递归神经网络自适应均衡抗突发干扰研究

短波信道的突发干扰对判决反馈递归神经网络自适应均衡器有破坏作用并能导致均衡器失效,从而影响整个通信系统的连续性。本文对突发干扰时判决反馈递归神经网络自适应均衡器特性进行了分析,提出了2种改进算法。仿真结果证明了这2种改进算法的有效性。     

LMS算法和RLS算法在水声信道通信系统中应用的比较

为了减小水声通信系统中存在的由于多径传播效应引起的符号间干扰,可在系统中使用线性均衡器。首先介绍了LMS算法和RLS算法基本原理,利用Matlab仿真软件,给出了两种算法在水声信道通信系统中的自适应均衡的仿真系统,并对这两种算法对于均衡器的影响进行了比较,最后对比较的结果进行了分析。     

LMS算法和RLS算法在水声信道通信系统中应用的比较

为了减小水声通信系统中存在的由于多径传播效应引起的符号间干扰,可在系统中使用线性均衡器。首先介绍了LMS算法和RLS算法基本原理,利用Matlab仿真软件,给出了两种算法在水声信道通信系统中的自适应均衡的仿真系统,并对这两种算法对于均衡器的影响进行了比较,最后对比较的结果进行了分析。     

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。     

激光通信系统的波特间隔均衡器设计

当前应用的均衡器，主要采用单一的盲自适应算法实现信道均衡处理，容易出现误差扩散的现象，导致均衡器误码率较高。因此，针对激光通信系统，设计一种新的波特间隔均衡器。根据激光通信系统的接收端接收信号模型、干扰模型，定义激光通信系统信道模型。基于信道均衡要求，设计由前滤波器、反馈滤波器两个主要部分组成的多阶滤波器，作为波特间隔均衡器的基础结构。通过设置MSE切换门限联动LMS算法和CMA算法，形成自适应混合均衡算法，确保均衡器具有优越的信道均衡处理性能。最后，在FPGA上实现波特间隔均衡器。实验结果显示：应用所设计均衡器后，激光通信系统的最小误码率降低至10^-4,达到了提升激光通信质量的目的。     

几种LMS算法在水声信道通信系统中应用的比较

为了减小水声通信系统中存在的由于多径传播效应引起的符号间干扰,在系统中使用了线性均衡器.本文首先介绍了几种LMS算法基本原理,利用Matlab仿真软件,给出了这几种算法在水声信道通信系统中的自适应均衡的仿真系统,并由这些算法对于均衡器的影响进行了比较,最后又对比较的结果进行了分析.     

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.     

联合OFDM技术的常数模盲均衡仿真研究

针对传统盲均衡技术理论上消除码间干扰需要无限长均衡器抽头系数的缺陷,丈中采用OFDM技术与盲均衡技术进行结合,提出了一种联合OFDM技术的常数模盲均衡算法。利用OFDM抗多径衰落性能,再利用有限长度均衡器对信号进行均衡接收,有效地提高了通信质量。计算机仿真证明了这一方法的有效性。     

一种混合型盲均衡算法

盲均衡器在通信系统中有着重要的作用，但一般的盲均衡器存在收敛速度慢的缺点，本文以广泛使用的CMA（ConstantModulusAlgorithm）为基础，提出一种混合型均衡算法，不仅提高了收敛速度，而且减小了收敛后的剩余干扰，使均衡器收敛后不必切换到普通均衡方式。     

用于克服MIMO信道时变性的去相关自举均衡器

本文提出了一种用于克服MIMO信道时变性的自举均衡器.本文首先提出了用于MIMO通信系统的去相关均衡算法,该算法利用通信信源的统计特性实现不同源信号之间的去相关,从而克服了MIMO系统的同信道干扰.接着本文将去相关均衡算法用于时变的MIMO系统,提出了用于克服MIMO信道时变性的自举均衡器.该均衡器仅利用其输入信号来对时变的MIMO系统进行均衡,在仅增加很小的运算量的条件下,大大克服了因信道时变而在常规均衡器输出端产生的同信道干扰,提高了系统的误码性能.仿真实验证实,本文提出的去相关MIMO自举均衡器克服了信道时变的影响,明显改善了接收机的误码性能.     

基于Kalman滤波的水声混合双向迭代信道均衡算法

水声信道均衡中基于信道估计的均衡方法理论上具有更优的均衡性能,但较高的计算复杂度限制了算法的实际应用。针对这一问题,该文首先基于Kalman滤波和Turbo均衡提出一种迭代Kalman均衡器,实现了基于软符号的迭代信道估计与迭代Kalman均衡,且复杂度较常规方法降低约1个数量级。其次,针对单一均衡算法和单一方向Turbo均衡器存在的误差传递现象,设计了基于迭代Kalman均衡器与改进成比例归一化LMS (IPNLMS)自适应均衡器相结合的混合双向Turbo均衡器,提高了自适应均衡器的收敛速度和均衡性能,并通过双向均衡结构带来的增益改善了符号估计误差传递的现象。理论分析与仿真实验验证了该文算法的有效性。     

一种新颖的用于Turbo均衡的均衡器

针对符号间干扰信道，从接收信号序列服从联合高斯分布的假设出发，使用增扩的实矩阵表达推导出了一种新颖的均衡器-联合高斯均衡器，并给出了低复杂度的计算方法。使用这种低复杂度均衡器和新反馈策略的Turbo均衡系统与传统的基于最小均方误差均衡器的Turto均衡系统相比不仅性能上有显著提高，而且复杂度大大降低。     

Blind constant modulus equalization via convex optimization

In this paper, we formulate the problem of blind equalization of constant modulus (CM) signals as a convex optimization problem. The convex formulation is obtained by performing an algebraic transformation on the direct formulation of the CM equalization problem. Using this transformation, the original nonconvex CM equalization formulation is turned into a convex semidefinite program (SDP) that can be efficiently solved using interior point methods. Our SDP formulation is applicable to baud spaced equalization as well as fractionally spaced equalization. Performance analysis shows that the expected distance between the equalizer obtained by the SDP approach and the optimal equalizer in the noise-free case converges to zero exponentially as the signal-to-noise ratio (SNR) increases. In addition, simulations suggest that our method performs better than standard methods while requiring significantly fewer data samples.     

Computationally efficient methods for blind decision feedback equalization of QAM signals

This paper investigates computationally efficient methods for blind decision feedback equalization (DFE) that reduce the complexity and power requirements of blind equalization algorithms while maintaining their steady-state characteristics for quadrature amplitude modulation (QAM) signals. These include the power-of-two error (POT), selective coefficient update (SCU), and frequency-domain block (FDB) methods. A novel radius-directed stop-and-go (RSG) method is introduced, which selectively adjusts the equalizer tap coefficients based on the equalizer output radius. In addition, a new activation/de-activation method based on the equalizer output radius is utilized to control the feedback equalizer (FBE) of the DFEs. Simulation studies and analysis are provided for empirically derived cable and microwave channels and Ricean fading channels.     

无人机数据链信道线性Turbo均衡研究

Turbo均衡是一种基于Turbo迭代解码原理的均衡技术,利用的是均衡器与解码器之间信息的迭代使用来达到消除码间干扰的目的。Turbo均衡技术中通常采用基于最大后验概率的最大后验概率(MAP)均衡器,虽然性能较好,但计算量较大,系统延时较长。为降低延时,保证均衡性能,针对无人机遥控遥测数据链信道,设计了一种相对于MAP均衡器计算量较少的线性最小均方误差(MMSE)均衡器,通过仿真验证了这种线性Turbo均衡的性能,分析了其应用的可行性。     

TURBO EQUALIZATION WITH JOINTLY GAUSSIAN EQUALIZER

A Jointly Gaussian (JG) equalizer is derived for turbo equalization based on an augmented real matrix representation of channel model and a Gaussian approximation of the received symbol sequence. Using matrix inversion lemma and Cholesky decomposition, a lowcomplexity implementation of JG equalizer is also presented. The simulation results and complexity comparison confirm that turbo equalization with JG equalizer has a better performance and a lower complexity than the existing turbo equalization with linear minimum mean squared error equalizer.     

数字通信系统中均衡器研究综述

介绍了均衡技术的基本原理、均衡器的发展现状、盲均衡器算法的分类、均衡器算法的评价标准等,并对均衡技术的研究前景进行了展望。     

Iterative MAP Equalization and Decoding in Wireless Mobile Coded OFDM

Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (ICI). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Realizing that ICI channels are intrinsically ISI channels, this paper proposes a soft-in soft-out (SISO) maximum a posteriori (MAP) equalizer by extending Ungerboeck's maximum likelihood sequence estimator (MLSE) formulation to ICI channels. The SISO MAP equalizer employs BCJR algorithm and computes the bit log-likelihood ratios (LLR) for the entire received sequence by efficiently constructing a trellis that takes into account of the ICI channel structure. A reduced state (RS) formulation of the SISO MAP equalizer which provides good performance/complexity tradeoff is also described. Utilizing the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. This paper further proposes two computational efficient linear minimum mean square error (LMMSE) based equalization methods: recursive q-tap SIC-LMMSE equalizer and recursive Sliding-Window (SW) SIC-LMMSE equalizer respectively. Simulations results demonstrate that the iterative SISO RS-MAP equalizer achieves the performance of no ICI with normalized Doppler frequency f_dT_s up to 20.46% in realistic mobile WiMAX environment.     

Time-varying FIR equalization for doubly selective channels

We propose a time-varying (TV) finite impulse response (FIR) equalizer for doubly selective (time- and frequency-selective) channels. We use a basis expansion model (BEM) to approximate the doubly selective channel and to design the TV FIR equalizer. This allows us to turn a complicated equalization problem into an equivalent simpler equalization problem, containing only the BEM coefficients of both the doubly selective channel and the TV FIR equalizer. The minimum mean-square error (MMSE) as well as the zero-forcing (ZF) solutions are considered. Comparisons with the block linear equalizer (BLE) are made. The TV FIR equalization we propose here unifies and extends many previously proposed serial equalization approaches. In contrast to the BLE, the proposed TV FIR equalizer allows a flexible tradeoff between complexity and performance. Moreover, through computer simulations, we show that the performance of the proposed MMSE TV FIR equalizer comes close to the performance of the ZF and MMSE BLE, at a point where the design as well as the implementation complexity are much lower.