Linear Precoder Design for Correlated Rician Fading Channel Under Imperfect CSI

In this paper,we have modeled a linear precoder for indoor multiuser multiple input multiple output(MU-MIMO)system with imperfect channel state information(CSI)at transmitter.The Rician channel is presumed to be mutually coupled and spatially,temporarily correlated.The imperfection with CSI is primarily due to the channel estimation error at receiver and feedback delay amidst the receiver and transmitter in CSI transmission.Along with,the insufficient spacing between the antenna at transmitter and receiver persuades mutual coupling(MC)among the array elements.In addition,the MIMO channel is presumed to be jointly correlated(Weichselberger correlation model).When we look back on the existing precoder design,it considered spatial correlation alone disregarding joint correlation of antenna array elements.With all above assumption,we have designed a linear precoder which minimizes mean squared error(MSE)subjected to total transmit power constraint for MUMIMO system.The simulation results proven that proposed precoder shows substantial enhancement in bit error rate(BER)performance in comparison with the existing technique.The mathematical analysis corroborates the simulation results.

A Novel Decoder Based on Parallel Genetic Algorithms for Linear Block Codes

Genetic algorithms offer very good performances for solving large optimization problems, especially in the domain of error-correcting codes. However, they have a major drawback related to the time complexity and memory occupation when running on a uniprocessor computer. This paper proposes a parallel decoder for linear block codes, using parallel genetic algorithms (PGA). The good performance and time complexity are confirmed by theoretical study and by simulations on BCH(63,30,14) codes over both AWGN and flat Rayleigh fading channels. The simulation results show that the coding gain between parallel and single genetic algorithm is about 0.7 dB at BER = 10﹣5 with only 4 processors.

Lowering the Error Floor of ADMM Penalized Decoder for LDPC Codes

Decoding by alternating direction method of multipliers(ADMM) is a promising linear programming decoder for low-density parity-check(LDPC) codes. In this paper, we propose a two-step scheme to lower the error floor of LDPC codes with ADMM penalized decoder.For the undetected errors that cannot be avoided at the decoder side, we modify the code structure slightly to eliminate low-weight code words. For the detected errors induced by small error-prone structures, we propose a post-processing method for the ADMM penalized decoder. Simulation results show that the error floor can be reduced significantly over three illustrated LDPC codes by the proposed two-step scheme.

A LINEAR PRECODING STRATEGY BASED ON PARTICLE SWARM OPTIMIZATION IN MULTICELL COOPERATIVE TRANSMISSION

An optimal linear precoding scheme based on Particle Swarm Optimization(PSO),which aims to maximize the system capacity of the cooperative transmission in the downlink channel,is proposed for a multicell multiuser single input single output system.With such a scheme,the optimal precoding vector could be easily searched for each user according to a simplified objective function.Simulation results show that the proposed scheme can obtain larger average spectrum efficiency and a better Bit Error Rate(BER) performance than Zero Forcing(ZF) and Minimum Mean Square Error(MMSE) algorithm.

An Enhanced Jacobi Precoder for Downlink Massive MIMO Systems

Linear precoding methods such as zero-forcing(ZF)are near optimal for downlink massive multi-user multiple input multiple output(MIMO)systems due to their asymptotic channel property.However,as the number of users increases,the computational complexity of obtaining the inverse matrix of the gram matrix increases.Forsolving the computational complexity problem,this paper proposes an improved Jacobi(JC)-based precoder to improve error performance of the conventional JC in the downlink massive MIMO systems.The conventional JC was studied for solving the high computational complexity of the ZF algorithm and was able to achieve parallel implementation.However,the conventional JC has poor error performance when the number of users increases,which means that the diagonal dominance component of the gram matrix is reduced.In this paper,the preconditioning method is proposed to improve the error performance.Before executing the JC,the condition number of the linear equation and spectrum radius of the iteration matrix are reduced by multiplying the preconditioning matrix of the linear equation.To further reduce the condition number of the linear equation,this paper proposes a polynomial expansion precondition matrix that supplements diagonal components.The results show that the proposed method provides better performance than other iterative methods and has similar performance to the ZF.

Linear Precoding Based Iterative Detection Algorithm in Asynchronous MI MO-OFDM Systems

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.

PRECODING AND DECODING DESIGN FOR TWO-WAY MIMO AF MULTIPLE-RELAY SYSTEM

In this paper, a joint precoding and decoding design scheme is proposed for two-way Multiple-Input Multiple-Output (MIMO) multiple-relay system. The precoding and decoding matrices are jointly optimized based on Minimum Mean-Square-Error (MMSE) criteria under transmit power constraints. The optimization problem is solved by using a convergent iterative algorithm which in-cludes four sub-problems. It is shown that due to the difficulty of the block diagonal nature of the relay precoding matrix, sub-problem two cannot be solved with existing methods. It is then solved by converting sub-problem two into a convex optimization problem and a simplified method is proposed to reduce the computational complexity. Simulation results show that the proposed scheme can achieve lower Bit Error Rate (BER) and larger sum rate than other schemes. Furthermore, the BER and the sum rate performance can be improved by increasing the number of antennas for the same number of relays or increasing the number of relays for the same number of antennas.

Blind channel estimation through redundant linear precoding for OFDM systems

A novel approach of blind channel estimation through redundant linear precoding for orthogonal fre-quency-division multiplexing （OFDM） is proposed. A redundant linear frequency-domain preceder is ap-plied to each pair of blocks before they enter the OFDM system. With the aid of the introduced structure, the frequency-selective channel can be identified at the receiver through auto-correlation operations, sin-gular value decomposition （SVD） and scalar ambiguity resolution. The proposed blind channel estimation method has low computation complexity and requires no prior statistical information of channel or noise. The redundant linear frequency-domain precoder is employed to identify the frequency-selective fading channels. And the proposed blind channel estimation method has high spectral efficiency because it re-quires no training sequence. Computer simulations have proved that this proposed blind channel estima- tion method can identify the frequency-selective channels perfectly and have a good performance.

LOW COMPLEXITY LMMSE TURBO EQUALIZATION FOR COMBINED ERROR CONTROL CODED AND LINEARLY PRECODED OFDM

The turbo equalization approach is studied for Orthogonal Frequency Division Multiplexing （OFDM） system with combined error control coding and linear precoding. While previous literatures employed linear precodcr of small size for complexity reasons, this paper proposes to use a linear precoder of size larger than or equal to the maximum length of the equivalent discrete-time channel in order to achieve full frequency diversity and reduce complexities of the error control coder/decoder. Also a low complexity Linear Minimum Mean Square Error （LMMSE） turbo equalizer is derived for the receiver. Through simulation and performance analysis, it is shown that the performance of the proposed scheme over frequency selective fading channel reaches the matched filter bound; compared with the same coded OFDM without linear precoding, the proposed scheme shows an Signal-to-Noise Ratio （SNR） improvement of at least 6dB at a bit error rate of 10 6 over a multipath channel with exponential power delay profile. Convergence behavior of the proposed scheme with turbo equalization using various type of linear precoder/transformer, various interleaver size and error control coder of various constraint length is also investigated.

Approximate Iteration Detection and Precoding in Massive MIMO

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.

Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

The lattice-reduction （LR） has been developed to im- prove the performance of the zero-forcing （ZF） precoder in multiple input multiple output （MIMO） systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter （CSIT）, an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex Lenstra- Lenstra-Lov^sz （LLL） algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error （LMMSE） pre- coder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate （BER）. Assuming a time division duplexing （TDD） MIMO system, correlated block flat fad- ing channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying （QPSK） modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when Eb-No is greater than 10 dB and 12 dB at all correlation coefficients.

Spectral Efficiency Analysis for Downlink Massive MIMO Systems with MRT Precoding

As an important part of the channel fading, large scale fading should be considered in downlink massive multiple-input multipleoutput(MIMO) systems. This paper investigates the downlink massive MIMO system over a large scale fading channel, when the base station takes advantage of maximum-radio transmission(MRT) precoding. The cases when the base station has perfect and imperfect channel state information(CSI) are considered respectively. Specially, through the analysis of single user's ergodic achievable rate, some novel and approximate expressions for the spectral efficiency(SE) are derived. Based on the approximate SE, the effect of the channel estimation error is analyzed intuitively. In addition, the average SE of all the users with different large-scale fading parameters is carefully investigated. Simulations validate that all the theoretical results coincide with numerical results and the large scale fading factors have little influence on SE reduction resulted from channel estimation.

Maximum Ratio Combining Precoding for Multi-Antenna Relay Systems

This paper addresses the design of practical communication strategies for multi-antenna amplify-and-forward and decode-and-forward relay systems. We show that simple linear techniques at the source and destination in conjunction with maximum ratio combining can provide an optimal transmission strategy in terms of received SNR without imposing a huge computational load over the relay node(s). Besides, the structures of precoding matrices are very similar at the source and relay nodes, which reduces the complexity as all nodes can play the role of source and relay nodes without changing their transmission structure. Numerical results show that the proposed transmission and reception techniques can improve the received SNR, and hence enhance the ergodic capacity.

Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)systems.The inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is used.In this paper,the horizontal Gauss-Seidel(HGS)method is proposed as precoding scheme in massive MIMO systems.In massive MIMO systems,the exact inversion of channel matrix is impractical due to the severe computational complexity.Therefore,the conventionalGauss-Seidel(GS)method is used to approximate the inversion of channel matrix.The GS has good performance by using previous calculation results as feedback.However,the required time for obtaining the precoding symbols is too long due to the sequential process of GS.Therefore,the HGS with parallel calculation is proposed in this paper to reduce the required time.The rows of channel matrix are eliminated for parallel calculation inHGSmethod.In addition,HGSuses the ordered channelmatrix to prevent performance degradation which is occurred by parallel calculation.The HGS with proper number of parallelly computed symbols has better performance and reduced required time compared to the traditional GS.

线性分组码的GRAND算法研究

随着5G通信技术的发展与应用,高可靠低时延通信场景下的短包信道编译码技术受到了广泛关注。GRAND是一种通用的最大似然译码算法,与传统译码算法不同,GRAND算法通过噪声猜测和码本查询来确定发送码字,具有高效的硬件实现结构。介绍了GRAND及其改进算法的基本原理,通过仿真分析了不同GRAND算法的误码率性能;针对5G NR的LDPC短码以及PAC短码给出了GRAND算法的设计方案,为未来移动通信的短码设计提供参考。

多输入多输出可见光通信系统中预编码技术的研究进展

近年来,可见光通信(VLC)技术得到飞速发展,该技术兼具室内低功耗照明和宽带信号高速接入的双重功能,因此在室内大数据通信领域具有较高的应用价值。多输入多输出(MIMO)作为一种在VLC系统中能实现信道容量倍增的技术正日益引起业界关注,但多信道具有强相关性容易导致用户间信息串扰,而在发射机中应用若干预编码技术可在一定程度上避免用户间信息干扰,且可以较低成本实现系统收发质量的提升。文章综述了MIMO-VLC系统中预编码技术的应用背景和基本原理,总结了典型线性及非线性预编码技术的研究进展,讨论并分析了该类技术的应用优势、发展趋势和面临的挑战。

Joint linear precoder and power allocation design for uplink MIMO systems with limited feedback

In this article, the authors consider joint design of a linear precoder and power allocation for uplink multiuser multiple input multiple output （MIMO） communication systems with limited feedback to improve the bit error rate （BER） performance for all users. Precoder selection from the codebook set is directly based on the exact BER performance, instead of other suboptimal criteria, to achieve the optimal precoder matrix, but closed-form expressions may not exist in the view of power allocation based directly on the BER criterion. From this perspective, the authors propose the joint transmitter optimization algorithm for the consideration of precoder design, with total power constraint for asymptotic MBER （AMBER） criterion. In this AMBER criterion, a closed-form solution has been derived for power allocation with an optimal precoder. The simulation results show that the proposed joint design algorithm can achieve a much better performance than precoding with uniform power allocation and only consideration of power allocation.

多输入多输出系统下行链路发射与接收的联合线性预编码

针对多用户多输入多输出系统下行链路线性预编码中的迫零法及正交化法对接收端的噪声有较强放大作用的问题,提出了一种发射与接收联合预编码的波束成形迭代法.该方法把联合预编码直接转变为波束成形问题,以惟一确定的最小范数解作为预编码矩阵,通过迭代得到各用户的预编解码矩阵.由于所得到的解码矩阵具有最小范数的特性,在解码时产生的噪声能量最小,从而有效地减少了对噪声的放大作用.同时,在基站总发射功率一定的条件下,根据用户的信道质量动态地分配功率可以使信道质量较差的用户得到较多的发射功率.仿真实验表明,所提出的方法与迫零法相比,在相同的仿真条件下,在平均误比特率为10-4时可以获得约9 dB的性能增益.

一种多用户多输入多输出系统下行链路线性预编码方法

针对多用户多输入多输出系统下行链路线性预编码的信干噪比最大化方法中,共信道干扰抑制和噪声抑制不能有效平衡的问题,提出将其中的噪声方差项修正为以噪声方差为变量的分段线性函数的改进方案.该方案通过对噪声方差项的分段修正,在噪声方差的值较小时依然能够保持共信道干扰抑制和噪声抑制间的平衡,从而使系统的误比特率性能和容量得到进一步提高.仿真结果表明,与信干噪比最大化法相比,所提方案对于基站天线数为5、移动用户数为3、移动用户天线数均为2的多用户系统,在平均误比特率为10-4水平上可以获得2 dB的性能增益,当信噪比为10dB时,可以使系统的各态历经容量增加1 b.(s.Hz)-1.

乘积码的一种新的迭代译码算法

乘积码是利用线性分组码实现长码的典范,能纠正大量的随机错误和突发错误,当以Turbo码的思想实现乘积码的迭代译码时,可获得很高的编码增益。针对乘积码提出一种新的迭代译码算法,该算法的反馈方式有别于Turbo码的传统迭代译码,是通过输出软信息与接收软信息进行线性叠加来实现的,此时子译码器的候选码字个数将大为降低,同时译码输出也无须做复杂的LLR计算,直接映射为由-1, +1组成的软输出矩阵,从而在牺牲较小性能的情况下很大程度地降低了译码复杂度。