l0-范数约束的稀疏多径信道分数间隔双模式盲均衡算法

针对深衰落稀疏多径信道下多进制相移键控（Multiple Phase Shift Keying,MPSK）信号的盲均衡问题,提出了一种l₀-范数约束的分数间隔稀疏自适应双模式盲均衡算法.该算法借鉴传统的分数间隔双模式盲均衡算法思想,结合稀疏自适应滤波理论,首先利用l₀-范数对均衡器抽头系数进行稀疏性约束,构造出一种l₀-范数约束的分数间隔双模式最小均方误差代价函数,然后依据梯度下降法推导出盲均衡器抽头系数更新公式,并对迭代步长进行归一化和比例系数化.理论分析和仿真实验表明,与基于门限稀疏化的盲均衡算法、基于分数阶范数的盲均衡算法及分数间隔双模式盲均衡算法相比,本文所提算法在保证较快收敛速度的前提下,能有效降低剩余符号间干扰.本文设计的盲均衡算法为水声通信系统中接收方恢复出发送信号,提供了一种快速有效的方法.     

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。     

多径衰落信道MPSK信号超指数迭代盲解调算法

为了提高多径衰落信道下的盲解调性能,提出了一种结构简单的MPSK信号盲解调算法。首先利用超指数迭代分数间隔盲均衡器实现联合定时同步与均衡,然后对均衡器输出信号进行非线性变换实现载波频偏的估计,最后利用二阶数字判决锁相环跟踪相位变化纠正剩余频偏和相偏。仿真结果表明,在多径衰落信道条件下,与现有算法相比,基于超指数迭代分数间隔盲均衡器的盲解调算法实现简单,误码率低,而且具有收敛速度快、性能稳定等优点。     

一种T/4分数间隔预测判决反馈盲均衡算法

为了消除由深衰落信道引起的严重码间干扰,本文给出一种基于改进双模式多模算法的 T/4 分数间隔预测判决反馈均衡器.该均衡器采用改进的双模式多模算法独立优化前向、反馈滤波器,前向滤波器采用 T/4 分数间隔,反馈滤波器采用预测结构,仍为符号速率.在两种深衰落信道条件下仿真实验表明,本文给出的均衡器能够避免传统判决反馈均衡器的误收敛情况;同时其稳态均方误差小于基于常模算法的 T/4 分数间隔均衡器、基于常模算法的 T/4 分数间隔判决反馈均衡器,以及基于双模式多模算法的 T/4 分数间隔预测判决反馈均衡器,更适合处理 QAM 信号.     

稀疏多径信道的T/2间隔CFE均衡器研究

完全反馈均衡器(Complete Feedback Equalizer, CFE)是判决反馈均衡器(DFE)的改进。该文提出了一种T/2分数间隔稀疏CFE(T/2 Sparse CFE, T/2-SCFE)结构,以避免接收机对于符号定时误差的敏感性,并有效利用长时延扩展多径信道的稀疏性来降低均衡器的复杂度。理论分析与基于实测信道的计算机仿真表明, T/2-SCFE均衡器对符号定时误差保持了稳健性,总体性能优于符号间隔CFE及分数间隔DFE。     

稀疏水声信道判决反馈盲均衡算法研究

针对高速水声通信中信道的稀疏特性,提出了一种基于常数模准则的稀疏水声信道判决反馈盲均衡算法。该算法将改进的常数模算法与一种变化的判决反馈均衡器结构(部分反馈均衡器)有机结合,利用水声信道的稀疏特性,不但很好地实现了稀疏水声信道的盲均衡,而且简化了计算,易于算法的硬件实现。用典型稀疏水声信道进行了计算机仿真。结果表明,该算法性能稳定,计算量小,稳态均方误差低,整体性能与基于自适应LMS的稀疏迭代算法接近。该研究为高速水声通信中稀疏信道的均衡提供了一种可实现的方法。     

基于FPGA的分数间隔预测判决反馈均衡器的设计与实现

针对高阶QAM信号,本文设计实现了一种基于FPGA的分数间隔预测判决反馈均衡器.前向滤波器采用分数间隔结构,反馈部分采用预测结构,仍保持符号速率.该均衡器充分结合了分数间隔均衡器与预测判决反馈均衡器的优势,能够消除由深衰落信道引起的严重码间干扰.同时,该均衡器采用简化后的双模式多模算法独立优化前向、反馈滤波器,简化算法...     

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。     

DVB-C接收机中均衡的一种实现方法

针对DVB-C信号的特点,接收机中自适应均衡器采用的是分数间隔判决反馈均衡器的结构,与改进的CMA盲均衡算法和自适应算法DDLMS相结合.在仿真中,在有线多径信道条件下,此均衡器能较好地消除多径干扰,具有较好的性能,而不需要任何的训练序列和导频的存在.     

分布式多入多出正交频分复用快衰落感知估计

针对分布式多输入多输出正交频分复用(MIMO-OFDM)快衰落系统,为了消除快衰落信道的干扰,提出一种分布式MIMO-OFDM系统快衰落信道估计方法.该方法利用分布式快衰落信道间的感知信息在空间、时延和多普勒频移上具有的互相关性,求取三维互相关联合稀疏信道模型.推导预相关随机导频测量矩阵,结合分布式压缩感知算法,以能量有效的方式,对快衰落稀疏信道参数进行联合压缩测量和重构,得到各分布式MIMO接收端任意的稀疏信道系数.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,可以明显提高系统频谱效率和误码率,减少计算复杂度.     

Doubly Iterative Equalization of Continuous-Phase Modulation

In this paper, a doubly iterative receiver is proposed for joint turbo equalization, demodulation, and decoding of coded binary continuous-phase modulation (CPM) in multipath fading channels. The proposed receiver consists of three soft-input soft-output (SISO) blocks: a front-end soft-information-aided minimum mean square error (MMSE) equalizer followed by a CPM demodulator and a back-end channel decoder. The MMSE equalizer, combined with an a priori soft-interference canceler (SIC) and an a posteriori probability mapper, forms a SISO processor suitable for iterative processing that considers discrete-time CPM symbols which belong to a finite alphabet. The SISO CPM demodulator and the SISO channel decoder are both implemented by the a posteriori probability algorithm. The proposed doubly iterative receiver has a central demodulator coupled with both the front-end equalizer and the back-end channel decoder. A few back-end demodulation/decoding iterations are performed for each equalization iteration so as to improve the a priori information for the equalizer. As presented in the extrinsic information transfer (EXIT) chart analysis and simulation results for different multipath fading channels, this provides not only faster convergence to low bit error rates, but also lower computational complexity.     

Double turbo equalization of continuous phase modulation with frequency domain processing

In this paper, a doubly-iterative linear receiver, equipped with a soft-information aided frequency domain minimum mean-squared error (MMSE) equalizer, is proposed for the combined equalization and decoding of coded continuous phase modulation (CPM) signals over long multipath fading channels. In the proposed receiver architecture, the front-end frequency domain equalizer (FDE) is followed by the soft-input, softoutput (SISO) CPM demodulator and channel decoder modules. The receiver employs double turbo processing by performing back-end demodulation/decoding iterations per each equalization iteration to improve the a priori information for the front-end FDE. As presented by the computational complexity analysis and simulations, this process provides not only a significant reduction in the overall computational complexity, but also a performance improvement over the previously proposed iterative and noniterative MMSE receivers.     

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.     

应用粒子滤波器实现混沌通信系统的盲信道均衡

粒子滤波器(Particle filter,PF)是一种结合重要性权重抽样的序贯蒙特卡罗方法,能够应用到任意状态空间模型,并且能较好地估计经过非线性变化后的随机变量的统计特性.本文应用粒子滤波器和信号建模技术研究混沌通信系统的盲信道均衡问题,发展基于混沌的通信系统的盲均衡技术.仿真结果证实了,当Logistic映射作为混沌发生器和通信场景为固定参数与时变衰落信道时,该盲信道均衡器与基于扩展卡尔曼滤波算法的盲均衡器和基于无先导变换的自适应盲均衡器相比,有较好的均衡实现.此外,利用本文的盲均衡算法,实现了一种混沌调制通信系统的解调.     

A new combination of adaptive channel estimation methods and TORC equalizer in MC‐CDMA systems

Adaptive systems identification has been widely studied, but most studies have focused on the convergence of these methods. Applications of equalization systems have also received much attention. This paper presents a new combination of adaptive Broadband Radio Access Networks (BRAN) channel identification algorithms for multicarrier code division multiple access (MC‐CDMA) systems downlink equalization. In fifth‐generation (5G) wireless communications, MC‐CDMA is expected to support the associated networks. The BRAN E channel parameters, representing an outdoor scenario normalized for MC‐CDMA systems, are identified using a recursive least mean pth power algorithm with logarithmic transformation (RlogLMP). For validity and test aim, this algorithm is compared with the existing recursive least square (RLS) and least mean square (LMS) algorithms. Moreover, we use the estimated coefficients in the adaptive equalization problem. We give a review of the threshold orthogonality restoring combining (TORC) equalizer, which is coupled with the presented algorithms to counteract channel fading, as evaluated by the bit error rate (BER). Our performance results show that the RlogLMP algorithm can estimate the measured BRAN E channel with good efficiency for various values of the signal‐to‐noise ratio (SNR), as compared with the classical algorithms RLS and LMS. In adaptive equalization problems, the achieved results demonstrate that two thresholds ρ_TH in the TORC equalizer minimize the performance degradation, in terms of the BER, of the MC‐CDMA system under multipath channel fading with very good accuracy, especially if the coefficients are estimated with the specific case of the power p in the RlogLMP algorithm.     

l0-范数约束的稀疏多径信道RLS常模盲均衡算法

针对稀疏多径信道下MPSK信号的快速盲均衡问题,提出了一种l0-范数约束的递归最小二乘常模盲均衡算法.该算法借鉴传统的递归最小二乘常模盲均衡算法思想,结合稀疏自适应滤波理论,首先利用l0-范数对均衡器抽头系数进行稀疏性约束,构造出一种l0-范数约束的加权最小二乘误差代价函数,然后依据递归最小二乘算法推导出均衡器抽头系数更新公式.该算法发挥递归最小二乘常模算法收敛速度快的优势,并对幅度极小系数附加零点吸引调整,从而实现不同幅度抽头系数的快速收敛.理论分析与仿真结果表明,与现有算法相比,该算法在保证较低剩余符号间干扰的前提下,能有效提高均衡器的收敛速度.     

MLSE and soft-output equalization for trellis-coded continuousphase modulation

This paper presents two equalizer structures for trellis-coded continuous phase modulation (TC-CPM) on multipath fading intersymbol interference (ISI) channels. An equivalent discrete-time (DT) model is developed by combining the tapped-delay-line (TDL) model of the frequency-selective channel and by oversampling at the receiver. The (noninterleaved) fractionally spaced maximum-likelihood sequence estimation (MLSE) equalizer performs continuous phase modulation (CPM) demodulation, trellis-coded modulation (TCM) decoding, and channel equalization by exploiting the finite state nature of the ISI-corrupted TC-CPM signal. Both simulation and analytical results show diversity-like improvement when performing joint MLSE decoding and equalization. For the interleaved soft-output equalizer, the soft symbol metric is delivered to the TCM decoder by using a forward and backward recursion algorithm. Three variants of the soft-output equalizer are examined. We conclude that the backward recursion is essential to partial response CPM schemes, and with moderate complexity, the soft-output equalizer can have a substantial advantage over a noninterleaved MLSE equalizer