基于粒子群优化的MIMO系统判决反馈均衡研究

为了更好地消除多输入多输出(MIMO)系统中的码间干扰(ISI),提出了一种基于粒子群优化(PSO)的判决反馈均衡(DFE)算法;将该算法与基于最小均方(LMS)算法的判决反馈均衡进行了比较.仿真结果表明,PSO DFE的误码率性能明显优于LMS DFE,且收敛速度快.     

基于空间投影的全双工MIMO中继站自反馈干扰抑制

建立由基站、全双工MIMO中继站和用户站组成的系统模型,获得MIMO自反馈干扰矩阵.当自反馈干扰信号最大多径时延大于符号周期时,根据自反馈干扰矩阵张成空间,设计并添加信号空间投影滤波器到中继站中实现自反馈干扰抑制.针对自反馈干扰矩阵是否满秩,滤波器设计分别采用子空间和零空间投影算法,并讨论了不同投影算法下对中继站接收信号误码率影响和自干扰信号的残留量.理论分析和仿真结果表明,所提出的空间投影算法对自反馈干扰的抑制有较理想的效果.     

基于盲判决反馈均衡的GPS信号多径干扰抑制方法

给出了存在多径效应时的GPS接收信号模型,分析了多径干扰对GPS接收机跟踪环路的影响,将均衡技术应用于跟踪环路,提出了一种GPS信号多径干扰抑制方法.该方法在GPS信号跟踪环路中引入了判决反馈分数间隔均衡器,同时,根据GPS信号为BPSK调制且发送的伪码序列被导航电文调制后存在正负反转不确定性的特点,均衡器系数更新时选...     

基于多用户反馈的判决反馈均衡器的研究

本文提出的一种新颖的基于多用户反馈的判决反馈均衡器,解决了在CDMA多用户检测中传统自适应判决反馈均衡器误码率高、系统容量小的缺点.它由具有误差反馈滤波器的判决反馈均衡器(Decision Feedback Equalizer with Error Feedback Filter,DFE-EFF)构成,并在判决后反馈多用户数据抵消多址干扰(多用户反馈干扰抵消).文中给出其结构图,分析各种判决反馈均衡算法.理论证明,具有误差反馈滤波器的多用户反馈干扰抵消判决反馈均衡器(多用户反馈干扰抵消DFE-EFF)较各种判决反馈均衡器为最优,它能同时有效处理ISI,MAI和噪声的干扰.仿真结果表明,在误码率性能和系统容量两方面,多用户反馈干扰抵消DFE-EFF比DFE、DFE-EFF均有较大改善.     

高频段下新MIMO时域均衡算法仿真研究

借鉴V-BLAST的MIMO检测思想,针对高频段信道提出了一种新的MIMO时域均衡算法,该算法基于特定的判决反馈均衡器结构,滤波器的系数可通过信道估计计算得到。新算法通过迭代进行分层均衡,前一层均衡出的发射信号可用于后一层均衡时的干扰消除。仿真表明,这一新算法不但计算复杂度低,还能有效地改善系统的误码性能。     

基于波束空间的米波MIMO雷达角度估计算法

针对米波多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达低仰角估计的问题,提出了一种基于波束空间的角度估计算法.结合米波MIMO雷达低仰角目标的回波特点,建立了同时考虑发射多径和接收多径的信号模型.算法首先在接收端形成多个接收波束,再利用发射信号进行匹配滤波,然后在接收端形成多...     

FMT系统中的迭代信道估计和Turbo均衡

在滤波多音调制(FMT)系统中,为了消除由于原型滤波器非理想重构特性和多径信道所导致的符号间干扰,提出了一种联合迭代信道估计和Turbo均衡的FMT系统接收方法,通过对FMT系统中每个子信道的等效冲激响应进行迭代估计,然后采用基于线性滤波器结构的Turbo均衡器来消除符号间干扰.仿真结果表明,不论采用QPSK调制方式还是16QAM调制方式,经过2次以上的迭代后,相比较于传统的判决反馈均衡算法,新算法的误码率性能得到了大大改善.     

一种GI不足的OFDM均衡算法研究

提出一种基于FIR反馈的均衡方法,利用FIR滤波器反映出多径的信息,并从接收信号中将滤波器输出的多径成分减去,这样就实现了消除码间干扰的目的,算法原理简单,通过在DVB-T系统平台中对算法的实现和仿真验证表明,均衡算法可以抵抗因为GI不足造成的ISI和ICI干扰.     

严格采样FMT系统频域均衡算法

根据滤波多音调制(FMT)系统基本原理推导了严格采样FMT系统的矩阵表示式,并针对严格采样FMT系统符号间干扰(ISI)严重的问题,根据最小均方误差准则提出了一种子信道频域均衡算法,给出了新算法的最小二乘迭代实现.仿真结果表明,新算法能有效均衡FMT信号,相比较于判决反馈均衡(DFE)算法,新算法的实现结构更简单并且误码率性能更好.     

一种改进的判决反馈盲均衡算法研究

以提高信号传输的效率,消除多径效应对传输信号的影响为背景,首先介绍了判决反馈盲均衡算法(DFE算法)的均衡原理,并且在此基础上提出了改进的分数间隔变步长判决反馈盲均衡算法(FSE-VSDFE算法).通过实验仿真结果的分析可知,改进方法在收敛速度、剩余误差等方面取得了明显的改善,具有一定的实际应用价值.     

Interference Cancellation with Space Diversity for Downlink MC-CDMA Systems

Modern wireless communications require an efficient spectrum usage and high channel capacity and throughput. Multiple-input and multiple-output (MIMO), Linear equalizers, multi-user detection and multicarrier code-division multiple access (MC-CDMA) are possible solutions to achieve spectral efficiency, high channel capacity, eliminate multiple access interference (MAI), eliminate Inter symbol interference (ISI) and robustness against frequency selective fading. In this paper, we combine all these techniques and investigate BER performance. We propose a low complexity receiver structure for Single-input Multiple-output (SIMO) downlink MC-CDMA systems. It employs an interference cancellation scheme to suppress the interference caused by the multipath fading channel. Also, the proposed scheme is developed for MIMO MC-CDMA system. The performance analysis of Downlink MIMO MC-CDMA systems with V-BLAST over frequency selective fading channel is investigated under various number of transmit and receive antennas. The simulation results show proposed SIMO equalization with parallel interference cancellation scheme is effective in reducing the ISI and the MAI. It improves the performance significantly and the simulation results show that MIMO MC-CDMA with V-BLAST multi-user detection provides high data rate and the BER significant improvement.     

Multistage soft decision equalization technique for MIMO systems in frequency selective channels

This article proposes a multistage soft decision equalization （SDE） technique for block transmission over frequency selective multi-input multi-output （MIMO） channels. Using the Toeplitz structure, the general signal model can be converted into a series of small-sized sub-signal models. For each sub-signal model, soft interference cancellation （SIC） is used firstly to remove partial effects of interfering symbols, then max-log-map sphere decoder is performed to get the desired a posteriori information. Simulation shows that with lower complexity the proposed method outperforms the probability data association SDE and the Schnorr-Euchner sphere decoder.     

基于软判决的MMSE-OSIC接收机

串行干扰相消接收机是广泛应用于多输入多输出系统中的一种接收端信号处理与检测技术。在串行干扰相消接收机中,先检测的层的判决准确性会对后续层的检测产生影响。检测过程中产生的判决误差,将对后续层的检测引入残留干扰,进而影响后续层检测的正确性,造成差错传播。本文提出一种基于软判决的最小均方误差检测带排序串行干扰相消接收机,可以有效减轻基于硬判决方法的带排序串行干扰相消接收机的差错传播问题。在重构干扰信号时,该接收机使用根据软判决信息得到的符号期望,替代硬判决方法,能够有效降低干扰相消时各层之间由判决误差引起的残留干扰;该接收机还可以精确估计残留干扰的功率以及各层数据流的后处理信干噪比,改善了基于硬判决方法的串行干扰相消接收机存在的各层后处理信干噪比估计值偏大的问题。可靠性更高的软判决结果有效降低了残留干扰,更精确的各层后处理信干噪比抑制了残留干扰对后续数据流检测的影响,提高了判决结果和排序过程的准确性。仿真结果证明,基于软判决的最小均方误差检测带排序串行干扰相消接收机可以有效避免差错传播的产生,因而获得较大的性能提升。      

Layered space-time equalization for wireless MIMO systems

We investigate layered space-time equalization (LSTE) architectures for multiple-input multiple-output (MIMO) frequency-selective channels. At each stage or layer of detection, a MIMO delayed decision feedback sequence estimator (MIMO-DDFSE) is used to tentatively detect a group of selected data streams, among which a subgroup of data streams are output and are canceled from the received signals. With the proposed architectures, the numbers of the tentatively detected data streams and output data streams can be different at different LSTE stages, while the MIMO-DDFSE can also reduce to the special cases of multiple-input single-output decision feedback equalizer (MISO-DFE), MISO-DDFSE, and MIMO-DFE, allowing tradeoffs between performance and complexity. We also derive the equalizer coefficients, discuss timing recovery, and consider channel estimation. Simulation results demonstrate the performance of the proposed LSTE structures and the tradeoffs between performance and complexity of the multistage structure and the single-stage version. We also demonstrate the impact of imperfect channel estimation, imperfect interference cancellation, the number of receive antennas, filter length, and oversampling on performance.     

非精确信道状态信息下MIMO系统中的干扰删除

复杂的多天线环境中,未知的干扰和噪声无处不在,这些因素不但引起了多输入多输出(MIMO)系统信号检测的偏差,还加大了获取精确信道状态信息(CSI)的难度。因此,为了删除MIMO系统中的未知干扰,该文建立了非精确CSI下的系统模型,模型中的非线性函数表示MIMO系统中的干扰。基于非参数理论提出了针对这种干扰的干扰删除方法。与以往方法不同的是,模型中的干扰是完全未知的。进一步地,从理论上证明了干扰删除的有效性,即证明了估计函数的收敛性。仿真结果表明,所提出的方法能有效地删除系统中的干扰。     

Adaptive Two-Stage GSC-Based PIC Detection for Time-Varying MIMO Channels

Adaptive parallel interference cancellation (PIC) has been recently proposed for the signal detection in multiple- input multiple-output (MIMO) systems. However, it suffers from error propagation when operated in time-varying channels. In this letter, an adaptive two-stage PIC with the minimum variance (MV) criterion is proposed to solve the problem. Adaptation with the MV criterion is realized with a decision feedback generalized sidelobe canceller (DFGSC). In the first-stage cancellation, a special structure involving dual DFGSCs is developed. All adaptation operations are implemented with the least-mean-square (LMS) algorithm. Simulations show that the proposed adaptive PIC detection can significantly outperform the conventional adaptive PIC detection in time-varying MIMO channel environments.     

MIMO系统中基于信号可靠性判定的OSIC检测

排序串行干扰消除（Ordered Successive Interference Cancellation,OSIC）是多输入多输出无线通信系统中一种重要的信号检测技术。为了降低该算法的计算复杂度,首先提出了基于信号可靠性判决的排序串行干扰消除算法,根据所设计的信号可靠性判决（Signal Reliability Decision,SRD）结构的判决结果选择不同的方法消除信号间的干扰。为了进一步提升SRD-OSIC算法的检测性能,提出了局部最优（Local Optimized,LO）的LO-SRD-OSIC算法。仿真结果表明,SRD-OSIC算法仅需要传统OSIC算法一半的复杂度就能获得相近的误码率性能。不仅如此,当LO-SRD-OSIC算法与SRD-OSIC算法的计算复杂度相同时,LO-SRD-OSIC算法可以获得额外3 dB的误码率性能增益。     

MIMO blind equalization algorithm based on successive interference cancellation

Modified Constant Modulus Algorithm (MCMA) is widely used in the SISO blind equalization for its simplicity. For MIMO systems MCMA can only equalize one of the source signals. Through the combination of channel estimation and successive interference cancellation, source signals can be equalized in turn. However the recovery of the first source and the channel estimation are the key points, which directly affects the recovery of the subsequent sources. This paper proposes a channel estimation method with a small amount of calculation, and can accurately estimate the channel vector. Meanwhile, a new blind equalization algorithm is put forward to reliably recovery the first source signal. Simulation results verify the effectiveness of the proposed algorithm.     

Blind equalization in spatial multiplexing MIMO-OFDM systems based on vector CMA and decorrelation criteria

In this paper we address the problem of blind recovery of multiple OFDM data streams in a Multiple-Input Multiple-Output (MIMO) system. We propose an equalization algorithm which is based on a combined criterion designed to cancel both inter-symbol interference (ISI) and co-channel interference (CCI). ISI is minimized by using a modified Vector Constant Modulus criterion while CCI is minimized by a decorrelation criterion. We establish conditions for the existence of the stable minima corresponding to the zero forcing receiver which performs the joint blind equalization and the co-channel signal cancellation. The local convergence properties of the algorithm are proved under the assumption that the balance parameter weighting the two criteria is set appropriately. We also provide the optimal value for this parameter. Reliable performance is achieved with relatively fast convergence and small steady-state error. The implementation of the blind equalizer requires low-computational cost, without any matrix inversions or other expensive operations.