Sequential sequence estimation for trellis-coded modulation onmultipath fading ISI channels

A new receiver structure is proposed for trellis-coded modulation on multipath fading intersymbol interference (ISI) channels that permits the use of large-state trellis codes. The receiver uses a sequential sequence estimator with the Fano algorithm, and a channel estimator consisting of a fast nonrecursive start-up algorithm for training and the LMS algorithm for tracking. During the tracking mode, the channel estimates are updated dynamically by using recent tentative decisions produced by the sequential sequence estimator. This approach results in good tracking even on rapidly varying channels, and reduces the degradation in performance of the sequential sequence estimator due to channel estimation error. The effect of fading is mitigated using both implicit time diversity in the form of interleaved trellis-coded modulation and explicit antenna diversity     

一种新的无线通信随机相位线性均方估值方案

本文提出了一种新的无线通信随机相位线性均方估值方案，分析了其性能；针对瑞利度落信道进行了计算机模拟，并将模拟结果与理论值进行了比较。理论分析和模拟结果表明，该方法是一种有效的无线通信随机相位估值方法。     

A new adaptive equalizer with channel estimator for mobile radiocommunication

For unknown mobile radio channels with severe intersymbol interference (ISI), a maximum likelihood sequence estimator, such as a decision feedback equalizer (DFE) having both feedforward and feedback filters, needs to handle both precursors and postcursors. Consequently, such an equalizer is too complex to be practical. This paper presents a new reduced-state, soft decision feedback Viterbi equalizer (RSSDFVE) with a channel estimator and predictor. The RSSDFVE uses maximum likelihood sequence estimation (MLSE) to handle the precursors and truncates the overall postcursors with the soft decision of the MLSE to reduce the implementation complexity. A multiray fading channel model with a Doppler frequency shift is used in the simulation. For fast convergence, a channel estimator with fast start-up is proposed. The channel estimator obtains the sampled channel impulse response (CIR) from the training sequence and updates the RSSDFVE during the bursts in order to track changes of the fading channel. Simulation results show the RSSDFVE has nearly the same performance as the MLSE for time-invariant multipath fading channels and better performance than the DFE for time-variant multipath fading channels with less implementation complexity than the MLSE. The fast start-up (FS) channel estimator gives faster convergence than a Kalman channel estimator. The proposed RSSDFVE retains the MLSE structure to obtain good performance and only uses soft decisions to subtract the postcursor interference. It provides the best tradeoff between complexity and performance of any Viterbi equalizers     

Multiuser channel estimation and tracking for long-code CDMA systems

Channel estimation techniques for code-division multiple access (CDMA) systems need to combat multiple access interference (MAI) effectively. Most existing estimation techniques are designed for CDMA systems with short repetitive spreading codes. However, current and next-generation wireless systems use long spreading codes whose periods are much larger than the symbol duration. We derive the maximum-likelihood channel estimate for long-code CDMA systems over multipath channels using training sequences and approximate it using an iterative algorithm to reduce the computational complexity in each symbol duration. The iterative channel estimate is also shown to be asymptotically unbiased. The effectiveness of the iterative channel estimator is demonstrated in terms of squared error in estimation as well as the bit error rate performance of a multistage detector based on the channel estimates. The effect of error in decision feedback from the multistage detector (used in the absence of training sequences) is also shown to be negligible for reasonable feedback error rates using simulations. The proposed iterative channel estimation technique is also extended to track slowly varying multipath fading channels using decision feedback. Thus, an MAI-resistant multiuser channel estimation and tracking scheme with reasonable computational complexity is derived for long-code CDMA systems over multipath fading channels.     

A robust channel estimator for DS-CDMA systems under multipath fading channels

This paper addresses the problem of channel estimation for direct-sequence code-division multiple-access (DS-CDMA) systems with time-varying multipath fading channels. The multipath fading channels are modeled as autoregressive (AR) models. A method is first proposed to convert the time-varying regression model due to the time-varying nature of users' information symbols into a time-invariant one. Then, a polynomial approach is proposed to obtain the minimum mean square error (MMSE) estimator. The uncertainty of the channel model and decision errors of the DS-CDMA detector are taken into consideration in the design of the MMSE estimator. Compared with the Kalman estimator, the computational complexity of the proposed algorithm is much lower. The simulation results show that the proposed estimator provides a comparable estimation performance with the Kalman estimator and is robust for fast-fading channels.     

基于神经网络均衡器的小波包多载波扩频系统

在多径衰落信道下,本文提出了一种基于神经网络均衡器的小波包多载波扩频系统(Neural Network Equalizers Wavelet Packet Spread Spectrum,NNE-WPSS).本文利朋基于最小均方算法(Least Mean Square algorithm,LMS)的复径向基函数神经网络均衡器(Complex Radial Basis Function Network Equalizers,CRBF)来抑制由多径衰落信道引起的码间干扰(Inter-Symbol Interference,ISI)并且利用最大似然算法对解调后的码元进行检测.在多径衰落信道和白高斯噪声情况下,本文分析了基于神经网络均衡器的新型小波包多载波扩频系统的传输性能.仿真结果表明,本文所提出的基于神经网络均衡器的新型小波包多载波扩频系统的性能要优于传统的基于正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)多载波扩频系统;本文提出的复径向基函数神经网络均衡器(CRBF)的性能也优于迫零均衡器(Zero-Forcing Equalizer,ZFE).     

Joint estimation of carrier frequency offset and statistical parameters of the multipath fading channel

In this paper, we focus on the joint estimation of the carrier frequency offset and statistical parameters of the multipath mobile channel. By modeling the multipath fading channel with a complex bandpass autoregressive (AR) model, we show how the estimates for the frequency offset, Doppler spread, and power profile of the multipath channel can be extracted from the estimated complex AR coefficients obtained via the expectation-maximization algorithm. A main advantage of the proposed joint estimator is that while it has a capability of performing equally well in all scattering environments, it can provide accurate estimates even in high-mobility channel conditions. We also demonstrate how the complexity of the estimator can be significantly reduced, while only slightly trading off performance, by applying the mean field approximation technique. Moreover, we derive a fully adaptive joint synchronization and channel-estimation scheme, as well as a novel Kalman-smoother-based frequency-error detector that can be used in feedback frequency-recovery schemes and is particularly well suited for fast-fading channel conditions. Finally, we revisit the Cramer-Rao lower bound analysis, and show how the Fisher information matrix can be conveniently computed in the presence of a frequency-selective Rayleigh fading channel.     

MMSE multiuser detection for array multicarrier DS-CDMA in fading channels

Reception of asynchronous, multicarrier direct-sequence-code division multiple access (DS-CDMA) in time-varying, multipath radio channels with use of a receiving antenna array is investigated. Interference reducing minimum mean squared error (MMSE) receivers are discussed, and by considering the time-variation of the channel, a modified structure is derived which is efficient for channels experiencing small-scale fading. A blind implementation of this receiver is then proposed. Subspace concepts are applied to formulate a tracking, composite channel vector estimator which operates effectively in fading situations, even when high levels of interference are present. Both the modified MMSE weight matrix and diversity combining weights are generated from these channel estimates. Simulations of the proposed receiver show it to have superior performance over a standard MMSE receiver which is periodically re-evaluated to permit it to follow the channel variations due to small-scale fading. Furthermore, a hybrid MMSE receiver is proposed which applies different processing methods depending on each transmitters mobility, resulting in improved performance.     

基于卡尔曼滤波的盲空时检测器

文章提出了一种基于卡尔曼滤波的盲空时多用户检测方法。卡尔曼滤波是一种线性最小方差状态估计,把它有效地结合阵列天线与多用户检测。该自适应多用户检测方法不需要发送训练序列。在多径衰落信道下,仿真结果表明该方法收敛速度比LMS算法更快,有较强的抗多径和多址干扰能力。     

Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507–521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523–1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.     

Channel estimation for OFDM transmission in multipath fadingchannels based on parametric channel modeling

We present an improved channel estimation algorithm for orthogonal frequency-division multiplexing mobile communication systems using pilot subcarriers. This algorithm is based on a parametric channel model where the channel frequency response is estimated using an L-path channel model. In the algorithm, we employ the ESPRIT (estimation of signal parameters by rotational invariance techniques) method to do the initial multipath time delays acquisition and propose an interpath interference cancellation delay locked loop to track the channel multipath time delays. With the multipath time delays information, a minimum mean square error estimator is derived to estimate the channel frequency response. It is demonstrated that the use of the parametric channel model can effectively reduce the signal subspace dimension of the channel correlation matrix for the sparse multipath fading channels and, consequently, improve the channel estimation performance     

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.     

莱斯多径衰落信道下OFDM系统的容量方差分析

方差是系统容量的一个重要参数,可以用来估计通信系统的中断容量。该文研究了正交频分复用（OFDM）系统在莱斯衰落信道下的容量方差。首先该文建立了多径莱斯信道的模型并且定义了多径莱斯信道的莱斯因子,基于此信道模型推出了一个OFDM系统容量方差新的数学表达式,此表达式以OFDM系统的子载波数、信噪比、信道的多径时延等为参数。基于此表达式,计算机仿真和数值计算研究了信噪比、多径数目、莱斯因子对OFDM系统容量方差的影响。结果表明:计算机仿真和数值计算基本吻合,验证了所推导数学表达式的正确性;系统容量方差与信噪比成正比,与莱斯因子和信道的多径数目成反比。另外,该文以积分的形式给出了任意两个相关莱斯随机变量的联合概率密度函数。      

Two EM-type channel estimation algorithms for OFDM with transmitter diversity

We study channel estimation for orthogonal frequency-division multiplexing (OFDM) systems utilizing transmitter diversity and operating over multipath fading channels. Two expectation-maximization (EM)-type algorithms are introduced and compared with each other in terms of convergence rate. At each iteration and for every OFDM link, the EM-type algorithms partition the problem of estimating a multi-input channel into independent channel estimations for each transmit-receive antenna pair, therefore avoiding the matrix inversion encountered in the joint least-square estimation. The EM-type algorithms can also be used to efficiently implement a recently proposed algorithm, termed the significant-tap-catching estimator, so that the system performance is more robust to different multipath channel delay profiles.     

Constrained MMSE receivers for CDMA systems in frequency-selective fading channels

A constrained minimum mean square error (CMMSE)-RAKE receiver for multipath fading channels is developed by extending the CMMSE receiver for flat fading channels. Based on the observation that interpath interference causes a bias of the channel estimator in , a receiver that can remove such a bias is proposed, plus a closed-form expression of the bit-error rate of the receiver is derived. Computer simulation is used to demonstrate that the proposed receiver can outperform existing RAKE receivers.     

Receiver structures for time-varying frequency-selective fadingchannels

Several receiver structures for linearly modulated signals are proposed for time-varying frequency-selective channels. Their channel estimators explicitly model the time variation of the channel taps via polynomials. These structures are constructed from the following building blocks: (i) sliding or fixed block channel estimators; (ii) maximum likelihood sequence detectors (MLSDs) or decision feedback equalizers (DFEs); and (iii) single or multiple passes. A sliding window channel estimator uses a window of received samples to estimate the channel taps within or at the end of the window. Every symbol period, the window of samples is slid along another symbol period, and a new estimate is calculated. A fixed block channel estimator uses all received samples to estimate the channel taps throughout the packet, all at once. A single pass receiver estimates the channel and detects data once only. A multipass receiver performs channel estimation and data detection repetitively. The effect of the training symbol positions on the performance of the block multipass approach is studied. The bit error rate (BER) performance of the MLSD structures is characterized through simulation and analysis. The proposed receivers offer a range of performance/complexity tradeoffs, but all are well suited to time-varying channels. In fast fading channels, as the signal-to-noise ratio (SNR) increases, they begin to significantly outperform the per-survivor processing-based MLSD receivers which employ the least mean-squares (LMS) algorithm for channel estimation     

EM-based blind LDPC identification in multipath channels

As the advent of cognitive radios,blind encoder identification has attracted increasingly attentions since it plays an important role.The existing works mainly focus on additive white Gaussian noise (AWGN) channel,while the blind identification in multipath scenarios has not been sufficiently investigated.Considering the blind low density parity-check (LDPC) codes identification in the presence of unknown multipath fading channel,a likelihood-based classifier was proposed using the expectation maximization (EM) algorithm to obtain the maximum likelihood estimates of the unknown parameters.Then,an average log-likelihood ratio (LLR) estimator was adopted to classify the unknown encoder.Numerical results show that the proposed algorithm provides promising identification performance in multipath channels,especially in the low signal-to-noise ratio region.     

一种频选衰落信道下的Turbo多用户检测算法

联合MAP多用户检测与信道解码的迭代多用户检测(MUD)技术可显著提高宽带移动CDMA系统的容量和性能.在多径时变衰落的编码信道下,提出一种迭代实现干扰抑制、符号估计、信道解码的Turbo多用户检测算法.在每次迭代中,MUD自适应地实现干扰抑制并输出符号估计的软信息,软输入软输出的信道解码器使用LOG MAP方法实现信道解码并反馈符号估计的软信息作为下一次TurboMUD迭代的先验信息.仿真结果证实了该算法在频选衰落信道下经两次迭代就能逼近单用户编码CDMA系统的接收性能.     

Joint estimation of PN code delay and multipath using the extendedKalman filter

The problem of delay estimation in the presence of multipath is considered. It is shown that the extended Kalman filter (EKF) can be used to obtain joint estimates of time-of-arrival and multipath coefficients for deterministic signals when the channel can be modeled as a tapped-delay line. Simulation results are presented for the EKF joint estimator used for synchronization in a direct-sequence spread-spectrum system operating over a frequency-selective fading channel. A simplified model of the EKF joint estimator is considered for analysis purposes. The evolution in time of the tracking error probability density function and the nonlinear tracking error variance are examined through numerical solution of the Chapman-Kolmogorov equation. The nonlinear tracking error variance is compared to both the linear error variance estimate directly provided by the EKF and the Cramer-Rao lower bound