所获得的所有其他实施例，都属于本发明保护的范围。
根据本发明的实施例，提供了一种QR分解—并行干扰抵消检测方法，该QR分解—并行干扰抵消检测方法用于重叠复用系统。
如图1所示，根据本发明实施例的QR分解—并行干扰抵消检测方法包括：步骤S101，获取接收序列，其中，接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；步骤S103，采用QR分解算法和并行干扰抵消算法对接收序列进行检测，其中，步骤S103包括：步骤S105，根据QR分解算法和接收序列，对输入信号进行估计，得到第一估计值；步骤S107，根据预知的复用波形矩阵和第一估计值，去除接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号；步骤S109，根据接收信号和预知的复用波形矩阵，对需检测的输入信号进行再次估计，以得到第二估计值；步骤S111，循环执行步骤S107至步骤109，直至所有的输入信号均被估计出，则停止循环。
借助于上述区别技术特征，通过利用重叠复用系统的编码特性，并结合多天线系统中的QR分解检测方法和并行干扰抵消检测方法，对传输数据进行相应译码，从而解决了传统的译码方法，如维特比等译码、MAP、Log-MAP方法，其计算量较大和复杂度较高，且需要较大的存储容量，工程难以实现的问题，从而降低了重叠复用系统的译码复杂度。
为了更好的描述本发明，下面通过具体的实施例对上述技术方案进行详细的描述。
本发明的技术方案适用于重叠复用系统，该重叠复用系统可表示为重叠时分复用(Overlapped Time Division Multiplexing，OvTDM)系统、重叠频分复用(Overlapped Frequency Division Multiplexing，OvFDM)系统、重叠码分复用(Overlapped Code Division Multiplexing，OvCDM)系统、重叠空分复用(Overlapped Space Division Multiplexing，OvSDM)系统、重叠混合复用(Overlapped Hybrid Division Multiplexing，OvHDM)系统等，其系统等效模型如附图2所示。为了更好的描述本发明的技术方案，下面以重叠复用系统为例进行说明。
此外，根据重叠复用系统的编码特性，首先，假设重叠复用系数为K，复用波形的抽头系数分别定义为[h 0,h 1,…,h K-1]。此时，根据重叠复用关系的卷积特性，若设实信息比特序列长度为L，重叠复用系统编码后比特序列为N，其中N＝L+K-1，则此时，复用波形H可用矩阵形式表示为：
Figure PCTCN2018079742-appb-000015
并且该复用波形矩阵的大小为N×L。
另外，设重叠复用系统编码后的输出向量为Y＝[y 0,…,y N-1] T，输入向量为X＝[x 1,…,x L-1] T，则重叠复用系统的编码过程可表示为Y＝HX，即：
Figure PCTCN2018079742-appb-000016
则此时，接收序列r可表示为：
Figure PCTCN2018079742-appb-000017
其中，[n 0,n 1,…,n N-1] T为白噪声序列。
此外，接收端根据已知的复用波形矩阵H和接收序列r，进行相应译码。上述接收序列r与多天线接收序列结构模型相似，均为r＝HX+n，其中X为待传送序列，n为白噪声序列，r为接收序列，不同之处在于矩阵H所代表不同：在多天线系统中H表示信道参数矩阵，而在重叠复用系统中则表示复用波形矩阵。同时，多天线检测算法包含传统的检测算法，如最小二乘检测算法、最小均方误差检测、最大似然检测以及串行干扰抵消检测、QR分解，由于两者结构相似，因而可将检测算法用于对重叠复用系统数据进行相应译码。
另外，本发明主要介绍将QR分解—并行干扰抵消检测算法用于重叠复用系统数据检测中，其余在此不赘述。
首先，QR分解是将矩阵分解为一个酉矩阵和一个上三角矩阵的乘积。QR算法一方面简化了线性迫零的算法，另一方面也增强了算法的稳定性。将复用波形矩阵H的QR分解为：
H＝QR
其中，Q为N×L的酉矩阵，满足Q HQ＝I L，R是L×L的上三角矩阵，如下所示：
Figure PCTCN2018079742-appb-000018
利用QR分解算法对复用波形矩阵H进行QR分解相比于传统的检测算法，如迫零检测，可以相应降低检测复杂度。同时，利用r＝HX+N，可化简得到下式：
Figure PCTCN2018079742-appb-000019
此外，还可将上式可以得到另一种形式：
Figure PCTCN2018079742-appb-000020
从而，根据上述，可确定接收矢量第k个元素y k为：
y k＝R k,k·x k+η k+d k，
其中
Figure PCTCN2018079742-appb-000021
x k的软判决估计值为：
Figure PCTCN2018079742-appb-000022
其中，
Figure PCTCN2018079742-appb-000023
其中，R k,p代表矩阵R的(k，p)个元素，x' p是x p的硬判决，
Figure PCTCN2018079742-appb-000024
为x k的软判决，
Figure PCTCN2018079742-appb-000025
为R k,k的共轭。先对x L进行检测，最后检测x 1。
此外，而并行干扰抵消算法采用并行处理的方式进行符号间的干扰消除，在输入信号X初始估计值的基础上，恢复各输入信号，在判决信号的过程中，不需进行排序，而是直接进行判决信号。具体做法是：利用检测结果(初始估计值)构造所发送符号的干扰信号估计，在恢复某个输入信号时，都要把其余输入信号的影响作为干扰抵消掉，即在恢复第k个信号时，把第1个，第2个，.....第k-1个，第k+1个，....第L个信号作为干扰抵消掉，得到新的接收向量，然后判决输出第k个信号。该检测算法结合QR分解检测，即QR分解和并行干扰抵消算法，其具体检测步骤如下所示：
第一步：根据接收信号r，复用波形矩阵H，对输入信号X进行初始估计,也即先进行QR分解检测估计(如上所述)，得到相应的估值
Figure PCTCN2018079742-appb-000026
其 中
Figure PCTCN2018079742-appb-000027
为输入信号x k的估计值。
第二步：接收到的信号经过干扰抑制后的表达式为：
Figure PCTCN2018079742-appb-000028
其中，(H) j表示取H的第j列。从上式可看出在接收到的信号中，将其他所有层的干扰信号都去除了，只留下想要检测的接收信号。
第三步：计算置零矩阵G k，可以为迫零检测对应的置零矩阵，也可为最小均方误差检测对应的置零矩阵，即：
G k＝(H k HH k) -1H k H或G k＝(H k HH k+σ 2) -1H k H
其中，H k表示的是取矩阵H的第k列，σ 2为噪声功率，最后得到检测为：
Figure PCTCN2018079742-appb-000029
循环上述过程，直至所有输入信号均被检测，如附图3所示。
此外，为了更好的理解本发明的技术方案，下面通过具体的实施例进行详细的描述。
将该检测算法替代现有的重叠复用系统中的译码方法，对应的重叠复用系统编码处理过程如下所示：
根据设计参数在调制域内生成包络波形；
波形在调制域内按预定的移位间隔进行移位，得到调制域内的各移位包络波形；
将移位包络波形写成矩阵形式，再与待调制序列中的符号相乘，得到调制域内的复调制包络波形。
此外，下面以OvTDM系统为例，其发送端编码具体处理步骤如下：
(1)首先设计生成发送信号的包络波形h(t)；
(2)将(1)中所设计的包络波形h(t)经特定时间移位后，形成其它各个时刻发送信号包络波形h(t-i×ΔT)。
(3)将包络波形h(t-i×ΔT)写成复用波形矩阵H形式，然后与所要发送的符号向量x相乘，形成发射信号波形。
其中，OvTDM系统发送端编码处理框图如附图4所示，重叠复用方法遵循平行四边形规则，如附图5所示。
另外，以OvFDM系统为例，其发送端系统编码具体处理步骤如下：
(1)首先设计生成发送信号的频谱信号H(f)。
(2)将(1)所设计的谱信号H(f)经特定载波频谱间隔ΔB移位后，形成其它各个频谱间隔为ΔB的子载波频谱波形H(f-i×ΔB)。
(3)将频谱波形H(f-i×ΔB)写成矩阵H形式，然后与所要发送的符号向量x相乘，形成复调制信号的频谱S(f)。
(4)将(3)生成的复调制信号的频谱进行离散傅氏反变换，最终形成时间域的复调制信号，发送信号可表示为：
Signal(t) TX＝ifft(S(f))
其中，OvFDM系统发送端编码处理框图如附图6所示，重叠复用方法遵循平行四边形规则，如附图7所示。
此外，重叠复用系统的接收端处理过程：
对接收端接收到的信号进行预处理，得到预处理的信号；
对所述预处理信号在对应域内按照上述QR分解—并行干扰抵消检测算法进行信号检测，得到输入的信息流；
其中所述预处理过程包括：对接收端接收到的信号进行同步、信道估计、均衡处理等运算；
此外，以OvTDM系统为例，其接收端处理过程如附图8所示，具体步骤如下：
(1)首先对接收信号进行同步，包括载波同步、帧同步、符号时间同步等；
(2)按照上述检测算法对预处理后的数据进行相应检测。
另外，以OvFDM系统为例，其接收端处理过程如附图9所示，具体步骤如下：
(1)首先对接收信号进行fft(傅里叶变换)运算，使时域信号转换到频域；
(2)对频域信号进行同步，包括载波同步、帧同步、符号时间同步等；
(3)按照上述检测算法对预处理后的数据进行相应检测。
根据本发明的实施例，还提供了一种QR分解—并行干扰抵消检测装 置。
如图10所示，根据本发明实施例的QR分解—并行干扰抵消检测装置包括：获取模块101，用于获取接收序列，其中，接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；检测模块103，采用QR分解算法和并行干扰抵消算法对接收序列进行检测，其中，检测模块103包括：第一估计模块105，用于根据QR分解算法和接收序列，对输入信号进行估计，得到第一估计值；去除模块107，用于根据预知的复用波形矩阵和第一估计值，去除接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号；第二估计模块109，根据接收信号和预知的复用波形矩阵，对需检测的输入信号进行再次估计，以得到第二估计值；循环模块111，用于循环利用去除模块和第二估计模块，直至所有的输入信号均被估计出，则停止循环。
根据本发明的一个实施例，接收序列为：
r＝HX+n
其中，r为接收序列，H为预知的复用波形矩阵，X为输入信号，n为高斯白噪声序列。
根据本发明的一个实施例，第一估计模块105包括：
分解获得模块(未示出)，用于将预知的复用波形矩阵分解为一个酋矩阵和一个上三角矩阵，以及根据酋矩阵特性，对接收序列进行矩阵相乘处理，获得数据序列，其中，数据序列为：
y＝RX+η
其中，y为数据序列，R为上三角矩阵，η为高斯白噪声序列；
第一估计子模块(未示出)，用于根据数据序列和上三角矩阵，得到第一估计值，其中，第一估计值为：
Figure PCTCN2018079742-appb-000030
其中，
Figure PCTCN2018079742-appb-000031
为输入信号中的第k个元素x k对应的第一估计值，R k,k为上三角矩阵中的第k行第k列的元素，
Figure PCTCN2018079742-appb-000032
为R k,k的共轭，L为待发送序列 的长度，R k,p为上三角矩阵中的第k行第p列的元素，x' p为输入信号中的元素x p对应的硬判决值。
根据本发明的一个实施例，去除模块107包括：
去除子模块(未示出)，用于根据预知的复用波形矩阵和第一估计值，将除了需检测的输入信号以外的其他信号去除，从而去除接收序列上的干扰信号，从而得到只留下需检测的输入信号对应的接收信号，其中，接收信号为：
Figure PCTCN2018079742-appb-000033
其中，r k为接收信号，r为接收序列，
Figure PCTCN2018079742-appb-000034
为第一估计值中的第j个元素，(H) j为预知的复用波形矩阵H的第j列。
根据本发明的一个实施例，第二估计模块109包括：
计算模块(未示出)，用于根据预知的复用波形矩阵，通过迫零算法或最小均方误差算法，计算需检测的输入信号对应的置零矩阵，其中，置零矩阵为：
G k＝(H k HH k) -1H k H，或G k＝(H k HH k+σ 2) -1H k H，
其中，G k为置零矩阵，H k为预知的复用波形矩阵H的第k列，σ 2为噪声功率。
根据本发明的一个实施例，还包括：
Figure PCTCN2018079742-appb-000035
Figure PCTCN2018079742-appb-000036
为需检测的输入信号第k个元素x k对应的第二估计值。
综上所述，借助于本发明的上述技术方案，利用重叠复用系统的编码特性，并结合多天线系统中的QR分解检测方法和并行干扰抵消检测方法，对传输数据进行相应译码，从而解决了传统的译码方法，如维特比等译码、MAP、Log-MAP方法，其计算量较大和复杂度较高，且需要较大的存储容量，工程难以实现的问题，从而降低了重叠复用系统的译码复杂度。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (12)

  1. 一种QR分解—并行干扰抵消检测方法，所述QR分解—并行干扰抵消检测方法用于重叠复用系统，其特征在于，包括：
    步骤S1，获取接收序列，其中，所述接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；
    步骤S2，采用QR分解算法和并行干扰抵消算法对所述接收序列进行检测，其中，所述步骤S2包括：
    步骤S21，根据所述QR分解算法和所述接收序列，对所述输入信号进行估计，得到第一估计值；
    步骤S22，根据预知的复用波形矩阵和所述第一估计值，去除所述接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号；
    步骤S23，根据所述接收信号和所述预知的复用波形矩阵，对所述需检测的输入信号进行再次估计，以得到第二估计值；
    步骤S24，循环执行所述步骤S22至所述步骤23，直至所有的输入信号均被估计出，则停止循环。
  2. 根据权利要求1所述的QR分解—并行干扰抵消检测方法，其特征在于，所述QR分解—并行干扰抵消检测方法中，所述接收序列为：
    r＝HX+n
    其中，r为所述接收序列，H为所述预知的复用波形矩阵，X为所述输入信号，n为高斯白噪声序列。
  3. 根据权利要求1所述的QR分解—并行干扰抵消检测方法，其特征在于，根据所述QR分解算法和所述接收序列，对所述输入信号进行估计，得到第一估计值包括：
    将所述预知的复用波形矩阵分解为一个酋矩阵和一个上三角矩阵，以及根据所述酋矩阵特性，对所述接收序列进行矩阵相乘处理，获得数据序列，其中，所述数据序列为：
    y＝RX+η
    其中，y为所述数据序列，R为所述上三角矩阵，η为高斯白噪声序列；
    根据所述数据序列和所述上三角矩阵，得到第一估计值，其中，所述第一估计值为：
    Figure PCTCN2018079742-appb-100001
    其中，
    Figure PCTCN2018079742-appb-100002
    为所述输入信号中的第k个元素x k对应的第一估计值，R k,k为所述上三角矩阵中的第k行第k列的元素，
    Figure PCTCN2018079742-appb-100003
    为所述R k,k的共轭，L为待发送序列的长度，R k,p为所述上三角矩阵中的第k行第p列的元素，x' p为所述输入信号中的元素x p对应的硬判决值。
  4. 根据权利要求1所述的QR分解—并行干扰抵消检测方法，其特征在于，根据预知的复用波形矩阵和所述第一估计值，去除所述接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号包括：
    根据所述预知的复用波形矩阵和所述第一估计值，将除了所述需检测的输入信号以外的其他信号去除，从而去除所述接收序列上的干扰信号，从而得到所述只留下需检测的输入信号对应的接收信号，其中，所述接收信号为：
    Figure PCTCN2018079742-appb-100004
    其中，r k为所述接收信号，r为所述接收序列，
    Figure PCTCN2018079742-appb-100005
    为所述第一估计值中的第j个元素，(H) j为所述预知的复用波形矩阵H的第j列。
  5. 根据权利要求1所述的QR分解—并行干扰抵消检测方法，其特征在于，根据所述接收信号和所述预知的复用波形矩阵，对所述需检测的输入信号进行再次估计，以得到第二估计值包括：
    根据所述预知的复用波形矩阵，通过迫零算法或最小均方误差算法，计算所述需检测的输入信号对应的置零矩阵，其中，所述置零矩阵为：
    G k＝(H k HH k) -1H k H，或G k＝(H k HH k+σ 2) -1H k H，
    其中，所述G k为所述置零矩阵，H k为所述预知的复用波形矩阵H的第k列，σ 2为噪声功率。
  6. 根据权利要求5所述的QR分解—并行干扰抵消检测方法，其特征在于，还包括：
    Figure PCTCN2018079742-appb-100006
    Figure PCTCN2018079742-appb-100007
    为所述需检测的输入信号第k个元素x k对应的第二估计值。
  7. 一种QR分解—并行干扰抵消检测装置，所述QR分解—并行干扰抵消检测装置用于重叠复用系统，其特征在于，包括：
    获取模块，用于获取接收序列，其中，所述接收序列是根据复用波形矩阵对输入信号进行编码调制后经过高斯信道得到的序列；
    检测模块，采用QR分解算法和并行干扰抵消算法对所述接收序列进行检测，其中，所述检测模块包括：
    第一估计模块，用于根据所述QR分解算法和所述接收序列，对所述输入信号进行估计，得到第一估计值；
    去除模块，用于根据预知的复用波形矩阵和所述第一估计值，去除所述接收序列上的干扰信号，只留下需检测的输入信号对应的接收信号；
    第二估计模块，根据所述接收信号和所述预知的复用波形矩阵，对所述需检测的输入信号进行再次估计，以得到第二估计值；
    循环模块，用于循环利用所述去除模块和所述第二估计模块，直至所有的输入信号均被估计出，则停止循环。
  8. 根据权利要求7所述的QR分解—并行干扰抵消检测装置，其特征在于，所述接收序列为：
    r＝HX+n
    其中，r为所述接收序列，H为所述预知的复用波形矩阵，X为所述输入信号，n为高斯白噪声序列。
  9. 根据权利要求7所述的QR分解—并行干扰抵消检测装置，其特征在于，所述第一估计模块包括：
    分解获得模块，用于将所述预知的复用波形矩阵分解为一个酋矩阵和一个上三角矩阵，以及根据所述酋矩阵特性，对所述接收序列进行矩阵相乘处理，获得数据序列，其中，所述数据序列为：
    y＝RX+η
    其中，y为所述数据序列，R为所述上三角矩阵，η为高斯白噪声序列；
    第一估计子模块，用于根据所述数据序列和所述上三角矩阵，得到第 一估计值，其中，所述第一估计值为：
    Figure PCTCN2018079742-appb-100008
    其中，
    Figure PCTCN2018079742-appb-100009
    为所述输入信号中的第k个元素x k对应的第一估计值，R k,k为所述上三角矩阵中的第k行第k列的元素，
    Figure PCTCN2018079742-appb-100010
    为所述R k,k的共轭，L为待发送序列的长度，R k,p为所述上三角矩阵中的第k行第p列的元素，x' p为所述输入信号中的元素x p对应的硬判决值。
  10. 根据权利要求7所述的QR分解—并行干扰抵消检测装置，其特征在于，所述去除模块包括：
    去除子模块，用于根据所述预知的复用波形矩阵和所述第一估计值，将除了所述需检测的输入信号以外的其他信号去除，从而去除所述接收序列上的干扰信号，从而得到所述只留下需检测的输入信号对应的接收信号，其中，所述接收信号为：
    Figure PCTCN2018079742-appb-100011
    其中，r k为所述接收信号，r为所述接收序列，
    Figure PCTCN2018079742-appb-100012
    为所述第一估计值中的第j个元素，(H) j为所述预知的复用波形矩阵H的第j列。
  11. 根据权利要求7所述的QR分解—并行干扰抵消检测装置，其特征在于，所述第二估计模块包括：
    计算模块，用于根据所述预知的复用波形矩阵，通过迫零算法或最小均方误差算法，计算所述需检测的输入信号对应的置零矩阵，其中，所述置零矩阵为：
    G k＝(H k HH k) -1H k H，或G k＝(H k HH k+σ 2) -1H k H，
    其中，所述G k为所述置零矩阵，H k为所述预知的复用波形矩阵H的第k列，σ 2为噪声功率。
  12. 根据权利要求11所述的QR分解—并行干扰抵消检测装置，其特征在于，还包括：
    Figure PCTCN2018079742-appb-100013
    Figure PCTCN2018079742-appb-100014
    为所述需检测的输入信号第k个元素x k对应的第二估计值。
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