MIMO多中继系统中基于不完全信道状态信息的预编码算法研究

针对配置多个中继节点的多输入多输出（Multiple-input Multiple-Output,MIMO）系统,提出一种不完全信道状态信息（Imperfect channel state information,CSI）下基于最小均方误差（Minimum Mean-Squared Error,MMSE）准则的预编码设计方案,该方案综合考虑各个节点天线之间的相关性及信道估计误差。由于各个中继端预编码矩阵之间可视为相互独立,故将约束优化问题转化为若干半正定规划问题,继而通过内点法或CVX工具箱求解预编码矩阵,然后采用求导法推导出接收端处理矩阵。最后利用迭代算法交替迭代来联合优化预编码矩阵和接收端处理矩阵,直到算法收敛。仿真结果表明,与未能综合考虑各个节点的预编码算法相比,本文提出的算法能明显改善系统BER性能。      

TD-LTE非理想信道互易性下的下行单用户波束成形算法

在TD-LTE系统中由于上下行信道的时变特性、干扰非对称特性以及射频器件非对称特性会影响基于信道互易性的波束成形技术应用,降低系统增益。针对非理想信道互易性下的预编码矩阵设计问题,以最大化接收信号平均信干噪比做为目标函数,通过计算信道状态信息(CSI)估计值以及互易性误差的统计自相关矩阵,构造正则矩阵束,将最大化接收信干噪比的预编码矩阵求解问题转化为正则矩阵束的广义特征向量求解问题。计算机仿真验证了算法设计的预编码矩阵能有效增强系统的鲁棒特性。     

一种空时相关信道下的鲁棒SLNR预编码算法

为了改善存在信道误差、空时相关条件下多用户多入多出（MIMO）系统的性能,给出了一种基于信漏噪声比（SLNR）的鲁棒预编码算法.通过推导空时相关信道环境下信道向量的条件均值和协方差,分别建立了发送端信道状态信息（CSIT）和接收端信道状态信息（CSIR）模型.在此模型基础上,推导了收发两端信道状态信息（CSI）均不理想情况下的鲁棒SLNR 预编码以及相应的接收滤波矩阵.仿真结果表明,该算法对空间相关性、时间相关性以及信道误差均具备一定的鲁棒性.     

协同系统鲁棒波束成形算法研究

由于实际很难获得理想信道状态信息(CSI),传统协同波束成形算法性能严重下降。设计对信道误差具有鲁棒性的波束成形算法具有重要的实际意义。针对放大转发协同系统最大化目的节点信噪比(SNR)准则下的波束成形设计,提出对应鲁棒算法。该算法从最坏情况鲁棒设计思想出发,建立保证鲁棒性的最优化问题,应用扩展S引理和Schur补定理将该问题由初始不可解转化为可解的准凸问题,进而求解出保证鲁棒性的波束成形因子。仿真表明:同等CSI偏差下,所提鲁棒算法的中断概率性能优于传统波束成形算法。     

基于协作多点下行传输的非线性鲁棒预编码

对于协作多点系统,下行信道信息误差会大幅降低联合传输的性能。为了避免下行信道信息误差对联合传输的影响,本文利用其二阶统计特性,设计了非线性鲁棒预编码算法。由于协作多点系统的特点和非线性鲁棒预编码的结构会导致用户间的性能差异,本文通过优化非线性鲁棒预编码算法的连续干扰消除先后顺序,从而改善性能最差用户的误码率,降低非线性鲁棒预编码算法的平均误码率。仿真结果表明当下行信道信息误差存在时,本文所提出的非线性鲁棒预编码性能优于传统的线性和非线性预编码性能。仿真结果还表明优化排序能提高非线性鲁棒预编码的性能增益。     

上行多用户MIMO中继系统中基于不完全信道状态信息的预编码算法

论文研究了存在信道估计误差及天线相关条件下,上行多用户MIMO中继系统的预编码问题,目标是提升系统的误比特率性能。针对基于放大转发中继技术的上行多用户MIMO中继系统,考虑源-中继和中继-目的端信道中存在的信道估计误差及天线相关,提出一种基于不完全信道状态信息(Channel State Information, CSI)的预编码设计方案。首先根据最小均方误差(Minimum Mean-Squared Error, MMSE)准则设计代价函数,以发射端和中继端最大功率为约束条件,通过理论推导求得中继端和发射端的线性预编码矩阵,最后采用迭代下降法得到接收端处理矩阵的闭式解。数值仿真结果表明,在存在信道估计误差和天线相关的条件下,与现有算法相比,所提算法能有效降低系统的误比特率。     

大规模MIMO时分双工系统的鲁棒预编码设计

对于采用大规模MIMO技术的时分双工系统,天线互易误差会破坏上下行信道互易特性,大幅降低预编码算法下行传输性能。由于实际系统难以完全消除天线互易误差,该文以最大化各用户平均信泄噪比为目标,根据天线互易误差的统计特性,设计了对该误差具有鲁棒性的线性预编码算法。同时为了进一步降低用户接收端的等效噪声功率,该文还将该线性鲁棒预编码算法扩展为基于矢量扰动的非线性鲁棒预编码算法,并通过减格辅助技术降低其扰动矢量求解复杂度,使其更适用于大规模MIMO系统应用。计算机仿真结果表明在存在基站天线互易误差条件下,该文所提出的线性与非线性鲁棒性预编码算法的性能均优于传统预编码算法的性能。     

一种基于QR分解的稳健干扰对齐算法

大多数干扰对齐算法都假定发送端可以获得理想的信道状态信息(CSI),由于信道估计误差、反馈延迟等原因,实际通信系统中CSI往往是有误差的。为此,该文提出一种基于QR分解的稳健干扰对齐算法。对含有误差的联合接收信号进行基于QR分解的预处理,消除一半有误差的干扰;然后在有误差的等效信道联合矩阵下,充分考虑信道误差和干扰的影响,通过最小化发送端泄漏到非目标接收端的干扰信号功率来设计预编码矩阵,并基于最小均方误差(MMSE)准则来设计干扰抑制矩阵。最后,在理想CSI和误差CSI的情况下,通过实验仿真,证明了该算法有效地提高了系统性能。     

大规模MU-MIMO系统归一化预编码算法

针对大规模MU-MIMO系统中预编码技术性能不佳的问题,在不完善信道状态信息(CSI)的情况下,对迫零(ZF)和最大比发射(MRT)预编码技术提出了两种归一化算法：向量归一化与矩阵归一化。首先基站通过上行导频序列估计CSI,并在下行链路中用所提的算法对预编码矩阵进行归一化处理,然后将其与发送信号以及信道进行匹配。仿真结果表明,在高信噪比时,ZF预编码使用向量归一化算法实现了更好的系统性能;而在低信噪比时,MRT预编码使用矩阵归一化算法使系统性能得到了良好改善。     

OFDM调制系统中一种鲁棒的MMSE信道均衡算法

在OFDM调制系统中,由于多载波的存在,载波间ICI对信道均衡结果影响很大,同时,采用MMSE信道均衡算法对不同的信道模型也存在均衡误差不稳定的情况。本文提出一种鲁棒的MMSE信道均衡算法,该算法的核心是针对不同信道对信道的PDP进行归一化处理,从而得到在不同类型信道下稳定且鲁棒的信道均衡性能。     

Capacity of a Multiple-Antenna Fading Channel With a Quantized Precoding Matrix

Given a multiple-input multiple-output (MIMO) channel, feedback from the receiver can be used to specify a transmit precoding matrix, which selectively activates the strongest channel modes. Here we analyze the performance of random vector quantization (RVQ), in which the precoding matrix is selected from a random codebook containing independent, isotropically distributed entries. We assume that channel elements are independent and identically distributed (i.i.d.) and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using $B$ bits. We first derive the large system capacity of beamforming (rank-one precoding matrix) as a function of $B$, where large system refers to the limit as $B$ and the number of transmit and receive antennas all go to infinity with fixed ratios. RVQ for beamforming is asymptotically optimal, i.e., no other quantization scheme can achieve a larger asymptotic rate. We subsequently consider a precoding matrix with arbitrary rank, and approximate the asymptotic RVQ performance with optimal and linear receivers (matched filter and minimum mean squared error (MMSE)). Numerical examples show that these approximations accurately predict the performance of finite-size systems of interest. Given a target spectral efficiency, numerical examples show that the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback.      

Design of Robust Transceiver for Precoded Uplink MU-MIMO Transmission in Limited Feedback System

This paper proposes a robust transceiver design against the effect of channel state information (CSI) estimation error to optimize precoded uplink (UL) multi-user multiple-input multiple-output (MU-MIMO) transmission in limited feedback system under the consideration of the least-square technique on CSI estimation. To improve this limited feedback precoding, the constrained minimum variance (MV) approach with quadratic form to realize the computationally-efficient optimization problem, advantageously invoking the characteristics of the CSI estimation error, is proposed to suppress the effect of CSI estimation error, multiple user interference and noise. According to the Lagrange multiplier method on this MV approach, the deterministic function to resist uncertain CSI can be obtained to optimize design of the precoder and adaptive matrices jointly. With these optimum adaptive and precoder matrices, an optimum robust weighting matrix can be obtained to facilitate the user-wise detection in precoded UL MU-MIMO system. Performance analysis shows that the proposed robust weighting matrix is an unbiased design and it also can regularize the diagonal loading factor technique, and the detection performance of the proposed robust transceiver design can be predicted simplistically by applying our derived signal-to-interference-plus-noise ratio formulation. Computer simulations are conducted to confirm the efficacy of the proposed design in both perfect and imperfect CSI estimation.     

Multiple antenna MMSE based downlink precoding with quantized feedback or channel mismatch

In this paper, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. In any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-tonoise ratio (SNR) regime, and similar to [1], [2], it is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance.     

多小区块对角化的MMSE矢量扰动预编码

针对多小区基站协作的多输入多输出(MIMO)系统中,小区之间和用户之间的干扰对系统造成的性能降低的问题,提出了基于块对角化的最小均方误差(MMSE)矢量扰动预编码方案,实现多小区系统的性能改善。首先使用块对角化方法消除多小区间干扰;在预编码设计环节上,通过MMSE准则设计预编码矩阵,从而抑制病态信道对系统性能的影响;最后使用格基规约方法求解发射端矢量扰动信号。仿真表明,提出的算法提高了多小区矢量预编码的误码率性能,使其优于已有的块对角化及矢量扰动预编码等算法的误码率。     

Cellular Downlink Performance with Covariance-CSIT-Based MIMO Precoding

The nature of the trade-off between reduced overhead of channel state information (CSI) and resultant performance losses influences the design of frequency-division duplexed practical cellular systems. One candidate for CSI feedback reduction is the use of covariance-matrix-based CSI at the transmitter (CSIT) in conjunction with linear precoding techniques. This paper analyzes the performance of such systems in the downlink for both single-user (SU-) and multiuser (MU-) multiple-input multiple output (MIMO) in comparison to those using optimal perfect-instantaneous-CSIT-based precoding. In addition, the effectiveness of techniques enforcing frequency domain diversity versus those based on the maximal ergodic channel capacity criterion is evaluated. A novel precoding scheme using covariance matrix information that supports spatial multiplexing in both SU- and MU-MIMO is proposed. Simulation results show that the spectral efficiency loss from covariance-CSIT-based techniques from those utilizing perfect, instantaneous CSIT is shown to be about 1 dB in a highly correlated urban channel environment for both SU- and MU-MIMO, whereas for microcell environments it is between 3 and 4 dB.     

融合蚁群算法MMSE准则在MMW 混合波束形成中的应用

波束形成预编码技术是毫米波通信的核心技术,其中模拟和数字混合波束形成技术可以很好地平衡 模拟预编码技术和数字预编码技术的优缺点,既可以得到足够的波束形成增益、减少传播损耗,又降低了硬件成本 和功耗。均方误差(MSE)是表征毫米波通信传输可靠性的性能指标,利用最小均方误差(MMSE)准则的混合预编码 设计可以在毫米波大规模多输入多输出(MIMO)系统中获得较好的频谱效率。将MMSE 与广泛应用于解决旅行商 问题的蚁群算法相融合,以进一步优化基于流形优化的混合预编码算法。仿真结果表明,融合后的优化算法具有更 低的误码率和更好的频谱效率。     

Robust Cognitive Beamforming With Bounded Channel Uncertainties

This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users. We aim to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINRs) of the SUs, subject to the constraints of the total SU transmit power and the received interference power at the primary users (PUs) by optimizing the beamforming vectors at the SU transmitter based on imperfect channel state information (CSI). To model the uncertainty in CSI, we consider a bounded region for both cases of channel matrices and channel covariance matrices. As such, the optimization is done while satisfying the interference constraints for all possible CSI error realizations. We shall first derive equivalent conditions for the interference constraints and then convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation, which leads to iterative algorithms for obtaining the robust optimal beamforming solution. Results demonstrate the achieved robustness and the performance gain over conventional approaches and that the proposed algorithms can obtain the exact robust optimal solution with high probability.      

基于协作多点传输的非线性顽健预编码

A nonlinear robust precoding algorithm was proposed,which redesigned the feedback matrix,the forward matrix and the scaling matrix of the traditional tomlinson-harashima precoding algorithm based on the statistical characteristics of the downlink channel state information errors.Simulation results show that the nonlinear robust precoding algorithm can achieve better performance than the traditional linear and nonlinear precoding algorithms when the downlink channel state information errors exist.Due to the different downlink channel state information errors between user equipments in the coordinated multi-point transmission,the traditional “best-first” ordering algorithm was invalid.So an improved ordering algorithm was proposed to reduce the average bit error rate of the nonlinear robust precoding algorithm.     

Performance Analysis of Dual-Hop AF Relay Networks in the Presence of Channel Estimation Errors and Feedback Delay

In this letter, we investigate the performance of multiple-input multiple-output two hop beamforming amplify-and-forward (AF) relay networks under imperfect channel state information (CSI) including channel estimation errors (CEE) and feedback delay (FD). To quantify the effect of imperfect CSI on our considered network, we derive the closed-form expression for the outage probability. To gain more insight, we also present an asymptotic analysis which provides the details of the diversity order and array gain. Through our works, one can see the effect of CEE and FD on the system as well as the benefits of deploying multiple antennas at the terminals. Numerical and simulation results are provided to verify the analysis and compare the performance of the considered network for two different models for channel estimation error.