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     

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.     

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     

自适应均衡算法在信道均衡技术中的应用研究

文中描述了两种非线性均衡器分别为判决反馈均衡器(DFE)和最大似然序列估计(MLSE)均衡器.所用信道模型为加性白高斯噪声信道,在DFE和线性均衡器(LE)中都是使用递归最小二乘(RLS)算法和最小均方(LMS)算法对数据进行分块处理.MLSE均衡器中使用了维特比最佳译码算法.就误比特性能来做以比较,DFE远好于LE,MLSE均衡器又明显优于DFE,并且它能达到几乎最优的性能.     

BAD: bidirectional arbitrated decision-feedback equalization

The bidirectional arbitrated decision-feedback equalizer (BAD), which has bit-error rate performance between a decision-feedback equalizer (DFE) and maximum a posteriori (MAP) detection, is presented. The computational complexity of the BAD algorithm is linear in the channel length, which is the same as that of the DFE, and significantly lower than the exponential complexity of the MAP detector. While the relative performance of BAD to those of the DFE and the MAP detector depends on the specific channel model, for an error probability of 10/sup -2/, the performance of BAD is typically 1-2 dB better than that of the DFE, and within 1 dB of the performance of MAP detection.     

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。     

An adaptive truncated MLSE receiver for Japanese personal digitalcellular

This paper describes a dual-mode Japanese personal digital cellular receiver that uses an adaptive truncated symbol-spaced maximum-likelihood sequence-estimation (MLSE) equalizer in one mode and a tangent type differential detector in the other. The receiver employs a channel estimation and symbol synchronization procedure that uses the known phase shifts between successive symbols in the synchronization word. Per-survivor processing is used to track the channel variations and carrier frequency offset. Simulation results are presented for multipath Rayleigh fading channels having various delay profiles. Comparisons between the regular symbol-spaced truncated MLSE equalizer and a fractionally spaced truncated MLSE equalizer are also furnished     

Adaptive MLSE equalizers with parametric tracking for multipathfast-fading channels

We use the parametric channel identification algorithm proposed by Chen and Paulraj (see Proc. IEEE Vehicular Technology Conf., p.710-14, 1997) and by Chen, Kim and Liang (see IEEE Trans. Veh. Technol., p.1923-35, 1999) to adaptively track the fast-fading channels for the multichannel maximum likelihood sequence estimation (MLSE) equalizer using multiple antennas. Several commonly-used channel tracking schemes, decision-directed recursive least square (DD/RLS), per-survivor processing recursive least square (PSP/RLS) and other reduced-complexity MLSE algorithms are considered. An analytic lower bound for the multichannel MLSE equalizer with no channel mismatch in the time-varying specular multipath Rayleigh-fading channels is derived. Simulation results that illustrate the performance of the proposed algorithms working with various channel tracking schemes are presented, and then these results are compared with the analytic bit error rate (BER) lower bound and with the conventional MLSE equalizers directly tracking the finite impulse response (FIR) channel tap coefficients. We found that the proposed algorithm always performs better than the conventional adaptive MLSE algorithm, no matter what channel tracking scheme is used. However, which is the best tracking scheme to use depends on the scenario of the system     

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     

Efficient bad equalizer in two-ray multipath fading channels

An efficient bidirectional arbitrated decision feedback (BAD) equalizer is presented in single-carrier block transmission system in the Two-Ray multipath fading channels, where the output from the bidirectional equalizers are combined together directly using maximal ratio combining (MRC) rule to improve the signal-to-noise ratio (SNR) before demodulation. The computational complexity of the BAD equalizer presented is linear with the channel length, which is the same as conventional decision feedback equalizer (DFE) and is significantly lower than that of conventional BAD equalizer as well as the maximum likelihood (ML) algorithm. While the performance of the new scheme depends on the specific channel characteristics, it is shown by simulation results that the performance of the new BAD can surpass the one of DFE dramatically in the minimum or non-minimum phase Two-Ray multipath fading channels.     

Adaptive Decision Feedback Space–Time Equalization With Generalized Sidelobe Cancellation

In wireless communications, cochannel interference (CCI) and intersymbol interference (ISI) are two main factors that limit system performance. Conventionally, a beamformer is used to reduce CCI, whereas an equalizer is used to compensate for ISI. These two devices can be combined into one as space–time equalizer (STE). A training sequence is usually required to train the STE prior to its use. In some applications, however, spatial information corresponding to a desired user is available, but the training sequence is not. In this paper, we propose an adaptive decision feedback STE to cope with this problem. Our scheme consists of an adaptive decision feedback generalized sidelobe canceller (DFGSC), a blind decision feedback equalizer (DFE), and a channel estimator. Due to the feedback operation, the proposed DFGSC is not only superior to the conventional generalized sidelobe canceller but also robust to multipath channel propagation and spatial signature error. Theoretical results are derived for optimum solutions, convergence behavior, and robustness properties. With the special channel-aided architecture, the proposed blind DFE can reduce the error propagation effect and be more stable than the conventional blind DFE. Simulation results show that the proposed STE is effective in mitigating both CCI and ISI, even in severe channel environments.      

稀疏多径信道的T/2间隔CFE均衡器研究

完全反馈均衡器(Complete Feedback Equalizer, CFE)是判决反馈均衡器(DFE)的改进。该文提出了一种T/2分数间隔稀疏CFE(T/2 Sparse CFE, T/2-SCFE)结构,以避免接收机对于符号定时误差的敏感性,并有效利用长时延扩展多径信道的稀疏性来降低均衡器的复杂度。理论分析与基于实测信道的计算机仿真表明, T/2-SCFE均衡器对符号定时误差保持了稳健性,总体性能优于符号间隔CFE及分数间隔DFE。     

Estimation of co-channel signals with linear complexity

To increase wireless system capacity using co-channel signals and multiple receiver antennas, we develop the partitioned Viterbi algorithm (PVA). The PVA estimation complexity increases linearly with each additional co-channel signal rather than exponentially as it does with joint maximum-likelihood sequence estimation (MLSE). The estimation problem involves multiple signals simultaneously transmitted and observed through slow-fading, frequency-selective channels. Although transmission is assumed to be in bursts according to a time-division multiple-access scheme, more than one signal can occupy the same time and frequency slot (these signals are referred to as “co-channel” signals). Separation and estimation of the symbol bursts is accomplished by exploiting channel differences, PVA estimation consists of a set of Viterbi detectors, one per signal, that operate in parallel with cross-coupling to allow approximate interference cancellation by means of tentative decisions. The forward filter of a decision feedback equalizer (DFE) is used to “prefilter” received signals prior to PVA estimation. Prefiltering delays the energy of interfering signals so that tentative decisions become reliable enough to use. Simulation results show PVA performance remains near-optimal with respect to the performance of joint MLSE     

A channel estimation using sliding window approach and tuningalgorithm for MLSE

A simultaneous sliding window channel estimation and timing adjustment method is proposed for adaptive maximum-likelihood sequence equalizer (MLSE) in the global system for mobile communication (GSM) system, and also a tuning scheme based on least mean squared (LMS) algorithm is presented in order to improve the performance of equalizer. Simulation results show that the proposed channel estimation technique is effective for channel estimation of the adaptive equalizer     

Adaptive maximum-likelihood sequence estimation by means ofcombined equalization and decoding in fading environments

This paper proposes an adaptive maximum-likelihood sequence estimation (MLSE) by means of combined equalization and decoding, i.e., adaptive combined MLSE, which employs separate channel estimation for respective states in the Viterbi algorithm. First, an approximate metric including channel estimation is derived analytically for this proposed adaptive combined MLSE. Secondly, procedures to accomplish blind equalization are investigated for the proposed MLSE. Finally, its excellent BER performance on fast time-varying fading channels is confirmed by computer simulation, when the proposed MLSE operates as a blind equalizer     

On adaptive decision-feedback equalization of intersymbolinterference channels in coded modulation systems

Recently, Eyuboglu (1988) has shown that adaptive noise-predictive decision-feedback equalization (DFE) can be combined with coded modulation to achieve high-speed data transmission by periodic interleaving. In this paper, we present a new method of adaptive DFE with periodic interleaving for coded modulation systems. The method is an improved version of that proposed by Eyuboglu, where the deinterleaving operation is performed on a vector-by-vector basis, instead of a sample-by-sample basis. Unlike the original system in which the linear equalizer's coefficients can be adjusted only with hard decisions from the threshold detector, the improved structure updates the coefficients of both the linear equalizer and the noise predictor based on soft decisions from the most likely path in the soft decoder. The improved system achieves better error-rate performance than the original with a little increase in hardware complexity. As compared to another improved design reported by Zhou et al. (1990), the new structure also gains advantages in error-rate performance, hardware complexity, and throughput delay     

Adaptive decision feedback equalization for digital satellitechannels using multilayer neural networks

This paper introduces an adaptive derision feedback equalization using the multilayer perceptron structure of an M-ary PSK signal through a TDMA satellite radio channel. The transmission is disturbed not only by intersymbol interference (ISI) and additive white Gaussian noise, but also by the nonlinearity of transmitter amplifiers. The conventional decision feedback equalizer (DFE) is not well-suited to detect the transmitted sequence, whereas the neural-based DFE is able to take into account the nonlinearities and therefore to detect the signal much better. Nevertheless, the applications of the traditional multilayer neural networks have been limited to real-valued signals. To overcome this difficulty, a neural-based DFE is proposed to deal with the complex PSK signal over the complex-valued nonlinear MPSK satellite channel without performing time-consuming complex-valued back-propagation training algorithms, while maintaining almost the same computational complexity as the original real-valued training algorithm. Moreover, a modified back-propagation algorithm with better convergence properties is derived on the basis of delta-bar-delta rule. Simulation results for the equalization of QPSK satellite channels show that the neural-based DFE provides a superior bit error rate performance relative to the conventional mean square DFE, especially in poor signal-to-noise ratio conditions     

Electrical equalization for advanced optical communication systems

We investigate equalizers for electronic dispersion compensation (EDC) of dispersion limited optical fibre communication links in combination with different modulation formats. We show that the performance of conventional equalizers including feedforward equalizer (FFE) and decision feedback equalizer (DFE) are fundamentally limited by the nonlinearity of square-law detection of the photodiode in direct detection systems. Advanced modulation formats such as differential phase shift keying (DPSK) and optical duobinary further enhance this kind of nonlinearity and degrade further FFE/DFE performance. However, nonlinear FFE–DFE and maximum likelihood sequence estimation (MLSE) take into account the mitigation of nonlinear inter symbol interference (ISI) and hence can achieve much better performance. We show that in contrast to other modulation formats, optical single sideband modulation results in approximately linear distortions after detection and thus a simple linear FFE equalizer can achieve good compensation.     

时域自适应均衡技术的分析与应用

概述了频率选择性衰落信道的传输特性,论述了采用均衡技术的必要性。通过对各种均衡器结构和自适应均衡算法在抵抗符号间干扰能力、收敛速度以及运算复杂度等方面的分析与比较,选择了判决反馈作为均衡器结构、最小均方自适应算法作为自适应准则的均衡器方案。仿真及试验结果证实了设计的时域自适应均衡器不仅具有较强的抵抗符号间干扰能力,而且能够获得隐分集增益,在频率选择性衰落信道中具有良好的应用效果。     

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