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     

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。     

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.     

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     

On optimum detection of linearly filtered CPM signals

A novel structure of the MLSE receiver for linearly filtered CPM (continuous phase modulation) signals is derived. It is shown that the correlator bank required in the works of Svensson (1987) can equivalently be replaced by a reduced correlator bank, preceded by a linear filter with impulse response h*(-t) [channel matched filter]. The reduced correlator bank only incorporates characteristics of the CPM signals and is independent of the channel impulse response. This implies that the complexity of the modified correlator bank depends only linearly on the channel filter impulse response length. The proposed receiver structure permits considerable complexity reduction when compared to the currently known solution     

Adaptive Bayesian decision feedback equalizer for dispersive mobileradio channels

The paper investigates adaptive equalization of time-dispersive mobile radio fading channels and develops a robust high performance Bayesian decision feedback equalizer (DFE). The characteristics and implementation aspects of this Bayesian DFE are analyzed, and its performance is compared with those of the conventional symbol or fractional spaced DFE and the maximum likelihood sequence estimator (MLSE). In terms of computational complexity, the adaptive Bayesian DFE is slightly more complex than the conventional DFE but is much simpler than the adaptive MLSE. In terms of error rate in symbol detection, the adaptive Bayesian DFE outperforms the conventional DFE dramatically. Moreover, for severely fading multipath channels, the adaptive MLSE exhibits significant degradation from the theoretical optimal performance and becomes inferior to the adaptive Bayesian DFE     

Decision feedback sequence estimation for continuous phasemodulation on a linear multipath channel

An approach to reduced-complexity detection of partial response continuous phase modulation (CPM) on a linear multipath channel is presented. The method, referred to as decision feedback sequence estimation (DFSE), is based on a conventional Viterbi algorithm (VA) using a reduced-state trellis combined with decision feedback (DF). By varying the number of states in the VA, the receiver structure can be changed gradually from a DF receiver to the optimal maximum-likelihood sequence estimator (MLSE). In this way different tradeoffs between performance and complexity can be obtained. Results on the receiver performance, based on minimum distance calculations and bit error rate simulations, are given for Gaussian minimum-shift keying modulation on typical mobile radio channels. It is shown that for channels with a long memory, a significant complexity reduction can be achieved at the cost of a moderate degradation in performance     

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     

Fast adaptive equalization/diversity combining for time-varyingdispersive channels

We examine adaptive equalization and diversity combining methods for fast Rayleigh-fading frequency selective channels. We assume a block adaptive receiver in which the receiver coefficients are obtained from feedforward channel estimation. For the feedforward channel estimation, we propose a novel reduced dimension channel estimation procedure, where the number of unknown parameters are reduced using a priori information of the transmit shaping filter's impulse response. Fewer unknown parameters require a shorter training sequence. We obtain least-squares, maximum-likelihood, and maximum a posteriori (MAP) estimators for the reduced dimension channel estimation problem. For symbol detection, we propose the use of a matched filtered diversity combining decision feedback equalizer (DFE) instead of a straightforward diversity combining DFE. The matched filter form has lower computational complexity and provides a well-conditioned matrix inversion. To cope with fast time-varying channels, we introduce a new DFE coefficient computation algorithm which is obtained by incorporating the channel variation during the decision delay into the minimum mean square error (MMSE) criterion. We refer to this as the non-Toeplitz DFE (NT-DFE). We also show the feasibility of a suboptimal receiver which has a lower complexity than a recursive least squares adaptation, with performance close to the optimal NT-DFE     

基于快衰落信道的一种新型自适应MLSE接收器

在移动通信系统中,由于衰落和多普勒效应,为了实现基于Viterbi算法的极大似然序列估计(MLSE),需要不断跟踪信道参数变化.本文首先提出了一种新的基于插值的信道估计方法ICP(Interpolating channel processing),并给出了该方法的两种实现形式,同已有的一些算法的比较结果表明:新方法具有更小的计算复杂度,误码率更低.同时,本文对如何降低Viterbi算法(VA)的计算复杂度也作了探讨.通过采用自适应减小计算复杂度的算法(ATA),本文提出的ICP算法具有更优的性能.     

CCK demodulation via symbol decision feedback equalizer

A symbol decision feedback equalization (DFE) technique is developed for demodulating complementary code keying (CCK) signals. The efficacy of the proposed receiver is demonstrated on the physical layer (PHY) specified in the IEEE 802.11b wireless local area network (WLAN) standard. Packet error rate (PER) performance is compared with that of the conventional RAKE receiver. The proposed receiver structure and its low complexity variations demonstrate significant performance advantages over the RAKE receiver, especially in severe multipath channels. While a large delay spread can limit the performance of two low-complexity variations discussed here, performance of the optimal symbol DFE receiver is not limited by delay spread as long as the channel signal-to-noise ratio (SNR) is sufficiently high.     

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     

面向ASIC设计的单载波超宽带信道均衡研究

单载波超宽带通信系统的均衡在芯片实现中面临高吞吐率、高性能和低复杂度三方面问题。该文首先比较了最大似然均衡（MLSE）、线性均衡（LE）、判决反馈均衡（DFE）及单载波频域均衡（SC-FDE）在性能、复杂度及高速化实现上的优缺点,并综合考虑SC-UWB系统这一特殊的应用场景最终选择了DFE。然后针对DFE算法中的三个关键参数——前馈阶数Nf,反馈阶数Nb及判决延迟D,提出了一种实际系统中有效且实用的参数优化设计策略,最后仿真证明了优化策略的实用性和有效性。     

一种短波信道自适应均衡算法的研究

基于逐幸存路径处理(PSP)的思想,研究了一种减少状态序列估计(RSSE)的短波信道自适应均衡算法.该算法首先通过训练序列估计信道的参数,然后利用RLS算法对信道参数和输入数据的估计值同时进行逐幸存路径地更新.数值仿真表明,在短波信道环境下,RSSE-PSP算法在减小计算复杂度的同时最大限度地保持了性能增益,其性能明显优于其他均衡算法.     

Pole-zero decision feedback equalization with a rapidly convergingadaptive IIR algorithm

A decision feedback equalizer (DFE) containing a feedback filter with both poles and zeros is proposed for high-speed digital communications over the subscriber loop. The feedback filter is composed of a relatively short FIR filter that cancels the initial part of the channel impulse response, which may contain rapid variations due to bridge taps, and a pole-zero, or IIR, filter that cancels the smoothly decaying tail of the impulse response. Modifications of an adaptive IIR algorithm, based on the Steiglitz-McBride (1965) identification scheme, are proposed to adapt the feedback filter. A measured subscriber loop impulse response is used to compare the performance of the adaptive pole-zero DFE, assuming a two-pole feedback filter, with a conventional DFE having the same number of coefficients. Results show that the pole-zero DFE offers a significant improvement in mean squared error relative to the conventional DFE. The speed convergence of the adaptive pole-zero DFE is comparable to that of the conventional DFE using the standard least mean square (LMS) adaptive algorithm     

A decision feedback equalizer with time-reversal structure

This work describes the use of a receiver with a time-reversal structure for low-complexity decision feedback equalization of slowly fading dispersive indoor radio channels. Time-reversal is done by storing each block of received signal samples in a buffer and reversing the sequential order of the signal samples in time prior to equalization. As a result, the equivalent channel impulse response as seen by the equalizer is a time-reverse of the actual channel impulse response. Selective time-reversal operation, therefore, allows a decision feedback equalizer (DFE) with a small number of forward filter taps to perform equally well for both minimum-phase and maximum-phase channel characteristics. The author evaluates the theoretical performance bounds for such a receiver and quantifies the possible performance improvement for discrete multipath channels with Rayleigh fading statistics. Two extreme cases of DFE examples are considered: an infinite-length DFE; and a DFE with a single forward filter tap. Optimum burst and symbol timing recovery is addressed and several practical schemes are suggested. Simulation results are presented. The combined use of equalization and diversity reception is considered     

Block adaptive techniques for channel identification and datademodulation over band-limited channels

A new approach to the problem of data detection for communications over band-limited channels with unknown parameters is introduced. We propose a new way to implement the Viterbi algorithm (VA) for maximum-likelihood data sequence estimation (MLSE) in a known channel environment and utilize it to derive block adaptive techniques for joint channel and data estimation, when the channel-impulse response (CIR) is unknown. We show, via simulations, that we can achieve a probability of error very close to that of the known channel environment and nearly reach a mean-square error in the channel estimate as predicted by analytical bounds, operating on static channels, which exhibit deep nulls in their magnitude response and nonlinear phase. The proposed schemes accomplish channel acquisition after processing a few hundred symbols while operating without a training sequence, whereas linear blind equalizers, such as Sato's (1975) algorithm, fail to converge at all. The application of block processing to adaptive MLSE is also investigated for time-varying frequency-selective Rayleigh-fading channels, which are used for modeling mobile communication systems. In such environments it is shown that the proposed scheme exhibits improved performance compared to the conventional adaptive MLSE receiver using tentative delayed decisions     

抑制DS-UWB多径干扰的RAKE-MLSE接收机

为达到高数据速率，直接序列超宽带（DS-UWB）系统通常使用低扩频增益，在密集多径信道中这可能会增强多径干扰（MPI）从而降低系统的性能。文中将最大序列似然估计（MLSE）引入DS-UWB接收机结构中来抑制MPI。推导了DS-UWB信号的MLSE公式，作为MLSE算法的近似提出采用RAKE-MLSE接收机结构来降低计算复杂度。使用Viterbi算法实现了该接收机，并在IEEE802．15．3a建议的室内信道中对一个DS-UWB系统进行仿真。仿真结果表明该接收机较一般RAKE接收机性能有很大提高。     

一种低复杂度聚类估计MLSE均衡器

给出了一种新的聚类估计最大似然序列均衡器(CBSE),避开了传统MLSE均衡需要估计信道脉冲响应(CIR)和卷积运算,由接收信号估计聚类中心,同时利用聚类中心之间的对称性,仅需估计其中部分中心,其余中心可通过简单运算获取,从而在缩短训练序列的同时减少了运算量.仿真表明,新方法在取得与RLS均衡器相近收敛性能的同时,计算量比LMS均衡器小.     

Adaptive equalization for TDMA digital mobile radio

Adaptive equalization for a TDMA (time-division multiple-access) digital cellular system is discussed. A survey of adaptive equalization techniques that includes their performance characteristics and limitations and their implementation complexity is presented. The design of adaptive equalization algorithms for a narrowband TDMA system is considered. It is concluded that, on the basis of implementation complexity and performance in the presence of multipath distortion and signal fading, MLSE (maximum-likelihood sequence estimation) and DFE (decision feedback equalization) are viable equalization methods for mobile radio