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多天线通信系统中的信号检测与信道估计技术研究
Research on Signal Detection and Channel Estimation in Multi-antenna Communication Systems
【作者】 景小荣;
【导师】 周正中;
【作者基本信息】 电子科技大学 , 电路与系统, 2009, 博士
【摘要】 近年来,由于多媒体、Internet等数据业务的迅猛增长,要求未来的无线通信系统能够提供更高的数据传输率,以满足人们日益增长的数据业务的需求。目前有多种技术可作为未来无线通信系统中的候选关键技术,其中多输入多输出(Mulitple-Input Mulitple-Output,MIMO)技术,由于能够在功率及频谱带宽保持不变的情况下,成倍地提高通信系统的容量和频谱利用率,从而为未来宽带高速无线数据通信技术的发展指明了方向。本论文首先对MIMO无线通信系统中信号检测与信道估计研究的现状进行了系统的总结,并指出了目前该领域仍有待解决的若干重要问题,然后简要地概述了本文所进行的主要研究工作和取得的创新性成果。在论文的第二部分,针对独立的Rayleigh平坦衰落信道环境中的垂直-贝尔实验室分层空时(Vertical Bell Laboratories Layered Space Time,V-BLAST)系统,在对信道矩阵作修正的选主列QR分解(QR-Decomposition,QRD)的基础上,联合球形译码(Sphere Decoding,SD)算法和逐层检测算法,本论文提出了一种基于信道质量的自适应分组检测算法。在该算法中,可通过分组门限的选择,在系统检测性能和复杂度之间取得十分灵活的折中。更有意义的是:该自适应分组算法从概率意义上将SD算法和逐层检测算法统一了起来。在论文的第三部分,主要研究了空间相关平坦衰落信道环境中数值稳健的低复杂度V-BLAST检测算法。首先,利用Householder变换,并结合WY表示形式,本论文提出了一种基于修正的Householder QRD(Modified Householder QRD,M-H-QRD)的V-BLAST检测算法。理论分析表明:在空间相关信道环境中,与标准的V-BLAST检测算法及排序QRD(Sorted-QRD,S-QRD)检测算法相比,M-H-QRD检测算法具有稳健的数值特性,特别地,在有限字长(Finite Word Length,FWL)精度下,M-H-QRD检测算法需要更少的字长就可达到与S-QRD检测算法同等的差错平层;同时,在中低信噪比范围内,该算法的性能十分接近标准的V-BLAST检测算法,但所需的计算复杂度与标准的V-BLAST检测算法相比,下降十分明显。在这些结论的基础上,考虑到具有较少收发天线数的V-BLAST系统通常具有更高的实用价值。因此,以M-H-QRD为基础,针对具有较少收发天线数的V-BLAST系统,本论文提出了一种基于M-H-QRD的V-BLAST迭代检测算法。仿真结果表明:迭代检测对V-BLAST系统的性能提升十分明显,同时又保留了M-H-QRD数值稳健性的优点。论文接下来研究了时变平坦衰落信道环境下Alamouti空时编码系统中的半盲信道估计及Alamouti空时码(Space-Time code,STC)的译码问题,本论文提出了两种联合译码与半盲信道估计算法。其中一种算法利用线性插值首先对信道估计进行初始化,然后根据期望最大化(Expectation-Maximization,EM)算法,以迭代方式,实现了Alamouti空时编码系统的联合译码与信道估计,并且研究了数据帧长对该算法性能的影响。另外一种算法联合Kalman滤波与框式约束ML(Box-Constrained ML,BCML)检测算法,实现了时变信道的即时追踪与AlamoutiSTC的译码。最后研究了时变频率选择性MIMO信道环境中的符号检测及信道追踪问题,本论文提出了一种带自适应信道追踪的、计算复杂度可控的序列检测方法,即Γ-H-MLSE方法。该方法对于将MLSE(Maximum Likelihood Sequence Estimation,MLSE)算法的思想推广到实际的多天线通信系统中具有一定的参考价值。
【Abstract】 In recent years,due to the rapid development of the data services such asmultimedia and Intemet,the higher data transmission rate has been required for futurewireless communications in order to meet the people’s growing demand.Currently,there are a variety of techniques that can be used as the key candidates for futurewireless communications,among which Mulitple-Input Mulitple-Output (MIMO)technology gives direction to the development of the future broadband high-speedwireless data communications technology since it can dramatically improve the channelcapacity and spectrum efficiency without increasing the power and bandwidth.We firstly survey the research status of the signal detection and channel estimationin MIMO system and point out a variety of important problems and questions needed tobe solved.Then the main research contents and contributions of this dissertation areoutlined.In the second part of the dissertation,at the basis of the modifiedQR-Decomposition (QRD) with column pivoting,an adaptive group detectionalgorithm based on channel quality is proposed by combining the sphere decoding (SD)algorithm and the layer-by-layer detection method for Vertical Bell Laboratories SpaceTime (V-BLAST) system over an i.i.d.Rayleigh flat-fading channels.Very flexibletradeoff can be achieved between performance and complexity via selecting the groupthresholds.More significantly,the proposed algorithm unifies the SD algorithm and thelayer-by-layer detection method into one fiamework in a probability sense.In the third part of the dissertation,we focus on numerically robust andlow-complexity V-BLAST detection algorithm over the spatially correlated channels.Using Householder transformation,and combining with the WY representation,afeasible V-BLAST detection algorithm based on the modified Householder QRD(M-H-QRD) is firstly proposed for the spatially correlated flat-fading channels.Theoretical analysis shows that the proposed M-H-QRD detection algorithm has robustnumerical property in contrast to the standard V-BLAST detection algorithm and thesorted QRD (S-QRD) detection algorithm over spatially correlated channel environments.Specially,compared to the S-QRD detection algorithm,the M-H-QRDdetection algorithm needs a smaller minimum word-length to reach the same value ofthe error floor for finite word length (FWL) precisions.Moreover,the proposedalgorithm can almost match the detection performance of the standard V-BLASTalgorithm in the moderate and low SNR region with much reduced computationalcomplexity.Then,for the practical purpose,an iterative detection algorithm based onthe M-H-QRD is proposed for V-BLAST system with the small number of receiver andtransmitter antennas.Simulation results show that the iterative scheme can achievemuch performance superiority over the standard V-BLAST algorithm with robustnumerical stability of the M-H-QRD.In the next part of the dissertation,we investigate the semi-blind channelestimation and decoding for the Alamouti space-time coded system over time-varyingfiat-fading channels,and two joint decoding and semi-blind channel estimationalgorithms are proposed.The first one,at the basis of channel estimation initializationby linear interpolation algorithm,employs the expectation-maximization (EM)algorithm to implement the joint Alamouti space-time code (STC)decoding and channelestimation in an iterative mode.The effects of the frame length of the data on theperformance of the algorithm are particully investigated.The other one combines theKalman filtering and the box-constrained ML (BCML) algorithm,in which the Kalmanfiltering is employed to tracking the time-varying channel,and then Alamouti STC isdecoded by BCML algorithm.Finally,we investigate the signal detection and channel tracking over the MIMOtime-varying frequency-selective channels and propose a complexity-controllablesequence detection method (i.e.Γ-H-MLSE method) with adaptive channel tracking.The proposed method has a certain reference value for extending the ideal of themaximum likelihood sequence estimation (MLSE) algorithm into multi-antennacommunication systems.
【Key words】 MIMO system; V-BLAST; Alamouti space-time code; signal detection; channel estimation; flat-fading; frequency-selective fading; maximum likelihood sequence estimation; Kalman filtering; Expectation-Maximization algorithm;