基于最低误码率准则及Volterra序列的几何特征均衡器

针对通信系统中带内噪声及干扰的滤波问题,提出一种基于最低误码率准则的非线性几何特征均衡器.考虑到噪声与干扰具有不同的统计特性,本文所建立的均衡模型把匹配滤波器输出映射到特征空间,使信号与干扰在特征空间形成不同的几何特征,再用Volterra序列予以分离,而分离是基于最低误码率准则.仿真表明:对于扩展的二元相移键控信号,在相对强的调频信号、调幅信号及噪声的联合干扰下,匹配滤波器和基于最小均方误差准则的线性均衡器均已失效,而几何特征均衡器仍能表现出良好的性能,并且基于奇次三阶Volterra序列的几何特征均衡器更具实用价值.     

基于混合遗传算法及最低误码率准则的几何特征均衡器

针对高效调制通信系统中带内干扰抑制问题,提出一种基于最低误码率准则的非线性几何特征均衡器,并用径向基函数神经网络来实现.为优化非线性均衡器的参数训练,本文构造了一种新的遗传随机梯度混合算法.仿真表明:对于扩展的二元相移键控信号,在相对强的窄带干扰下,匹配滤波器及线性均衡器已失效,而基于最低误码率准则的几何特征均衡器仍能表现出良好的性能,也大大优于基于最小均方误差准则的非线性均衡器.     

低计算复杂度的多级软判决均衡器用于干扰抑制

针对通信系统中非线性均衡器的计算复杂度问题,提出一种基于最低误码率准则的多级软判决均衡器.通过调节各级均衡器的拒绝门限,可使多级软判决均衡器在计算复杂度与误码率之间取得折衷.仿真表明:对于扩展的二元相移键控信号,在相对强的调频信号和调幅信号的联合干扰下,匹配滤波器和基于最小均方误差准则的线性均衡器已失效,而基于最低误码率准则的多级软判决均衡器仍能表现出良好的性能,并且大大减少计算复杂度.此外,还发现一个有趣的结果,即多个不同的非线性均衡器的协作可获得比单个均衡器更优的性能.     

复值的MBER非线性均衡器用于QAM信号

本文提出一种复值的最低误码率非线性滤波器用于非线性信道中QAM信号的均衡.推导了针对QAM信号的最低误码率准则训练算法的目标函数,并用Voherra序列来实现复值的非线性均衡器.为使非线性均衡器能在线自适应训练并增加训练算法的数值稳定性,提出～种滑窗随机梯度算法.大量仿真表明,对于非线性信道中QAM信号的均衡,最低误码率非线性均衡器的性能优于最小均方误差准则.     

最小均方误差均衡器的Matlab仿真设计

随着集成电路与计算机技术的发展,数字通信以其特有的优越性已得到广泛应用。就数字通信而言,误码率和频谱效率是两个主要的系统衡量指标。由于常用信道传输特性不是理想的,数字信号经过传输后会产生严重的码闽干扰,这对于接收机的正确判决非常不利,从而增加了通信的误码率,因此码间干扰的消除对提高通信系统的传输质量有重要意义。介绍基于最小均方误差准则的线性均衡器原理,利用Matlab对最小均方误差均衡器进行仿真设计,并对其性能进行分析。结果表明,最小均方误差均衡器能够有效消除码间干扰,增强基带传输系统的传输特性,是一种有效的均衡接收技术。     

警用无线通信的信道自适应性能研究

当前对于无线信道自适应性能的研究,仅在时不变信道模型下通过分析算法来推导说明,缺乏有效的仿真研究和验证。文中针对警用无线通信特点,并广泛适用于无线通信研究,建立了一种离散时变码间干扰信道模型,通过在部分离散时间点的信道跳变来模拟信道的时变,在此信道模型下研究自适应均衡器基于最小均方误差准则的最小均方和递推最小均方算法,仿真证明：该研究设计的自适应均衡器具有良好的信道自适应性能。     

一种基于符号级均衡的CDMA接收机

在使用较短扩频码的CDMA系统中,多径干扰会破坏用户扩频码之间的正交性,Rake接收机性能会严重下降.本文提出了一种新的基于Rake的符号级均衡的CDMA接收机,通过分析推导出了基于最小均方误差准则的均衡系数.性能仿真结果表明这种接收机与传统的Rake接收机相比,比特误码率性能有很大的提高,可以有效抑制跨多个符号的多径干扰.     

一种新的基于脉冲超宽带系统的发送分集方案

本文针对UWB信道特点,提出了预瑞克(Pre-RAKE)与空时块码(STBC)结合的新的发送分集方案,采用了基于最小均方误差准则(MMSE)的Pre-RAKE参数估计算法.最后仿真结果表明,基于MMSE算法的发送分集方案对系统误码率性能有较大改善,尤其是多径衰落严重而且存在符号间干扰(ISI)和窄带干扰(NBI)的非视距(NLOS)信道性能改善明显.     

一种新的群时延自适应均衡算法

为了补偿无线信道群时延特性所带来的影响,基于盲均衡器结构提出了一种优化的自适应均衡算法.该算法是基于最小均方误差准则的变步长LMS算法,通过自适应调节判决反馈均衡器两组横向滤波器的抽头系数,实现对信道群时延的自适应补偿.通过对16-QAM信号的仿真结果表明,新算法能够对有效补偿信道群时延带来的影响,并且明显降低系统的误码率.     

均方误差短时反馈算法的残余频偏纠正及阈值选取的研究

介绍了一种在全数字接收机中基于最小均方误差的残余频偏矫正算法,目的是改善由于残余频偏累积引起的误码率的加剧,以及通过利用最小均方误差判定准则确定判决门限值的大小.此种算法通过均方误差准则探测分析有无残余频偏,再利用短时反馈算法进行残余频偏的矫正.重点介绍了残余频偏矫正的算法和判决门限值的选取.矫正后误码率明显下降,码元质量得到有效改善.     

Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems

In time division-synchronous code division multiple access systems, the channel estimation for multiple subscribers requires the computation of very complicated algorithms through short training sequences. This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. Multi-user joint data detectors based linear equalizers are used to suppress inter-symbol interference and mitigate intra-cell multiple access interference. The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors.     

Multipath combining scheme in single-carrier transmission systems

In this letter, we introduce and investigate the RAKE combining receiver which is widely used in the code-division multiple access (CDMA) systems to the non-spectrum-spreading single-carrier transmission system. The initial estimate of the transmitted data is obtained by linear single-carrier equalizers, and then all the multipath signals are constructed from this initial solution and channel impulse response. By interference cancellation (IC) technique, we can acquire every multipath component in the received signal after cancelling the sum of all the other multipath signals constructed. Finally, all the components are combined together using selection combining (SC), equal gain combining (EGC) or maximal ratio combining (MRC), so that temporal diversity gain from the combined output can be obtained. Simulation results show that bit error rate (BER) performance of the new combining receiver based on zero forcing (ZF) and minimum mean square error (MMSE) equalizers can achieve the SNR gain dramatically in the SUI-5 wireless communication link.     

Finite dictionary techniques for MSER equalization in RKHS

Adaptive channel equalization is a signal processing technique to mitigate inter-symbol interference in a time dispersive channel. For adaptive equalization, minimum mean square error (MMSE) criterion-based reproducing kernel Hilbert spaces (RKHS) approaches such as the kernel least mean squares (KLMS) algorithm and its variants have been suggested in the literature for nonlinear channels. Another optimality criterion, based on minimum bit/symbol error rate (MBER/MSER), is a better choice for adapting an equalizer as compared to MMSE criterion. A kernel-based minimum symbol error rate (KMSER) equalization algorithm combines minimum symbol error rate (MSER)-based approaches with RKHS techniques. However, most algorithms in RKHS such as KMSER/KLMS require infinite storage requirement and hence cannot be practically implemented. To curtail the infinite memory requirement, and make adaptive algorithm suitable for implementation with finite memory and processing power, we propose quantized KMSER (QKMSER) and fixed-budget quantized KMSER (FBQKMSER)-based equalizers in this paper. In this paper, we derive the dynamical equation for MSE evolution of the QKMSER and FBQKMSER and find their performance to be asymptotically close to the MSE behavior of the KMSER. Also, it is found via simulations that the tracking performance of FBQKMSER is better than all the compared algorithms in this paper which is particularly useful for non-stationary channels.     

基于JUMMSE准则的前向分数间隔判决反馈均衡器

研究了前向分数间隔判决反馈均衡器的原理与结构,并推导了基于联合无偏差MMSE(JUMMSE)准则设计的最优解。文中讨论了均衡器长度对误符号率(SER)性能的影响。仿真结果表明,在较高的信噪比、选择恰当的均衡器长度时,这种均衡器对于高频信道的均衡效果是显著的。     

最低误码率非线性均衡器的快速自适应学习算法

针对最低误码率非线性均衡器的参数在线自适应学习问题,本文提出基于拟牛顿方法的快速自适应学习算法。采用Parzen窗函数方法估计误码率,通过设定切换条件,使参数学习在滑窗随机梯度法与滑窗拟牛顿法之间切换。这既增加了新算法的数值稳定性,又可提高收敛速度。通过对拟牛顿方法进行修改,还使新算法既可以在线自适应学习,也可用于高维参数的快速学习。仿真采用最低误码率非线性均衡器对通信系统进行干扰抑制和信道均衡,结果表明了新算法的高效性。     

Adaptive Multiuser Decision Feedback Detector: A Novel Parallel Interference Canceller

Adaptive decision feedback detector based on the parallel interference cancellation approach (ADFD-PIC) is presented for code division multiple access transmission, which not only combats the intersymbol interference and multiple access interference but also suppresses other-cell interference. For frequency-selective smoothly time-varying channels, the proposed ADFD-PIC structure using the erasure algorithm based soft-slicer and channel estimator (EC-ADFD-PIC) offers performance improvement by mitigating the adverse effects of error propagation. The simulation results are presented to demonstrate the substantial improvement in bit error rate performance of the minimum mean square error EC-ADFD-PIC over other multiuser detection techniques.     

Adaptive minimum symbol-error-rate decision feedback equalization for multilevel pulse-amplitude modulation

The design of decision feedback equalizers (DFEs) is typically based on the minimum mean square error (MMSE) principle as this leads to effective adaptive implementation in the form of the least mean square algorithm. It is well-known, however, that in certain situations, the MMSE solution can be distinctly inferior to the optimal minimum symbol error rate (MSER) solution. We consider the MSER design for multilevel pulse-amplitude modulation. Block-data adaptive implementation of the theoretical MSER DFE solution is developed based on the Parzen window estimate of a probability density function. Furthermore, a sample-by-sample adaptive MSER algorithm, called the least symbol error rate (LSER), is derived for adaptive equalization applications. The proposed LSER algorithm has a complexity that increases linearly with the equalizer length. Computer simulation is employed to evaluate the proposed alternative MSER design for equalization application with multilevel signaling schemes.     

大规模MIMO系统中的一种自适应SIC检测算法

与传统系统相比,大规模多入多出（MIMO）系统能更加有效地提高频谱效率。利用传统的最小均方误差（MMSE）信号检测算法求解大规模MIMO系统,虽然检测结果接近最优,但是矩阵的求逆运算导致计算的复杂度非常高。提出了一种自适应排序干扰消除（SIC）检测算法,在逐次超松弛（SOR）迭代运算的基础上,通过干扰消除降低待检测矩阵的维度。通过仿真分析,得出所提算法的复杂度低于Jacobi、SOR检测算法,且在迭代次数较少的情况下,算法的误码率（BER）性能明显优于SOR检测算法。