Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC...Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.展开更多
An improved wavelet packet domain least mean square （IWPD-LMS） based adaptive muhiuser detection algorithm is proposed. The algorithm employs the wavelet packet transform to rewhiten the input data, and chooses the ...An improved wavelet packet domain least mean square （IWPD-LMS） based adaptive muhiuser detection algorithm is proposed. The algorithm employs the wavelet packet transform to rewhiten the input data, and chooses the best wavelet packet basis according to a novel convergence contribution function rather than the conventional Shannon entropy. The theoretic analyses show that the inadequacy of the eigenvalue spread of the tap-input correlation matrix is ameliorated, thus the convergence performance is improved greatly. The simulation result of convergence performance and bit error rate（BER） performance as a function of the signal power to noise power ratio（SNR） are presented finally to prove the validity of the proposed algorithm.展开更多
RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In s...RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.展开更多
Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework ...Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework with parallel interference cancellation, a supervision decision algorithm based on pre-decision of probabilistic data association (PDA) and hard decision is proposed. The detection performance is analyzed and simulation is implemented to show that the supervision decision algorithm improves the detection performance effectively.展开更多
To improve the computational speed, the ROLS-AWS algorithm was employed in the RBF based MUD receiver. The radial basis function was introduced into the multi-user detection （MUD） firstly. Then a three-layer neural ...To improve the computational speed, the ROLS-AWS algorithm was employed in the RBF based MUD receiver. The radial basis function was introduced into the multi-user detection （MUD） firstly. Then a three-layer neural network demodulation spread-spectrum signal model in the synchronous Gauss channel was given and the multi-user detection receiver was analyzed intensively. Simulations by computer illustrate that the proposed RBF based MUD receiver employing the ROKS-AWS algorithm is better than conventional detectors and common BP neural network based MUD receivers on suppressing multiple access interference and near-far resistance.展开更多
A graph model is constructed for the Multi-user Detection of DS-CDMA system. Based on it, a Hopfield-like algorithm is put forward for the implementation of optimum receiver. Compared with the Hopfield approach, it ha...A graph model is constructed for the Multi-user Detection of DS-CDMA system. Based on it, a Hopfield-like algorithm is put forward for the implementation of optimum receiver. Compared with the Hopfield approach, it has a higher computational complexity but better performance.展开更多
The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the...The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems.In this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two stages.The first stage estimates the channel parameters,and the second performsmulti-user detection.The proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural networks.This study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO receivers.The FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.展开更多
In the uplink grant-free non-orthogonal multiple access(NOMA)scenario,since the active user at the sender has a structured sparsity transmission characteristic,the compressive sensing recovery algorithm is initially a...In the uplink grant-free non-orthogonal multiple access(NOMA)scenario,since the active user at the sender has a structured sparsity transmission characteristic,the compressive sensing recovery algorithm is initially applied to the joint detection of the active user and the transmitted data.However,the existing compressed sensing recovery algorithms with unknown sparsity often require noise power or signal-to-noise ratio(SNR)as the priori conditions,which greatly reduces the algorithm adaptability in multi-user detection.Therefore,an algorithm based on cross validation aided structured sparsity adaptive orthogonal matching pursuit(CVA-SSAOMP)is proposed to realize multi-user detection in dynamic change communication scenario of channel state information(CSI).The proposed algorithm transforms the structured sparsity model into a block sparse model,and without the priori conditions above,the cross validation method in the field of statistics and machine learning is used to adaptively estimate the sparsity of active user through the residual update of cross validation.The simulation results show that,compared with the traditional orthogonal matching pursuit(OMP)algorithm,subspace pursuit(SP)algorithm and cross validation aided block sparsity adaptive subspace pursuit(CVA-BSASP)algorithm,the proposed algorithm can effectively improve the accurate estimation of the sparsity of active user and the performance of system bit error ratio(BER),and has the advantage of low-complexity.展开更多
Multi-user detection is one of the important technical problems for moderncommunications. In the field of quantum communication, the multi-access channel onwhich we apply the technology of quantum information processi...Multi-user detection is one of the important technical problems for moderncommunications. In the field of quantum communication, the multi-access channel onwhich we apply the technology of quantum information processing is still an openquestion. In this work, we investigate the multi-user detection problem based on thebinary coherent-state signals whose communication way is supposed to be seen as aquantum channel. A binary phase shift keying model of this multi-access channel isstudied and a novel method of quantum detection proposed according to the conclusionof the quantum measurement theory. As a result, the average interference betweendeferent users is presented and the average error probability of the quantum detection isderived theoretically. Finally, we show the maximum channel capacity of this effectivedetection for a two-access quantum channel.展开更多
Multi-user detection techniques are currently being studied as highly promising technologies for improving the performance of unsourced multiple access systems. In this paper, we propose joint multi-user detection sch...Multi-user detection techniques are currently being studied as highly promising technologies for improving the performance of unsourced multiple access systems. In this paper, we propose joint multi-user detection schemes with weighting factors for unsourced multiple access. First, we introduce bidirectional weighting factors in the extrinsic information passing process between the multi-user detector based on belief propagation (BP) and the LDPC decoder. Second, we incorporate bidirectional weighting factors in the message passing process between the MAC nodes and the user variable nodes in BP- based multi-user detector. The proposed schemes select the optimal weighting factors through simulations. The simulation results demonstrate that the proposed schemes exhibit significant performance improvements in terms of block error rate (BLER) compared to traditional schemes. .展开更多
Minimum mean square error(MMSE) detection algorithm can achieve nearly optimal performance when the number of antennas at the base station(BS) is large enough compared to the number of users. But the traditional MMSE ...Minimum mean square error(MMSE) detection algorithm can achieve nearly optimal performance when the number of antennas at the base station(BS) is large enough compared to the number of users. But the traditional MMSE involves complicated matrix inversion. In this paper, we propose a modified MMSE algorithm which exploits the channel characteristics occurring in massive multiple-input multipleoutput(MIMO) channels and the relaxation iteration(RI) method to avoid the matrix inversion. A proper initial solution is given to accelerate the convergence speed. In addition, we point out that the channel estimation scheme used in channel hardening-exploiting message passing(CHEMP) receiver is very appropriate for our proposed detection algorithm. Simulation results verify that the proposed algorithm can achieve very close performance of the traditional MMSE algorithm with a small number of iterations.展开更多
The steered covariance matrix(STCM) and its inverse matrix should be calculated in each beam for steered minimum variance(STMV) . The inverse matrix needs complex computation and restricts its application in engineeri...The steered covariance matrix(STCM) and its inverse matrix should be calculated in each beam for steered minimum variance(STMV) . The inverse matrix needs complex computation and restricts its application in engineering. Combining the integration character of one-phase regressive filter with the iterative formula of inverse matrix,an STMV iterative algorithm is proposed. The computational cost of the iterative algorithm is reduced approximately to be 2/M times of the original one when there are M sensors,and is more advantaged for the realization of the algorithm in real time. Simulation results show that the STMV iterative algorithm can preserve the characters of STMV on high azimuth resolution and weak target detection while the computational cost reduced sharply. The analysis on sea trial data proves that the proposed algorithm can estimate each target's azimuth even when the source powers differ in large scales or their bearings are very approximate.展开更多
Aiming at a class of nonlinear systems that contains faults, a novel iterative learning scheme is applied to fault detec- tion, and a novel algorithm of fault detection and estimation is proposed. This algorithm first...Aiming at a class of nonlinear systems that contains faults, a novel iterative learning scheme is applied to fault detec- tion, and a novel algorithm of fault detection and estimation is proposed. This algorithm first constructs residual signals by the output of the practical system and the output of the designed fault tracking estimator, and then uses the residuals and the difference- value signal of the adjacent two residuals to gradually revise the introduced virtual faults, which can cause the virtual faults to close to the practical faults in systems, thereby achieving the goal of fault detection for systems. This algorithm not only makes full use of the existing valid information of systems and has a faster tracking con- vergent speed than the proportional-type （P-type） algorithm, but also calculates more simply than the proportional-derivative-type （PD-type） algorithm and avoids the unstable effects of differential operations in the system. The final simulation results prove the validity of the proposed algorithm.展开更多
Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection a...Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection and precoding. Recently, many detection and precoding methods were proposed using approximate iteration methods, which meet the demand of precision with low complexity. In this paper, we compare these approximate iteration methods in precision and complexity, and then improve these methods with iteration refinement at the cost of little complexity and no extra hardware resource. By derivation, our proposal is a combination of three approximate iteration methods in essence and provides remarkable precision improvement on desired vectors. The results show that our proposal provides 27%-83% normalized mean-squared error improvement of the detection symbol vector and precoding symbol vector. Moreover, we find the bit-error rate is mainly controlled by soft-input soft-output Viterbi decoding when using approximate iteration methods. Further, only considering the effect on soft-input soft-output Viterbi decoding, the simulation results show that using a rough estimation for the filter matrix of minimum mean square error detection to calculating log-likelihood ratio could provideenough good bit-error rate performance, especially when the ratio of base station antennas number and the users number is not too large.展开更多
The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receive...The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receiver, which exchanges soft extrinsic information between a soft-in soft-out(SISO) detector and an SISO decoder in an iterative fashion, is an efficient method to reduce the uplink inter-beam-interference(IBI),and so the receiving bit error rate(BER).We propose to replace the linear SISO detector of traditional dual-turbo iterative detection and decoding with the AMP detector for the low-density parity-check(LDPC) coded multibeam MSC uplink. This improvement can reduce the computational complexity and achieve much lower BER.展开更多
In this paper, we investigate the self-encoded multirate and the multimedia (SEMM) transmission. In SEMM system, the spreading codes are derived from its own previously transmitted bits rather than the pseudorandom co...In this paper, we investigate the self-encoded multirate and the multimedia (SEMM) transmission. In SEMM system, the spreading codes are derived from its own previously transmitted bits rather than the pseudorandom code generator. We employ block chip interleaving at the transmitter to combat the deep fading over the channels. At the receiver, decorrelation scheme separates the combined signals not only to reduce the crosstalk between different applications, but also provide a better estimation for the despreading sequence. Interference cancelation (IC) is also adopted to improve both the correlation detection and iterative detection (ID) performance. The simulation results show that the proposed scheme significantly improves performance over fading channels.展开更多
An iterative detection and decoding algorithm with outer code decision feedback is proposed for the dual polarized( DP) land mobile satellite( LMS) MIMO systems using concatenated codes. A feedback structure is added ...An iterative detection and decoding algorithm with outer code decision feedback is proposed for the dual polarized( DP) land mobile satellite( LMS) MIMO systems using concatenated codes. A feedback structure is added after the outer decoder in the proposed algorithm. The feedback information is exploited to control the detecting list in the MIMO detector and reduce the number of symbols which have to be processed at each iteration. As a result,the computational complexity is reduced. Meanwhile,the successfully decoded outer code words are used to calculate the more reliable initial information for the inner decoder and the system performance can be improved by this step. The simulation results show that the proposed algorithm can reduce the computational complexity compared to the traditional iterative detection and decoding algorithm and achieve better performance.展开更多
In this paper, we propose a new iterative detection and decoding scheme based on parallel interference cancel (PIC) for coded MIMO-OFDM systems. The performance of proposed receiver is improved through the joint PIC M...In this paper, we propose a new iterative detection and decoding scheme based on parallel interference cancel (PIC) for coded MIMO-OFDM systems. The performance of proposed receiver is improved through the joint PIC MIMO detection and iterative detection and decoding. Its performance is evaluated based on com-puter simulation. The simulation results indicate that the performance of the proposed receiver is greatly im-proved compared to coded MIMO-OFDM systems based on VBLAST detection scheme.展开更多
A number of study results demonstrated that the performance of the coded MIMO scheme can be highly enhanced by incorporating iterative decoding and detection scheme by exchanging soft information between the symbol de...A number of study results demonstrated that the performance of the coded MIMO scheme can be highly enhanced by incorporating iterative decoding and detection scheme by exchanging soft information between the symbol detector and decoder. One of the critical problems of these iterative schemes is an exponential order of the complexity with increase of number of bits in a symbol and the number of antennas. In this paper, we present an efficient iterative detection and decoding scheme for MIMO systems with phase shift keying (PSK) modulation schemes and low density parity check (LDPC) codes. In order to reduce the complexity by the number of antennas, we adopt minimum mean square error (MMSE) based linear detection scheme with parallel interference cancellation. In addition, soft bit estimation is made only with a single distance calculation per bit, with approximating performance to the maximum likelihood detection1.展开更多
In asynchronous Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing(MIMO-OFDM) over the selective Rayleigh fading channel,the performance of the existing linear detection algorithms improves slow...In asynchronous Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing(MIMO-OFDM) over the selective Rayleigh fading channel,the performance of the existing linear detection algorithms improves slowly as the Signal Noise Ratio (SNR) increases.To improve the performance of asynchronous MIMO-OFDM,a low complexity iterative detection algorithm based on linear precoding is proposed in this paper.At the transmitter,the transmitted signals are spread by precoding matrix to achieve the space-frequency diversity gain,and low complexity iterative Interference Cancellation(IC) algorithm is used at the receiver,which relieves the error propagation by the precoding matrix.The performance improvement is verified by simulations.Under the condition of 4 transmitting antennas and 4 receiving antennas at the BER of 10-4,about 6 dB gain is obtained by using our proposed algorithm compared with traditional algorithm.展开更多
基金supported by the National Natural Science Foundation of China(6104000561001126+5 种基金61271262)the China Postdoctoral Science Foundation Funded Project(201104916382012T50789)the Natural Science Foundation of Shannxi Province of China(2011JQ8036)the Special Fund for Basic Scientific Research of Central Colleges (CHD2012ZD005)the Research Fund of Zhejiang University of Technology(20100244)
文摘Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.
基金Sponsored by the National"863"Program Projects (2007AA012293)
文摘An improved wavelet packet domain least mean square （IWPD-LMS） based adaptive muhiuser detection algorithm is proposed. The algorithm employs the wavelet packet transform to rewhiten the input data, and chooses the best wavelet packet basis according to a novel convergence contribution function rather than the conventional Shannon entropy. The theoretic analyses show that the inadequacy of the eigenvalue spread of the tap-input correlation matrix is ameliorated, thus the convergence performance is improved greatly. The simulation result of convergence performance and bit error rate（BER） performance as a function of the signal power to noise power ratio（SNR） are presented finally to prove the validity of the proposed algorithm.
基金financially supported by Key Technologies R&D Program of Shandong Province(2015GSF115018)Natural Science Foundation of Shandong Province(ZR2013FL027+1 种基金ZR2013DM 014)Youth Foundation of Shandong Academy of Science(2013QN030)
文摘RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.
文摘Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework with parallel interference cancellation, a supervision decision algorithm based on pre-decision of probabilistic data association (PDA) and hard decision is proposed. The detection performance is analyzed and simulation is implemented to show that the supervision decision algorithm improves the detection performance effectively.
文摘To improve the computational speed, the ROLS-AWS algorithm was employed in the RBF based MUD receiver. The radial basis function was introduced into the multi-user detection （MUD） firstly. Then a three-layer neural network demodulation spread-spectrum signal model in the synchronous Gauss channel was given and the multi-user detection receiver was analyzed intensively. Simulations by computer illustrate that the proposed RBF based MUD receiver employing the ROKS-AWS algorithm is better than conventional detectors and common BP neural network based MUD receivers on suppressing multiple access interference and near-far resistance.
文摘A graph model is constructed for the Multi-user Detection of DS-CDMA system. Based on it, a Hopfield-like algorithm is put forward for the implementation of optimum receiver. Compared with the Hopfield approach, it has a higher computational complexity but better performance.
文摘The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems.In this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two stages.The first stage estimates the channel parameters,and the second performsmulti-user detection.The proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural networks.This study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO receivers.The FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.
基金Supported by the National Natural Science Foundation of China(No.62001001)。
文摘In the uplink grant-free non-orthogonal multiple access(NOMA)scenario,since the active user at the sender has a structured sparsity transmission characteristic,the compressive sensing recovery algorithm is initially applied to the joint detection of the active user and the transmitted data.However,the existing compressed sensing recovery algorithms with unknown sparsity often require noise power or signal-to-noise ratio(SNR)as the priori conditions,which greatly reduces the algorithm adaptability in multi-user detection.Therefore,an algorithm based on cross validation aided structured sparsity adaptive orthogonal matching pursuit(CVA-SSAOMP)is proposed to realize multi-user detection in dynamic change communication scenario of channel state information(CSI).The proposed algorithm transforms the structured sparsity model into a block sparse model,and without the priori conditions above,the cross validation method in the field of statistics and machine learning is used to adaptively estimate the sparsity of active user through the residual update of cross validation.The simulation results show that,compared with the traditional orthogonal matching pursuit(OMP)algorithm,subspace pursuit(SP)algorithm and cross validation aided block sparsity adaptive subspace pursuit(CVA-BSASP)algorithm,the proposed algorithm can effectively improve the accurate estimation of the sparsity of active user and the performance of system bit error ratio(BER),and has the advantage of low-complexity.
基金Supported by the National Natural Science Foundation of Chinaunder Grant Nos. 61501247, 61373131 and 61702277the Six Talent Peaks Project ofJiangsu Province (Grant No. 2015-XXRJ-013)+2 种基金Natural Science Foundation of JiangsuProvince (Grant No. BK20171458)the Natural Science Foundation of the HigherEducation Institutions of Jiangsu Province (China under Grant No. 16KJB520030)theNUIST Research Foundation for Talented Scholars under Grant Nos. 2015r014, PAPDand CICAEET funds.
文摘Multi-user detection is one of the important technical problems for moderncommunications. In the field of quantum communication, the multi-access channel onwhich we apply the technology of quantum information processing is still an openquestion. In this work, we investigate the multi-user detection problem based on thebinary coherent-state signals whose communication way is supposed to be seen as aquantum channel. A binary phase shift keying model of this multi-access channel isstudied and a novel method of quantum detection proposed according to the conclusionof the quantum measurement theory. As a result, the average interference betweendeferent users is presented and the average error probability of the quantum detection isderived theoretically. Finally, we show the maximum channel capacity of this effectivedetection for a two-access quantum channel.
文摘Multi-user detection techniques are currently being studied as highly promising technologies for improving the performance of unsourced multiple access systems. In this paper, we propose joint multi-user detection schemes with weighting factors for unsourced multiple access. First, we introduce bidirectional weighting factors in the extrinsic information passing process between the multi-user detector based on belief propagation (BP) and the LDPC decoder. Second, we incorporate bidirectional weighting factors in the message passing process between the MAC nodes and the user variable nodes in BP- based multi-user detector. The proposed schemes select the optimal weighting factors through simulations. The simulation results demonstrate that the proposed schemes exhibit significant performance improvements in terms of block error rate (BLER) compared to traditional schemes. .
基金supported by the National Hightech R&D Program of China(2014AA01A704)the Natural Science Foundation of China(61201135)111 Project(B08038)
文摘Minimum mean square error(MMSE) detection algorithm can achieve nearly optimal performance when the number of antennas at the base station(BS) is large enough compared to the number of users. But the traditional MMSE involves complicated matrix inversion. In this paper, we propose a modified MMSE algorithm which exploits the channel characteristics occurring in massive multiple-input multipleoutput(MIMO) channels and the relaxation iteration(RI) method to avoid the matrix inversion. A proper initial solution is given to accelerate the convergence speed. In addition, we point out that the channel estimation scheme used in channel hardening-exploiting message passing(CHEMP) receiver is very appropriate for our proposed detection algorithm. Simulation results verify that the proposed algorithm can achieve very close performance of the traditional MMSE algorithm with a small number of iterations.
文摘The steered covariance matrix(STCM) and its inverse matrix should be calculated in each beam for steered minimum variance(STMV) . The inverse matrix needs complex computation and restricts its application in engineering. Combining the integration character of one-phase regressive filter with the iterative formula of inverse matrix,an STMV iterative algorithm is proposed. The computational cost of the iterative algorithm is reduced approximately to be 2/M times of the original one when there are M sensors,and is more advantaged for the realization of the algorithm in real time. Simulation results show that the STMV iterative algorithm can preserve the characters of STMV on high azimuth resolution and weak target detection while the computational cost reduced sharply. The analysis on sea trial data proves that the proposed algorithm can estimate each target's azimuth even when the source powers differ in large scales or their bearings are very approximate.
基金supported by the National Natural Science Foundation of China (61100103)
文摘Aiming at a class of nonlinear systems that contains faults, a novel iterative learning scheme is applied to fault detec- tion, and a novel algorithm of fault detection and estimation is proposed. This algorithm first constructs residual signals by the output of the practical system and the output of the designed fault tracking estimator, and then uses the residuals and the difference- value signal of the adjacent two residuals to gradually revise the introduced virtual faults, which can cause the virtual faults to close to the practical faults in systems, thereby achieving the goal of fault detection for systems. This algorithm not only makes full use of the existing valid information of systems and has a faster tracking con- vergent speed than the proportional-type （P-type） algorithm, but also calculates more simply than the proportional-derivative-type （PD-type） algorithm and avoids the unstable effects of differential operations in the system. The final simulation results prove the validity of the proposed algorithm.
文摘Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection and precoding. Recently, many detection and precoding methods were proposed using approximate iteration methods, which meet the demand of precision with low complexity. In this paper, we compare these approximate iteration methods in precision and complexity, and then improve these methods with iteration refinement at the cost of little complexity and no extra hardware resource. By derivation, our proposal is a combination of three approximate iteration methods in essence and provides remarkable precision improvement on desired vectors. The results show that our proposal provides 27%-83% normalized mean-squared error improvement of the detection symbol vector and precoding symbol vector. Moreover, we find the bit-error rate is mainly controlled by soft-input soft-output Viterbi decoding when using approximate iteration methods. Further, only considering the effect on soft-input soft-output Viterbi decoding, the simulation results show that using a rough estimation for the filter matrix of minimum mean square error detection to calculating log-likelihood ratio could provideenough good bit-error rate performance, especially when the ratio of base station antennas number and the users number is not too large.
基金supported by the National Natural Science Foundation of China under Grants 61320106003 and 61401095the Civil Aerospace Technologies Research Project under Grant D010109The Fundamental Research Funds for the Central Universities under Grant YZZ17009
文摘The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receiver, which exchanges soft extrinsic information between a soft-in soft-out(SISO) detector and an SISO decoder in an iterative fashion, is an efficient method to reduce the uplink inter-beam-interference(IBI),and so the receiving bit error rate(BER).We propose to replace the linear SISO detector of traditional dual-turbo iterative detection and decoding with the AMP detector for the low-density parity-check(LDPC) coded multibeam MSC uplink. This improvement can reduce the computational complexity and achieve much lower BER.
文摘In this paper, we investigate the self-encoded multirate and the multimedia (SEMM) transmission. In SEMM system, the spreading codes are derived from its own previously transmitted bits rather than the pseudorandom code generator. We employ block chip interleaving at the transmitter to combat the deep fading over the channels. At the receiver, decorrelation scheme separates the combined signals not only to reduce the crosstalk between different applications, but also provide a better estimation for the despreading sequence. Interference cancelation (IC) is also adopted to improve both the correlation detection and iterative detection (ID) performance. The simulation results show that the proposed scheme significantly improves performance over fading channels.
基金Sponsored by the Postdoctoral Science Foundation of China(Grant No.2011M500640)
文摘An iterative detection and decoding algorithm with outer code decision feedback is proposed for the dual polarized( DP) land mobile satellite( LMS) MIMO systems using concatenated codes. A feedback structure is added after the outer decoder in the proposed algorithm. The feedback information is exploited to control the detecting list in the MIMO detector and reduce the number of symbols which have to be processed at each iteration. As a result,the computational complexity is reduced. Meanwhile,the successfully decoded outer code words are used to calculate the more reliable initial information for the inner decoder and the system performance can be improved by this step. The simulation results show that the proposed algorithm can reduce the computational complexity compared to the traditional iterative detection and decoding algorithm and achieve better performance.
文摘In this paper, we propose a new iterative detection and decoding scheme based on parallel interference cancel (PIC) for coded MIMO-OFDM systems. The performance of proposed receiver is improved through the joint PIC MIMO detection and iterative detection and decoding. Its performance is evaluated based on com-puter simulation. The simulation results indicate that the performance of the proposed receiver is greatly im-proved compared to coded MIMO-OFDM systems based on VBLAST detection scheme.
文摘A number of study results demonstrated that the performance of the coded MIMO scheme can be highly enhanced by incorporating iterative decoding and detection scheme by exchanging soft information between the symbol detector and decoder. One of the critical problems of these iterative schemes is an exponential order of the complexity with increase of number of bits in a symbol and the number of antennas. In this paper, we present an efficient iterative detection and decoding scheme for MIMO systems with phase shift keying (PSK) modulation schemes and low density parity check (LDPC) codes. In order to reduce the complexity by the number of antennas, we adopt minimum mean square error (MMSE) based linear detection scheme with parallel interference cancellation. In addition, soft bit estimation is made only with a single distance calculation per bit, with approximating performance to the maximum likelihood detection1.
基金supported by the Hi-Tech Research and Development Program of China under Grant No.2009AA01Z236the National Natural Science Foundation of China under Grants No.60902027,No.60832007 and No.60901018+1 种基金the Funds under Grant No.9140A21030209DZ02the Fundamental Research Funds for the Central Universities under Grants No.ZYGX2009J008,No.ZYGX2009J010
文摘In asynchronous Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing(MIMO-OFDM) over the selective Rayleigh fading channel,the performance of the existing linear detection algorithms improves slowly as the Signal Noise Ratio (SNR) increases.To improve the performance of asynchronous MIMO-OFDM,a low complexity iterative detection algorithm based on linear precoding is proposed in this paper.At the transmitter,the transmitted signals are spread by precoding matrix to achieve the space-frequency diversity gain,and low complexity iterative Interference Cancellation(IC) algorithm is used at the receiver,which relieves the error propagation by the precoding matrix.The performance improvement is verified by simulations.Under the condition of 4 transmitting antennas and 4 receiving antennas at the BER of 10-4,about 6 dB gain is obtained by using our proposed algorithm compared with traditional algorithm.
