基于不完全信道状态信息的多用户MIMO中继系统预编码算法

针对上行多用户MIMO中继系统，在信道存在反馈延迟及估计误差的条件下，以误比特率(Bit error rate, BER)为优化目标，提出了基于最小均方误差(Minimum mean?squared error, MMSE)准则的预编码算法。所提算法将求解发射端、中继节点、接收端矩阵的复杂非凸问题分解为3个独立的子优化问题，发射端的用户配备单天线且服从空间独立分布，先确定发射端预编码矩阵，将求解中继矩阵的凸优化问题转化为半正定规划(Semi?definite programming, SDP)问题，采用CVX工具箱求解，接收端处理矩阵通过线性搜索法求解，最后采用联合迭代法得到各节点矩阵的最优解。仿真结果表明，所提算法能有效改善系统的误比特率性能。     

Blind channel estimation and signal retrieving for MIMO relay systems

In this paper, we propose a blind channel estimation and signal retrieving algorithm for two-hop multiple-input multiple-output (MIMO) relay systems. This new algorithm integrates two blind source separation (BSS) methods to estimate the individual channel state information (CSI) of the source-relay and relay-destination links. In particular, a first-order Z-domain precoding technique is developed for the blind estimation of the relay-destination channel matrix, where the signals received at the relay node are pre-processed by a set of precoders before being transmitted to the destination node. With the estimated signals at the relay node, we propose an algorithm based on the constant modulus and signal mutual information properties to estimate the source-relay channel matrix. Compared with training-based MIMO relay channel estimation approaches, the proposed algorithm has a better bandwidth efficiency as no bandwidth is wasted for sending the training sequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm.     

Adaptive robust Max-SLNR precoder for MU-MIMO-OFDM systems with imperfect CSI非完美信道状态信息下多用户MIMO-OFDM系统自适应稳健的最大化信泄噪比预编码算法

The accuracy of channel state information (CSI) available at a base station (BS) has a direct impact on the performance of precoding in wideband multi-user multiple input, multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems and depends on many factors, including: the delay between estimation and beamforming at the BS (also called the CSI delay), Doppler spread, the channel estimation method used, the average transmit power of pilot symbols, and the average number of pilot symbols that must be estimated per channel parameter. In this paper, the coefficient of CSI error needed to adapt to fading channels is modeled as a function of Doppler spread, CSI delay, and signal-to-noise ratio (SNR). In terms of the Gaussian-Markov CSI error model, an adaptive robust maximum signal-to-leakage-and-noise ratio (Max- SLNR) precoder is designed to track the statistical parameters of CSI error. The Doppler spread and SNR can be obtained through real-time estimation based on orthogonal pilot patterns. Simulation results show that, compared to non-adaptive robust and non-robust precoders of Max-SLNR, the proposed adaptive robust Max- SLNR precoder performs much better in terms of bit error rate (BER). Moreover, as either the average number of training symbols per channel parameter or the average transmit power increases, the BER performance of the proposed precoder approaches that of a precoder with ideal CSI.     

Robust multiuser MIMO scheduling algorithms with imperfect CSI

Robust multiuser multiple-input-multiple-output (MIMO) scheduling algorithms are proposed in this paper.With imperfect channel state information (CSI),traditional scheduling algorithms for the multiuser MIMO system based on the zero forcing precoding scheme will lose some performance due to the multi-user interference (MUI).In order to improve the system average throughput,we study the robust multiuser MIMO scheduling problem with imperfect CSI.From the average capacity formula,we derive a robust factor which can transform the robust multiuser MIMO scheduling problem into the traditional one,thus most existing non-robust scheduling algorithms can be robust if this factor is adopted.Simulation results show that compared with the traditional algorithms,the proposed robust algorithms can improve the system average throughput significantly under the CSI error environment.     

Optimization of a robust collaborative-relay beamforming design for simultaneous wireless information and power transfer

We investigate a collaborative-relay beamforming design for simultaneous wireless information and power transfer. A non-robust beamforming design that assumes availability of perfect channel state information (CSI) in the relay nodes is addressed. In practical scenarios, CSI errors are usually inevitable; therefore, a robust collaborative-relay beamforming design is proposed. By applying the bisection method and the semidefinite relaxation (SDR) technique, the non-convex optimization problems of both non-robust and robust beamforming designs can be solved. Moreover, the solution returned by the SDR technique may not always be rank-one; thus, an iterative sub-gradient method is presented to acquire the rank-one solution. Simulation results show that under an imperfect CSI case, the proposed robust beamforming design can obtain a better performance than the non-robust one.     

Robust power allocation algorithm for analog network coding with imperfect CSI

Power allocation promises significant benefits in wireless networks. However, these benefits depend on knowledge of the channel state information （CSI）, which is hardly perfect. Therefore, robust algorithms that take into account such CSI uncertainties play an important role in the design of practical systems. In this paper, we formulate the power allocation problem as the maximum individual outage probability minimization subject to total power consumption for analog network coding （ANC） protocol of a two-way relay system. We show that these problems can be cast as convex optimization problems. Non-robust power allocation algorithm is first developed under the ideal assumption of perfect CSI. Then we introduce robust optimization methodology that accounts for the imperfect CSI. We show that ignoring CSI uncertainties in our designs can lead to drastic performance degradation. On the other hand, the proposed robust power allocation provides significant performance gain over non-robust power allocation and uniform power allocation in terms of overall system outage probability over a wide range of channel estimation errors. This work highlights the importance of the proposed robust algorithm in realistic two-way relaying networks.     

协作通信中一种中继节点选择方案的设计

针对协作通信系统中源到中继及中继到目的两阶段的瞬时信道状态信息(CSI)影响系统整体误码率(BER)的问题,提出一种综合衡量两阶段信道系数的中继选择方案.首先,根据每个候选中继的CSI,比较源到中继及中继到目的的两阶段信道系数,选出两者中较差的信道状态;然后,按照较差的信道状态对候选中继排序,得到近似较优的中继节点集合;最后,从中选择两阶段信道系数之和最大者作为被选中继参与协作传输.仿真结果表明,当候选中继节点数为100及5,BER下降到10^-4及10^-5时,所提的中继选择方案与基于最优较差信道的中继选择方案、基于最近邻关系的中继选择方案相比,所需信噪比(SNR)分别降低了0.4 dB和0.2 dB.所提方案能够增加无线中继网络的信息传输范围,提高信息传输的可靠性.     

MU-MIMO系统的用户调度和预编码联合优化

提出了一种有限反馈下多用户MIMO下行链路中用户调度和预编码的联合设计方法。在该方法中,每个用户向基站反馈自己希望的预编码向量序号,以及量化误差和自己信道的最大奇异值这两个标量。基站根据估计的信干噪比,选取信干噪比最大的一个用户,利用该用户反馈的预编码向量来生成一个预编码矩阵。基站继续逐个地选择其他用户,选择的准则是用户的信道能更好地匹配这个生成的预编码矩阵中的向量。该方法同时解决了多用户MIMO系统中,用户调度和预编码向量的设计这两个问题,属于一种跨层设计。仿真结果验证了所提方法的有效性。     

User scheduling for downlink FD-MIMO systems under Rician fading exploiting statistical CSI

In this paper, we consider the user scheduling algorithm for downlink full-dimension multipleinput multiple-output (FD-MIMO) system under Rician fading channels. We assume that two-dimensional (2D) large-scale antenna array is deployed at base station (BS). An approximation of user’s signal-tointerference- plus-noise ratio (SINR) and a lower bound of user’s average signal-to-leakage-plus-noise ratio (SLNR) are derived. Based on these, two user scheduling algorithms exploiting only statistical channel state information (CSI) are proposed. The proposed algorithms take both the achievable sum rate and fairness into account. Simulation results reveal that the proposed user scheduling algorithms can make good trade-off between the achievable rate and fairness.     

一种基于MIMO预编码的多径分离方法

针对选择性MIMO信道多经分离问题,提出了一种基于预编码的收发联合设计方案。该方案中的每路发射矢量及其解码矩阵处于其他时延信道的共同零空间,把选择性信道多径分离为空间正交的若干平坦子信道,从而使平坦信道的预编码研究成果可以直接应用于选择性MIMO信道,解决了传统Z域处理中未消除ISI的问题,复杂度为Z域方法的L(多径数目)倍。仿真结果表明,该算法具有较好容量性能和误码率性能。     

Joint adaptive power allocation and interference suppression algorithms based on theMSER criterion for wireless sensor networks

In this study, a two-hop wireless sensor network with multiple relay nodes is considered where the amplify-and-forward （AF） scheme is employed. Two algorithms are presented to jointly consider interference suppression and power allocation （PA） based on the minimization of the symbol error rate （SER） criterion. A stochastic gradient （SG） algorithm is developed on the basis of the minimum-SER （MSER） criterion to jointly update the parameter vectors that allocate the power levels among the relay sensors subject to a total power constraint and the linear receiver. In addition, a conjugate gradient （CG） algorithm is developed on the basis of the SER criterion. A centralized algorithm is designed at the fusion center. Destination nodes transmit the quantized information of the PA vector to the relay nodes through a limited-feedback channel. The complexity and convergence analysis of the proposed algorithms are carried out. Simulation results show that the proposed two adaptive algorithms significantly outperform the other previously reported algorithms.     

基于协作中继的多点广播码分多址信息系统设计

为了提高多群多点广播中继网络系统的性能,提出一种改进的协作中继多点广播码分多址(CDMA)系统设计。该方案利用协作中继辅助的分布式波束形成 实现单天线基站多播,获得了较好的空间分集增益。在该系统中,多个基站利用多个中继节点向多个目的地的各个小组传播消息;利用CDMA技术来减少中继节点以及目的地节点的多址干扰(MAI)障碍,同时每个中继节点作为线性预编码波束合成器,可以在合适的代码空间重塑基站信号;对线性波束形成矩阵进行优化,使得中继节点的功率最小化,从而满足QoS在信号干扰噪声比方面的要求。系统性能仿真对比实验的结果表明,提出的改进方案明显优于传统的正交复用方案(FDMA / TDMA)。     

基于最小均方误差准则的相关旋转预编码算法

针对传统相关旋转(CR)算法放大噪声的问题,利用拉格朗日函数最小化接收信号与发射信号间的误差,通过贝叶斯理论和信道统计特性计算不完美信道状态信息,设计了信道状态信息(CSI)完美和不完美两种情况下基于最小均方误差(MMSE)准则的CR预编码算法的系统方案。分析与仿真结果表明,与传统迫零(ZF)准则下的CR算法相比较：信道状态信息完美时设计方案在同一信噪比(SNR)下误码率性能提高2~3dB;信道状态信息不完美时系统误码性能也有显著的提高。     

Optimization of resource allocation for underlay device-to-device communications in cellular networks

Underlay device-to-device (D2D) communication in cellular networks has been considered as a promising technique that can improve the spectral efficiency of cellular systems and meet the growing demand for wireless local services. In underlay D2D, it is of primary importance to manage the mutual interference between cellular links and D2D links through effective resource allocation. While most of previous works on D2D resource allocation are developed based on the knowledge of the channel state information (CSI) on the interference channels as well as the desired channels, it is hard to obtain full CSI in practice. Accordingly, we consider D2D resource allocation schemes based on distance between nodes. In particular, we formulate two optimization problems for D2D resource allocation using the outage probability computed based on the distance information as cost functions. One is a linear sum assignment problem (LSAP) and the other is a linear bottleneck assignment problem (LBAP). By applying the graph theory, we provide efficient algorithms for solving the optimization problems. Numerical results are provided to show the effectiveness of the proposed optimization as compared to previously proposed distance-based resource allocation algorithms.     

Analytical characterization of CSI quantization effects on broadband multipath channels

The knowledge of channel state information (CSI) at transmitter is crucial in precoding techniques to efficiently explore wireless multiuser multi-antenna capabilities namely to mitigate the interference and/or to separate spatial streams. For frequency division duplex systems, the CSI available is a quantized version fed back from the receivers, and the nonlinear effects associated to CSI quantization can lead to significant performance degradation. The knowledge of the statistical characteristics of those nonlinear distortion effects is important for performance evaluation purposes, as well as to design robust precoding techniques.In this paper we consider a general broadband multipath channel sampled in the frequency domain and obtain the analytical statistical characterization of the nonlinear distortion effects associated to CSI quantization. Our analytical approach is valid for non-uniform quantizers, and it also includes quantizer saturation and channel oversampling effects. It provides a detailed statistical characterization in time and frequency domains, associated to the channel impulse and frequency responses, respectively. The derived theoretical statistical characterization of quantization distortion is validated by simulation, showing its high accuracy. As an application, we consider a multicarrier transmission employing a precoding technique with reduced feedback techniques employing a small number of quantization bits per channel sample.     

一种多用户MIMO系统中有限反馈预编码算法及性能分析

多用户多输入多输出(MIMO)系统中,用户可以通过反馈的方式把信道状态信息(CSI)传递给基站,基站利用该CSI进行预编码或者用户调度,可以有效地提取复用增益。但是传统的反馈方式,反馈量太大,占用过多上行资源。针对收发都是多天线条件的多用户MIMO系统,提出一种基于Grassmannian码本的有限反馈预编码方法,通过对用户信道矩阵进行量化,每个用户仅仅需要反馈一个序号而不是信道矩阵,从而大大减少了反馈量。通过对系统误码率(BER)和吞吐率的仿真,表明了该方法能保证系统性能。同时,由于信道估计存在误差,量化过程存在误差,所以,分析了信道矩阵误差对于新方法性能的影响,得到了系统吞吐率同信道矩阵误差的方差,以及基站发射功率三者的关系,并通过仿真进行验证,从而为评估信道估计和量化过程的优劣提供了理论依据。     

Robust secrecy beamforming for full-duplex two-way relay networks under imperfect channel state information

Consider a two-way amplify-and-forward (AF) relay network where two legitimate nodes communicate through a relay in the presence of an eavesdropper. Assuming full duplexity at the legitimate nodes and the relay, a robust artificial noise (AN)-aided AF scheme is proposed to maximize the worst-case sum secrecy rate under imperfect channel state information (CSI) of the eavesdropper. This robust sum secrecy rate maximization (SSRM) problem is formulated as a max-min semi-infinite problem and is tackled by the semidefinite relaxation (SDR) method. In particular, we first convert the max-min semi-infinite problem into a maximization problem with a finite number of constraints. Then, an efficient two-block alternating difference-of-concave (DC) programming approach is proposed to iteratively solve the SDR problem, with one of the blocks computed in closed form. In addition, a specific robust rank-one solution construction procedure is presented to extract a feasible solution for the original robust SSRM problem from the SDR solution. The efficacy of the proposed method is demonstrated by numerical simulations.     

Cross-layer resource allocation in wireless multi-hop networks with outdated channel state information

The cross-layer resource allocation problem in wireless multi-hop networks （WMHNs） has been ex-tensively studied in the past few years. Most of these studies assume that every node has the perfect channel state information （CSI） of other nodes. In practical settings, however, the networks are generally dynamic and CSI usually becomes outdated when it is used, due to the time-variant channel and feedback delay. To deal with this issue, we study the cross-layer resource allocation problem in dynamic WMHNs with outdated CSI under channel conditions where there is correlation between the outdated CSI and current CSI. Two major contributions are made in this work： （1） a closed-form expression of conditional average capacity is derived under the signal-to-interference-plus-noise ratio （SINR） model; （2） a joint optimization problem of congestion control, power control, and channel allocation in the context of outdated CSI is formulated and solved in both centralized and distributed manners. Simulation results show that the network utility can be improved significantly using our proposed algorithm.     

A simple amplify-and-forward opportunistic relaying based on outdated channel state information

Opportunistic relay selection(ORS)is a promising approach for cooperative communications owing to its low complexity by activating only the best relay.However,in mobile scenarios,the channel state information(CSI)estimated in relay selection may be different from the actual CSI employed in data transmission due to relatively fast varying channels,i.e.,CSI is outdated,which may lead to incorrect relay selection,and hence system performance deteriorates.To address the problem,this paper designs a relay selection strategy with instaneous and statistical CSIs in amplify-and-forward(AF)cooperative networks whose instantaneous CSIs of two hops employed in relay selection are both outdated.Based on high signal-to-noise ratio(SNR)analysis,we propose a distinctive relay selection strategy which can be described as selecting the relay with the asymptotic optimum average symbol error probability(SEP)and outage probability at high SNR.The corresponding asymptotic outage probability and SEP performance analysis are also provided.Finally,simulation results not only validate our theoretical analysis,but also show that in asymmetrical outdated CSI scenarios,the proposed strategy achieves better performance than existing relay selection strategies at medium and high SNR values.     

Adaptive robust beamformer formulti-pair two-way relay networks with imperfect channel state information

In wideband multi-pair two-way relay networks, the performance of beamforming at a relay station (RS) is intimately related to the accuracy of the channel state information (CSI) available. The accuracy of CSI is determined by Doppler spread, delay between beamforming and channel estimation, and density of pilot symbols, including transmit power of pilot symbols. The coefficient of the Gaussian-Markov CSI error model is modeled as a function of CSI delay, Doppler spread, and signal-to-noise ratio, and can be estimated in real time. In accordance with the real-time estimated coefficients of the error model, an adaptive robust maximum signal-to-interferenceand- noise ratio (Max-SINR) plus maximum signal-to-leakage-and-noise ratio (Max-SLNR) beamformer at an RS is proposed to track the variation of the CSI error. From simulation results and analysis, it is shown that: compared to existing non-adaptive beamformers, the proposed adaptive beamformer is more robust and performs much better in the sense of bit error rate (BER); with increase in the density of transmit pilot symbols, its BER and sum-rate performances tend to those of the beamformer of Max-SINR plus Max-SLNR with ideal CSI.