Adaptive combined DFE/MLSE techniques for ISI channels

By embedding a decision-feedback equalizer (DFE) into the structure of a maximum-likelihood sequence estimator (MLSE), an adaptive combined DFE/MLSE scheme is proposed. In this combined DFE/MLSE, the embedded DFE has three functions: (i) prefiltering the received signals and truncating the equivalent channel response into the desired one, (ii) compensating for channel distortions, and (iii) providing the MLSE detector with predicted values of input signals. Since the embedded MLSE detector operates on the predicted signals the detected symbols at the output of the DFE/MLSE do not suffer any delay and can be directly fed back into the embedded DFE so that the error propagation, which usually takes place in a conventional DFE, can be greatly reduced. Analytical and simulation results indicate that the performance is significantly improved by the DFE/MLSE compared to the conventional DFE while its computation complexity is much less than that of the conventional MLSE receiver. The combined DFE/MLSE can use different adaptive structures (block-updating, sliding window updating or symbol-by-symbol updating) to meet different performance objectives. Moreover, the proposed DFE/MLSE provides a trade-off between performance and complexity with a parameter m representing the MLSE detection depth as well as the number of predicting steps of the embedded DFE. For some particular values of m, this scheme is capable of emulating the conventional DFE, MLSE-VA, adaptive LE-MLSE equalizer, adaptive DDFSE, and adaptive BDFE without detection delay     

A Maximum-Likelihood Sequence Estimator with Decision-Feedback Equalization

A decision-feedback equalizer (DFE) is proposed as a prefilter which limits the complexity of a maximum-likelihood sequence estimator (MLSE) implemented by the Viterbi algorithm (VA) for channels having a long impulse response. By imbedding a DFE into the structure of the MLSE, the overall impulse response of the system is truncated to a short duration. With this practical receiver, a compromise may be made between performance and complexity by properly choosing the duration of a desired impulse response. A technique is also developed to estimate the performance of the receiver numerically, taking into account the effect of incorrect decision feedback on the VA. Analysis and computer simulation over a single-pole channel show that the proposed scheme can reduce the complexity of the MLSE while retaining much of its performance advantages.     

Cluster-based blind nonlinear-channel estimation

A cluster-based maximum-likelihood sequence estimator (MLSE) for nonlinear channels was described, which consists of a clustering network and an MLSE implemented by the Viterbi algorithm. The cluster-based MLSE can be used for digital communication through nonlinear finite-length channels because channel mapping estimation is used instead of channel estimation in the conventional MLSE. The clustering network of the cluster-based MLSE, which estimates the channel mapping between the signal input vectors and the noiseless channel outputs, is a supervised network and requires a training sequence. We propose a blind channel mapping estimator to estimate the channel mapping without using the training sequence. The blind channel mapping estimator has a clustering block and a mapping block. The clustering block estimates the channel outputs, which represent the channel mapping, subject to an unknown permutation operation because no training sequence is utilized. That permutation operation is resolved by the mapping block, and therefore, the channel mapping is obtained. Introducing the blind channel mapping estimator into the cluster-based MLSE, a blind cluster-based MLSE for nonlinear channels can be done. Computer simulations of the blind channel mapping estimator and the blind MLSE for nonlinear channels are presented     

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     

Mean-square crosstalk approach to CPM

The maximum-likelihood sequence estimator (MLSE) for continuous phase modulation (CPM) signals in an additive white Gaussian noise (AWGN) channel is a very efficient method of detection. This paper describes an extension of a relatively simple crosstalk approach for the performance analysis of linear quadrature receivers with cochannel interference (CCI) and adjacent channel interference (ACI) present to the MLSE receiver. Many CPM signals are analyzed, including those using new baseband modulating pulses. One of the new schemes allows an ACI signal to be 62 dB greater than the desired user signal at a frequency separation of one-and-a-half times the bit rate, with just a 2-dB degradation in required E_b/N₀     

MLSE and MAP Equalization for Transmission Over Doubly Selective Channels

In this paper, equalization for transmission over doubly selective channels is discussed. The symbol-by-symbol maximum a posteriori probability (MAP) equalizer and the maximum-likelihood sequence estimation (MLSE) are discussed. The doubly selective channel is modeled using the basis expansion model (BEM). Using the BEM allows for an easy and low-complexity mechanism for constructing the channel trellis to implement the MLSE and the MAP equalizer. The MLSE and the MAP equalizer are implemented for single-carrier transmission and for multicarrier transmission implemented using orthogonal frequency-division multiplexing (OFDM). In this scenario, a complexity-diversity tradeoff can be observed. In addition, we propose a joint estimation and equalization technique for doubly selective channels. In this joint estimation and equalization technique, the channel state information (CSI) is obtained in an iterative manner. Simulation results show that the performance of the joint channel estimation and equalization approaches the performance when perfect CSI is available at the receiver.     

Application of multiple channel estimators in MLSE detectors forfast time-varying and frequency selective channels

The authors propose a simplification of a maximum likelihood sequence estimator (MLSE) and multiple channel estimator algorithm used for equalising fast time-varying and frequency selective channels. The original algorithm suffers from a large computational burden when operating on typical mobile radio channels. The proposed algorithm reduces the number of channel estimators employed and the resulting performance/complexity tradeoff is simulated     

Joint array combining and MLSE for single-user receivers inmultipath Gaussian multiuser channels

The well-known structure of an array combiner along with a maximum likelihood sequence estimator (MLSE) receiver is the basis for the derivation of a space-time processor presenting good properties in terms of co-channel and intersymbol interference rejection. The use of spatial diversity at the receiver front-end together with a scalar MLSE implies a joint design of the spatial combiner and the impulse response for the sequence detector. This is faced using the MMSE criterion under the constraint that the desired user signal power is not cancelled, yielding an impulse response for the sequence detector that is matched to the channel and combiner response. The procedure maximizes the signal-to-noise ratio at the input of the detector and exhibits excellent performance in realistic multipath channels     

A structured channel estimator for maximum likelihood sequencedetection in multipath fading channels

This paper describes a channel estimator using known prior information about the transmit and receive filters, it is shown that the composite channel lies in a certain subspace obtained from the impulse responses of these filters. A structured linear channel model is then developed that is linearly parameterized by an unknown vector. To illustrate the potential usefulness of such an approach, the estimated structured channel is used in a multisensor and oversampled maximum likelihood sequence estimation (MLSE) receiver. We also present expressions on the pairwise error probability for the MLSE receiver based on the structured channel model. Using these results, we investigate the phenomenon of error flooring     

A continuously adaptive MLSE receiver for mobile communications:algorithm and performance

The paper presents a Euclidean distance maximum likelihood sequence estimation (MLSE) receiver, based on the Viterbi algorithm (VA), suitable for fading and noisy communications channels, as that specified by the Group Special Mobiles (GSM). In a mobile cellular system, the fast varying channel characteristics, due to the fading and Doppler effects, require adaptive methods to update the channel coefficients to the MLSE receiver. The proposed technique continuously estimates the channel characteristics directly within the metric calculation of the VA. At each step of the VA, the sequence associated to the path with the best metric value (minimum-survivor method) among the survivor paths is used to update the channel estimate (employing conventional adaptive algorithms) throughout the entire informative sequence. However, the detection of the transmitted data sequence is performed by the VA only at the end of each burst. The proposed technique allows simpler receiver implementation and the simulation results show a good performance of this adaptive MLSE receiver in typical GSM environments     

一种用于无线信道的逐幸存处理均衡器

提出了一种适用于无线时变信道的逐幸存处理均衡器。通过训练序列得到信道参数的初始估计值,此后在Viterbi算法进行网格搜索的过程中,使得每一条幸存路径维持各自的信道参数,并在确定幸存分支后利用历史幸存序列对信道参数值进行更新,实现了信道参数的无时延估计。仿真结果表明,在无线时变信道环境下,逐幸存处理均衡器的性能明显优于其他传统均衡器。     

A Practical Approach Toward Maximum Likelihood Sequence Estimation for Band-Limited Nonlinear Channels

A receiver structure, called a "pseudo maximum likelihood sequence estimation" (pseudo MLSE), which approximates MLSE with a simple hardware configuration, was derived. By introducting a tentatively estimated sequence, the pseudo MLSE detects the received sequence symbol by symbol, retaining the MLSE optimum decision property. The number of arithmetic operations required in one symbol duration is reduced fromM^{L + 1}to(L + 1)Min anM-ary signaling case with channel memory lengthL. An adaptation algorithm for the variation in the channel characteristics was also developed. Pseudo MLSE application to quadrature phase shift keying (QPSK) for a band-limited nonlinear channel is described. The most practical application of pseudo MSLE, named the "adaptive threshold detector with estimated sequence" (ATDES), detects symbols with threshold detection and is suitable for high bit rate operation. For both the pseudo MLSE processor and ATDES, most of the hardware is occupied by a replica memory stored in the receiver. Performance in a typical nonlinear satellite channel model is evaluated by computer simulation. Simulation results show a 0.8 dB improvement by ATDES with 64 replica memories and 1.3 dB improvement by the pseudo MLSE processor with 3072 replica memories. The tentative estimation error effect is estimated to be less than 0.1 dB in the simulated satellite channel.     

Analysis of LMS-adaptive MLSE equalization on multipath fadingchannels

We consider a practical maximum-likelihood sequence estimation (MLSE) equalizer on multipath fading channels in conjunction with an adaptive channel estimator consisting of a least mean square (LMS) estimator and a linear channel predictor, instead of assuming perfect channel estimates. A new LMS estimator model is proposed which can accurately characterize the statistical behavior of the LMS estimator over multipath fading channels. Based on this model, a new upper-bound on block error rate is derived under the consideration of imperfect channel estimates. Computer simulations verify that our analytical results can correctly predict the real system performance and are applicable over a wide range of the step size parameter of the LMS estimator     

带判决反馈的盲最大似然序列估计

本文提出了一种新型的带有判决反馈的减小状态最大似然序列估计ＲＳＳＤＦＰＳＰ,新算法带有两个信道估值器并且可以工作在盲环境下．使用最大似然序列估计（ＭＬＳＥ）来处理信道冲激响应的前导干扰及主径,反馈滤波器处理后尾干扰,并且用ＰｅｒＳｕｒｖｉｖｉｎｇＰｒｏｃｅｓｉｎｇ（ＰＳＰ）算法来得到ＭＬＳＥ部分的信道冲激响应,信道估值器２得到后尾干扰．计算机模拟表明,这种ＲＳＳＤＦＰＳＰ方案在减小ＭＬＳＥ的计算复杂度的同时能最大限度地得到ＭＬＳＥ的性能,是ＭＬＳＥ在计算复杂度与性能之间的较好折中．     

初始判决指导的DS／CDMA最大似然检测算法

本文首先给出了多径异步多用户ＤＳ／ＣＤＭＡ系统的一种数学模型，得出了恒参信道下最大似然检测（ＭＬＳＥ）算法的一种新的表示形式，然后作者具体分析了以ＲＡＫＥ接收机作为衰落信道的匹配滤波器时，最大似然检测器的算法设计问题，分析指出，在多径环境下ＭＬＳＥ算法的复杂度和计算量与多径时延的分布有关，如果有用户时延扩散在一个信息码元之内，算法复杂度和恒参信道下相同，而其实现可以用状态中变的Ｖｉｔｅｒｂｉ算法来     

Comparison of DFE and MLSE Receiver Performance on HF Channels

Data communication at rates near or above 2 kbits/s on 3 kHz-baadwidth HF radio channels is subject to impairment from severe linear dispersion, rapid channel time variation, and severe fading. In this investigation, recorded 2.4 kbit/s QPSK signals received from HF channels were processed to extract a time-varying estimate of the channel impulse response. From the estimated channel impulse responses, performance-related parameters were computed for ideal matched filter reception, maximum-likelihood sequence-estimation (MLSE), and decision feedback equalization (DFE). The results indicated that the simpler DFE receiver suffered only a small theoretical performance degradation relative to the more complex MLSE receiver. Other HF channel impulse response statistics were also obtained to shed light on equalization and filter adaptation techniques.     

Error performance of innovations-based MLSE for Rayleigh fadingchannels

Error performance of maximum likelihood sequence estimation (MLSE) of digital signals transmitted over Rayleigh fading channels is studied in this paper. The application of the innovations approach provides us not only with a general MLSE receiver structure, but also with a tool for analyzing the performance of the receiver. We show that the sequence pairwise error probability of the MLSE receiver is determined by the eigenvalues of a matrix generated from the autocorrelation function of the received signal. For any practical applications, the MLSE for Rayleigh fading channels exhibits an irreducible error floor that depends on the channel characteristics such as the Doppler frequency bandwidth and frequency selectivity. An upper bound on bit error probability can be calculated by using the sequence pairwise error probability. Also, it is shown that diversity reception can significantly improve the MLSE error performance     

初始判决指导下的DS/CDMA最大似然检测算法

本文首先给出了多径异步多用户ＤＳ／ＣＤＭＡ系统的一种数学模型，得出了恒参信道下最大似然检测（ＭＬＳＥ）算法的一种新的表示形式。然后作者具体分析了以ＲＡＫＥ接收机作为衰落信道的匹配滤波器时，最大似然检测器的算法设计问题。分析指出，在多径环境下ＭＬＳＥ算法的复杂度和计算量与多径时延的分布有关，如果用户时延扩散在一个信息码元之内，算法复杂度和恒参信道下相同，而其实现可以用状态数可变的Ｖｉｔｅｒｂｉ算法来实现。最后，本文用传统判决方法得出的初始判决信息缩减Ｖｉｔｅｒｂｉ算法的搜索空间，在保证一定性能的前提下，算法的计算复杂度大大降低。     

Performance of sequence estimation scheme of narrowband digital FMsignals with limiter-discriminator detection

A communication scheme using binary FM with noncoherent limiter-discriminator detection has been well known. Up to now, the improvement of bit error rate at the receiver side has been carried out through the bandwidth optimization of the IF filter, the decision feedback equalization (DFE), or simple two-state maximum likelihood sequence estimator (MLSE). This channel is inherently the intersymbol interference (ISI) channel due to the premodulation baseband filtering as well as the narrowband IF filtering. So the sequence estimation scheme using the Viterbi algorithm can be applied successfully, although the channel is not additive white Gaussian and maximum likelihood in the strict sense. In this paper, through computer simulations, we examine the actual BER improvement of the sequence estimation scheme with multiple-state trellis especially for MSK and GMSK signals. We mainly consider static AWGN and frequency nonselective Rician fading channels. Consequently, by adjusting the IF filter bandwidth, very large estimation gains are obtained compared to the conventional DFE or MLSE detector for AWGN and Rician fading channels. This scheme does not produce large demodulation delay and is implemented only by adding the signal processing part to the final stage of the receiver. This scheme seems to be very useful for any applications including satellite mobile channels     

A suboptimal approach to channel equalization based on the nearestneighbor rule

Applications of clustering and neural network techniques to channel equalization have revealed the classification nature of this problem. This paper illustrates an implementation of a global system for mobile communications (GSM) receiver in which channel equalization and demodulation are realized by means of the nearest neighbor (NN) classifier algorithm. The most important advantage in using such techniques is the significant reduction in terms of the computational complexity compared with the maximum likelihood sequence estimation (MLSE) equalizer. The proposed approach involves symbol-by-symbol interpretation and the knowledge of the channel is embedded in the mapping process of the received symbols over the symbols of the training sequence. This means that no explicit channel estimation need be carried out, either with correlative blocks or using neural networks thus speeding up the entire process. The performance of the proposed receiver, evaluated through a channel simulator for mobile radio communications, is compared with the results obtained by means of a 16-state Viterbi algorithm and other suboptimal receivers. It is shown that the presented algorithm increases the bit error rate (BER) compared with the MLSE demodulator, but the performance degradation, despite the simplicity of the receiver, is kept within the limits imposed by the GSM specifications