改进的Summer算法及其在Turbo译码中的应用

由于Summer信噪比算法采用的信道模型为AWGN信道,他对衰落信道并不适用。通过在接收信号中增加了衰落因子,提出了一种能够应用于Nakagami衰落信道的改进Summer信噪比估计算法。仿真表明,运用改进的算法获得的信道信噪比信息非常接近实际的信噪比信息,同时,改进的Summer在线估计器使得Turbo译码性能得到明显的改善,而且不影响Turbo译码过程的总复杂度。     

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。     

一种改进的C.Loo信道模型衰落因子算法

为更好地反映实际无线信道的特性,介绍一种改进的C.Loo信道模型衰落因子算法。原始C.Loo信道模型衰落因子算法中不考虑多普勒频移的影响,本文加载了多普勒频移对衰落因子的影响,并说明其合理性、可行性及优点。     

两种定时同步算法的讨论与分析

介绍基于最大似然准则的定时同步算法,通过仿真发现该算法应用于AWGN信道效果很好,但是应用于平坦衰落信道效果相对较差。为了解决信号在平坦衰落信道传输过程中遇到的一系列问题,对基于循环平稳特性的定时同步算法进行了研究和改进。仿真结果表明该算法可以很好地适应于衰落信道。     

一种无线通信信道的设计与算法仿真

无线信道在实际中难以测试,但信道仿真可以解决这一问题。文中给出了一种灵活且适应性强的无线移动信道模型,并给出了该模型中的衰落信道模型及算法,运用该算法对衰落信道进行仿真,给出衰落信号的仿真结果以及输入信号经衰落信道处理后的结果。     

Nakagami衰落信道的信噪比估计及其在Turbo译码中的应用

在Turbo译码中，需要精确的信噪比信息来计算译码器生成的外信息，而在无线衰落信道中，Nakagami衰落信道具有通用性，文中对Summer信噪比估计算法进行了改进，使之能够应用于Nakagami衰落信道。最后，对应用了改进Summer信噪比约Turbo译码进行了性能仿真，从结果可以看出，改进的Summer信噪比估计算法能够成功应用到Turbo译码中，使得Turbo译码获得良好的性能。     

一种基于改进Lloyd-Max的信道估计算法

针对基于Lloyd-Max的平衰落信道估计算法估计精度低且无法适用于高阶QAM调制的问题,提出了基于改进Lloyd-Max的信道估计算法。该算法结合信源的具体调制样式,对Lloyd-Max算法的聚类过程施加星座图结构约束,从而避免了聚类后星座图结构畸形的问题,提高了信道参数估计精度。仿真试验表明,该算法相比于Lloyd-Max算法在较低信噪比下具有更高的信道参数估计精度,在调制阶数较高时,这种优势更加明显。     

基于最小二乘支持向量机的Jakes衰落信道预测

将LS-SVM用于Jakes衰落信道预测,进而提出了一种新的衰落信道预测算法.该算法利用衰落信道系数的既有观测值构建学习样本,然后借助LS-SVM的学习与判决能力实施非线性预测.对Jakes衰落信道的预测实验表明,文中预测算法可行且有效.另外,在实验中也讨论了嵌入维参数对预测准确度的影响,并给出最优嵌入维的选取方法.     

基于时变衰落信道分解的OFDM信号接收技术

OFDM信号在时变衰落信道中传输时存在载波间干扰(ICI),降低了系统的性能。基于衰落信道的多普勒分解,OFDM信号在时变衰落信道中的传输可以等效成信息数据直接通过无衰落的离散白噪声滤波器模型信道传输,改进的Viterbi算法可用于接收这类信号。该接收技术可以有效去除传统的OFDM系统中的载波间干扰,消除误码的地板效应,提高了系统性能。     

多径衰落信道下的超宽带信号同步算法仿真研究

超宽带无线通信因其潜在的性能优势,目前得到极大重视。但信号同步算法的硬件实现一直是困扰超宽带通信的难题。对传统的滑动同步算法进行了分析,并作了改进,在不增加硬件实现复杂度的同时,提高了同步性能。仿真结果证明,改进后的算法在多径衰落信道下具有较好的鲁棒性。     

A robust µopt‐LMS algorithm for the tracking of fading channels

This paper presents an application of LMS algorithm with optimum step size (µ_opt‐LMS) for fading channel estimation. The expression for optimum step size of the LMS algorithm is modified for use in the fading channel estimation problem. The robustness of the proposed µ_opt‐LMS algorithm is demonstrated via simulation in different channel conditions. Copyright © 2002 John Wiley & Sons, Ltd.     

Joint data and channel estimation for TDMA mobile channels

One of the main problems in time-division multiple-access (TDMA) digital mobile communications is the poor performance of the receiver for fast-fading channels. We propose to use a novel joint data and channel estimation (JDCE) technique to improve performance. The basic idea of this method originates from the so-called generalized likelihood ratio (GLR) test of classical detection theory. The technique was combined with the well-known Viterbi algorithm and applied to blind equalization by Seshadri [1]. In this paper, we introduce this technique to TDMA mobile communications. We find that the problems of delayed channel updating and divergence caused by error decision feedback in conventional maximum likelihood sequence estimation with decision delay (MLSE/DD) can be completely solved. An improvement of 4.5 dB can be obtained compared with the MLSE/DD method when it is applied to the Northern American Digital Cellular (NADC) system. The specified IS-54 requirement of 19 dB signal-to-noise ratio (SNR) at a bit error rate (BER) of 3% and a vehicle speed of 100 km/h can be met with a remarkable margin of 8 dB. When the intersymbol interference (ISI) of a channel is not severe, the required computation is moderate. For example, in the NADC system, the computational burden of the JDCE method is twice that of the MLSE/DD method if the least-mean-squares (LMS) algorithm is used for channel tracking.This work was presented in part in the Third International Symposium on Personal, Indoor and Mobile Radio Communications, Boston, MA, October 1992.     

一种用于实际OFDM系统的次优信道估计算法

基于对实际系统中信道冲激响应(CIR)泄漏问题的详细分析,提出了一种次优的时域信道估计算法。该算法克服了CIR泄漏的影响,因此能够很好地适应实际系统中的非整数采样多径衰落信道。该算法不需要预先知道信道统计特性,还具有低复杂度的特点。与已有信道估计算法进行了仿真比较,结果证明该算法极大地降低了信道估计MSE值,同时也不存在“地板效应”。     

Blind equalization of quadrature partial response‐trellis coded modulated signals in Rician fading

In this paper, a blind maximum‐likelihood channel estimation algorithm is developed for quadrature partial response‐trellis coded modulated (QPR‐TCM) signals propagating through a Rician fading environment. A hidden Markov model (HMM) formulation of the problem is introduced and the Baum–Welch parameter estimation algorithm is modified to provide a computationally efficient solution to the resulting optimization problem. Performance analysis of the proposed method is carried out through the evaluation of bit‐error probability upper bound for Rician fading channels. Also, some illustrative simulations are presented. Copyright © 2001 John Wiley & Sons, Ltd.     

OFDM系统的迭代联合信道估计与符号检测算法

提出了通过降低导频功率来提高OFDM传输效率,同时采用迭代的联合信道估计和符号检测算法来保证较好误码性能的接收方案。理论分析与仿真结果表明,当数据信息与导频信息的功率比不高于l0dB时,本文提出的算法能够有效地降低系统误码率,同时该方法还具有算法简单,收敛速度快的特点。     

Joint Data and Kalman Estimation for Rayleigh Fading Channels

Channel estimation is an essential part of many detection techniques proposed for data transmission over fading channels. For the frequency selective Rayleigh fading channel an autoregressive moving average representation is proposed based on the fading model parameters. The parameters of this representation are determined based on the fading channel characteristics, making it possible to employ the Kalman filter as the best estimator for the channel impulse response. For IS-136 formatted data transmission the Kalman filter is employed with the Viterbi algorithm in a Per-Survivor Processing (PSP) fashion and the ove rall bit error rate performance is shown to be superior to that of detection techniques using the RLS and LMS estimators. To allow more than one channel estimation per symbol interval, Per-Branch Processing (PBP) method is introduced as a general case of PSP and its effect on performance is evaluated. The sensitivity of performance to parameters such as fading model order and vehicle speed is also studied.     

一种基于数据辅助的OFDM系统符号同步算法

该文提出了一种改进的OFDM系统符号同步算法。在集相关法估计出FFT有效采样窗的基础上,加以数据的辅助,将恢复后的符号序列再次进行OFDM调制并与接收信号作相关,能够求出符号到达的准确时刻。这种基于数据辅助的方法提高了估计过程中的信噪比。仿真结果表明,该方法在多径衰落信道下能获得较好的定时同步性能。     

Channel estimation and long-range prediction of fast fading channels for adaptive OFDM system

This correspondence presents the channel estimation and long-range prediction technique for adaptive-orthogonal-frequency-division-multiplexing (AOFDM) system. The efficient channel loading is accomplished by feeding the accurately predicted channel-state-information (CSI) back to transmitter. The frequency-selective wireless fading channel is modelled as a tapped-delay-line-filter governed by a first-order autoregressive (AR1) process; and an adaptive channel estimator based on the generalised-variable-step-size least-mean-square (GVSS-LMS) algorithm tracks AR1 correlation coefficient. To compensate for the signal fading due to channel state variations, a modified-Kalman-filter (MKF)-based channel estimator is utilised. In addition, channel tracking is also performed for predicting future CSI at receiver, based on the numeric-variable-forgetting-factor recursive-least-squares (NVFF-RLS) algorithm. Subsequently, adaptive bit allocation for AOFDM system is employed by using predicted CSI at transmitter. Here, the proposed combination of GVSS-LMS and MKF algorithms for robust channel estimation and the NVFF-RLS algorithm for efficient channel prediction is incorporated. The performance validation of presented method is carried out by using different channel realisations through simulation, and also by comparing it with fixed step-size LMS, MKF and fixed forgetting-factor RLS algorithm based conventional techniques. Eventually, the reliable performance of underlying AOFDM system can be achieved in terms of the lower mean squared estimation/prediction errors and alleviated symbol error rate.