一种适用于稀疏多径信道的自适应均衡算法

针对传统的自适应均衡算法在稀疏多径信道下性能表现不佳的问题,提出了一种基于基追踪降噪的自适应均衡算法。该算法利用稀疏多径信道下均衡器权值的稀疏性,将自适应均衡器的训练过程看作压缩感知理论中稀疏信号对字典的加权求和,并利用重构算法直接对稀疏权值进行求解,解决了迭代参数设置和收敛慢的问题。采用基追踪降噪作为重构算法并选用变量分离近似稀疏重构对该最优化问题进行求解,既提高了权值的重构精度又降低了计算的复杂度。仿真结果表明,所提算法能够以较低的计算量和较少的训练序列达到更优性能,这对提升系统的通信性能具有参考价值。     

一种基于信道缩短的MB-OFDM UWB稀疏信道估计算法

在MB-OFDMUWB系统中,利用UWB信道的稀疏簇特性,提出一种基于信道缩短的MB-UWB稀疏信道估计算法。首先利用信道缩短滤波器来消除由于循环前缀长度不足造成信道间干扰和码间干扰,然后基于信道缩短后的接收信号,利用UWB信道的稀疏性,探测出非零值抽头的位置,避免了无谓的零值抽头估计,改善了算法的性能。仿真结果表明:当循环前缀CP长度小于信道长度时,LS算法和DFT算法逐渐失效,而新算法可以获得较好的估计性能。     

MIMO-OFDM快衰落信道的稀疏自适应感知估计

在多输入多输出（MIMO）-正交频分复用（OFDM） 系统中,怎样在较高频谱利用率的情况下对快时变信道进行较为准确的估计是一个具有挑战性的课题。该文在利用压缩感知理论可提高系统频谱利用率的基础上,提出了一种适合于快时变环境下MIMO-OFDM 系统的稀疏自适应信道估计方法。该方法不再受到奈奎斯特采样频率条件约束,避免了传统导频辅助信道估计方法频谱利用率低的缺点。该文方法通过构建多天线群时频结构特征稀疏基,利用多天线间和群时变OFDM符号内信道冲激响应具有更强稀疏性的特点,对MIMO-OFDM快衰落信道进行稀疏变换。由于实际MIMO-OFDM快衰落信道往往处于频率选择性、时变性和多种干扰并存的复杂环境,受到干扰的信道参数对系统而言是未知,采用该方法克服了现有基于压缩感知理论的信道估计方法需要预先知道信道冲激响应稀疏度才能重构信道参数的不足,在信道稀疏度未知道的情况下,运用稀疏自适应的方法来对不同时频结构特征的信道参数进行估计。仿真结果表明所提估计方法具有对快时变信道参数估计的鲁棒性和较高频谱利用率,且均方误差小。      

一种改进的稀疏多径信道盲辨识算法

针对无线多径稀疏信道,利用信道有效近似思想,提出了一种改进的基于矩阵外积分解的信道盲辨识与盲均衡算法。算法首先利用改进的VIA信道阶数估计准则,对多径稀疏信道“有效部分”的阶数进行精确估计,然后利用改进的矩阵外积分解算法估计出信道冲激响应的“有效部分”,最后利用该估计结果对接收数据进行反卷积运算,恢复出发送信号。为了降低噪声以及信道冲激响应中的“零抽头”部分对信道盲辨识性能的影响,本算法对噪声方差估计方法进行了改进,提高了算法在中、低信噪比条件下的盲辨识性能。与现有算法相比,本算法不仅降低了对信噪比的要求,而且克服了基于LC准则的子空间算法(SSA, Subspace Algorithm)的相位偏转问题,其中噪声方差的估计方法也可应用于信噪比估计技术。仿真实验以及对SPIB微波信道测试结果验证了本文算法的有效性。      

一种改进的重构算法在信道估计中的应用

研究了在多天线正交频分复用系统信道估计问题。特别利用了宽带MIMO-OFDM系统的时域稀疏特性,来研究这个系统中的基于导频符号的信道估计技术。本文将压缩感知理论应用在稀疏信道估计中,对现有的重构算法进行改进,在不需要预先知道信道的稀疏度信息就利用分次迭代,逐步逼近的方法可以精确重构信号。仿真结果表明,本文提出的信道估计方法性能更加良好。     

用Laguerre滤波器实现多径衰落信道自适应均衡

提出了一种衰落信道自适应均衡的新方法。该方法基于Laguerre滤波器结构,采用最小二乘估计估算滤波器极点,通过RLS算法实现自适应过程。仿真结果表明,由于Laguerre滤波器同时具有FIR和ⅡR结构的特点,在信噪比低、信道多径条件复杂的情况下,可以获得比通常的线性自适应均衡器和决策反馈均衡器更好的抗符号间干扰的效果;同时,Laguerre滤波器结构的稳定性有效地减少了差错传播的发生。     

衰落信道基于卡尔曼滤波的信噪比估计

无线通信场景中,由于复杂的电磁环境及移动通信双方之间的相对运动,使无线信道存在着严重的多径衰落及多普勒效应.信噪比是通信信道的重要衡量指标,直接指导通信策略的制定.针对多径衰落信道条件,提出基于卡尔曼滤波辅助的信噪比估计算法,利用卡尔曼滤波的方法对信道进行平滑,之后选取合适的长度进行信噪比估计.最后针对不同信道条件下信...     

MIMO-OFDM快衰落信道的压缩感知估计方法

在快衰落多输入多输出(MIMO)-正交频分复用(OFDM)系统中,为了避免传统的信道估计方法中存在大量系数需要估计的问题,利用快衰落信道在角时延多普勒域可稀疏的特性,提出了基于压缩感知的MIMO-OFDM系统快衰落信道估计方法。根据压缩感知的受限等距特性(RIP),推导了一种少量导频随机结构测量矩阵,用于测量快衰落信道在角时延多普勒域稀疏系数。接收端可从这些少量的测量数据中以高概率重构出快衰落信道。理论分析与仿真结果都表明:该方法与传统的信道估计方法相比,所得到的系统数据传输效率及估计性能都有了明显提高。     

一种稀疏增强的压缩感知MIMO-OFDM信道估计算法

基于压缩感知(Compressed Sensing, CS)的信道估计可以达到减少导频的目的,但在频-时域信道矩阵到时延-多普勒域的稀疏变换中存在谱泄漏现象,影响了信道矩阵的稀疏性和估计的均方误差(MSE)性能。为此该文对信道的稀疏性进行研究,提出一种时域加窗的稀疏优化CS信道估计算法。通过对时域加窗,所提算法抑制了由离散截断导致的多普勒域泄漏,再据此设计出观测矩阵,以此方式增强信道在时延-多普勒域的稀疏性,并实现对稀疏的信道矩阵更为准确的重构,达到改善信道估计MSE性能的目的。仿真结果表明随信噪比的增大,加窗CS算法相比无窗CS算法有效改善了信道估计的性能。     

一种自适应稀疏度的混合场信道估计算法

针对6G超大规模多输入多输出(Extremely Large-scale Multiple-Input Multiple-Output,XL-MIMO)系统信道特性变化造成现有的近场和远场信道估计方案不能准确估计XL-MIMO混合场信道的问题,同时考虑到实际系统中稀疏度难以获取,提出了一种基于分段弱正交匹配追踪的混合场信道估计(Hybrid-field Stagewise Weak Orthogonal Matching Pursuit,HF-SWOMP)算法。该算法利用XL-MIMO混合场中近场和远场区域不同的信道特性,分别对近场和远场信道分量进行估计,从而得到混合场信道。仿真结果表明,所提XL-MIMO混合场信道估计算法性能相对于仅考虑近场和远场信道估计方案分别提高了约3.5 dB和3 dB,更符合实际信道场景。     

Sparse adaptive constant blind equalization algorithm for sparse multipath channel

In order to improve the convergence rate of the blind equalizer for sparse multipath channel,a novel blind equalization approach called l₀-norm constraint proportionate normalized least mean square constant algorithm was proposed for M-order phase-shift keying (MPSK) signal.Based on the constant modulus characteristics of MPSK signal and the sparse property of equalizer,a new blind equalization cost function with the l₀-norm penalty on the equalizer tap coefficients was firstly constructed.Then the update formula of the tap coefficients was derived according to the gradient descent algorithm.Moreover,the iteration step was updated by drawing upon the normalized proportionate factor.The algorithm not only assigned step sizes proportionate to the magnitude of the current individual tap weights,but also attracted the inactive taps to zero adaptively.Theoretical analysis and simulation results show that the proposed algorithm outperforms the existing blind equalization algorithms for sparse channel in reducing ISI and improving convergence rate.     

一种适用于多径衰落无线信道的快速盲均衡算法研究

在无线数字通信中,信道衰落和多途传播效应引起的码间干扰,严重影响了通信的有效性和可靠性,盲均衡是对抗码间干扰的有效方法。文章研究了一种适用于无线信道的快速盲均衡算法,并进行了计算机仿真。仿真结果表明,在算法剩余均方误差非常接近的情况下,该算法快于传统的常数模算法。     

基于分形的多径衰落信道估计

该文研究了多径衰落的分形性质,提出了一种利用分形维数和小波重构来改进最小均方误差方法的新型多径衰落信道估计算法。该算法改进了衰落信道参数估计的准确度,并消除了判决方法的错误传递性。仿真结果表明该算法能较准确地估计出多径衰落信道的参数,显著提高快衰落条件下接收机的误码性能。     

Nonlinear equalization of multipath fading channels withnoncoherent demodulation

A nonlinear decision-based adaptive equalizer compatible with differentially coherent phase shift keying (PSK) is proposed for frequency-selective fading channels. This equalization scheme is appropriate whenever conventional equalizers are not capable of tracking phase variations in selective fading channels. The received signal is first converted to a baseband signal and then sent through a differential detector. A nonlinear processor before the equalizer generates the needed nonlinear terms that are weighted and summed in the equalizer. Nonlinear intersymbol interference at the output of the differential detector is dealt with by minimizing an error signal between the output of the equalizer and the detected data. The adaptation algorithm can be any algorithm currently used for conventional equalizers. Our simulation results confirm that for channels with spectral nulls, equalization is achieved successfully with the proposed scheme, whereas, linear equalizers, either with coherent or noncoherent detection, fail     

基于小波变换变步长LMS自适应信道均衡的新方法

结合变换域最小均方(LMS)和变步长LMS算法的优势,提出了一种基于小波变换的变步长LMS自适应均衡方法。该方法中步长调整函数采用了改进的Sigmoid函数,该函数具有简单且误差信号接近零时变化缓慢的特点。并且,在训练模式、判决引导模式以及混合模式下,将提出方法和传统均衡方法进行了仿真比较。结果表明,所提出的方法比传统的线性LMS算法、变步长LMS以及小波变换LMS收敛更快、性能更优。     

Adaptive joint multiuser detection and channel estimation in multipath fading CDMA channels

The problem of joint multiuser detection and channel estimation in frequency-selective Rayleigh fading CDMA channels is considered. First the optimal multiuser detector for such channels is derived, which is seen to have a computational complexity exponential in the product of the number of users and the length of the transmitted data sequence. Two suboptimal detectors are then developed and analyzed, both of which employ decorrelating filters at the front-ends to eliminate the multiple-access interference and the multipath interference. The symbol-by-symbol detector uses a Kalman filter and decision feedback to track the fading channel for diversity combining. The per-survivor sequence detector is in the form of the Viterbi algorithm with the trellis updates being computed by a bank of Kalman filters in the per-survivor fashion. Both suboptimal detectors require the knowledge of all waveforms of all users in the channel and the channel fading model parameters. Adaptive versions of these suboptimal detectors that require only the knowledge of the waveform of the user of interest are then developed. The adaptive receivers employ recursive-least-squares (RLS) minimum-mean-square-error (MMSE) filters at the front-end to mitigate the interference, and use a bank of linear predictors to track the fading channels. It is shown that the front-end RLS-MMSE filters can be implemented using systolic arrays to exploit massively parallel signal processing computation, and to achieve energy efficiency. Finally, the performance of the suboptimal detectors and their adaptive versions are assessed by simulations. This revised version was published online in July 2006 with corrections to the Cover Date.     

Adaptive modulation using multipath fading compensation

An adaptive modulation/TDMA/TDD system using bi-directional multipath fading compensation is proposed. Computer simulation shows that the proposed system achieves higher quality and higher bit rate transmission than the conventional adaptive modulation/TDMA/TDD system using pilot symbol assisted fading compensation in a frequency selective fading environment     

Multistage multiuser detector for DS-CDMA multipath fading channel

The proposed multistage multiuser detector for DS-CDMA communication over a multipath fading channel consists of a bank of matched filters and a linear equaliser whose outputs are diversity combined to produce initial data estimates. Using this data, multiuser interference is removed from the matched filter bank output. Diversity combining is then applied again, which produces the final decision statistics. Simulation results indicate that this detector is near-far resistant