Comparative study of space-diversity techniques for MLSE receiversin mobile radio

Several space-diversity techniques combined with maximum-likelihood sequence estimation (MLSE) are considered for time-division multiple-access (TDMA) digital mobile radio. Under the assumption that diversity paths fade independently, the Nth order diversity maximum-likelihood (ML) receiver is analyzed. Two categories of diversity receivers with MLSE are taken into account: the receivers performing diversity on the signal samples and those applying diversity inherently in the sequential algorithm. The simulation study was performed for standard global system for mobile communication (GSM) channel models. The results confirm the fact that even second-order diversity is a very powerful means improving the TDMA system 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     

MULTIPLE-TRAINING BI-DIRECTIONAL ADAPTIVE EQUALIZERS FOR TDMA DIGITAL CELLULAR SYSTEMS

In this paper, two popular adaptive equalization methods, fractionally spaced decision feedback equalization (FSDFE) and maximum-likelihood sequence estimation (MLSE), are investigated for the design of digital mobile receivers for the IS-54 specifications of the NADC* system. A bi-directional equalization technique is incorporated and a multiple training LMS (MT-LMS) algorithm is used as the adaptive algorithm for both equalization methods. The results show that both MT-MLS and bi-directional techniques are effective in improving the receiver performance. However, the MT-LMS algorithm is more useful for MLSE than FSDFE whereas the bi-directional equalization technique improves FSDFE much more than MLSE.     

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     

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     

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     

Equalization concepts for EDGE

An equalization concept for the novel radio access scheme Enhanced Data rates for GSM Evolution (EDGE) is proposed by which high performance can be obtained at moderate computational complexity. Because high-level modulation is employed in EDGE, optimum equalization as usually performed in Global System for Mobile Communications (GSM) receivers is too complex and suboptimum schemes have to be considered. It is shown that delayed decision-feedback sequence estimation (DDFSE) and reduced-state sequence estimation (RSSE) are promising candidates. For various channel profiles, approximations for the bit error rate of these suboptimum equalization techniques are given and compared with simulation results for DDFSE. It turns out that a discrete-time prefilter creating a minimum-phase overall impulse response is indispensable for a favorable tradeoff between performance and complexity. Additionally, the influence of channel estimation and of the receiver input filter is investigated and the reasons for performance degradation compared to the additive white Gaussian noise channel are indicated. Finally, the overall system performance attainable with the proposed equalization concept is determined for transmission with channel coding     

New approaches to adjacent channel interference suppression inFDMA/TDMA mobile radio systems

The capacity and signal quality of wireless communication systems can be improved by enhancing receiver performance in the presence of adjacent channel interference (ACI), In this paper, maximum-likelihood sequence estimation (MLSE) receivers based on joint demodulation and successive cancellation of adjacent channel signals are developed. The proposed receivers provide significant improvement in performance over a wide range of carrier-to-interference ratios. To provide coherent reception, novel channel estimation techniques are used, exploiting knowledge of the transmit and receive filter responses. Performance is evaluated and compared via simulation for the Global System for Mobile communications (GSM) digital cellular system     

Performance analysis of an adaptive receiver structure for digital mobile communications

In this paper we investigate the performance of a combined estimation/equalization technique for the mobile radio channel, assuming a GSM-recommended transmission format (narrowband TDMA with midamble, recommendation 5.04) and MSK modulation scheme. Channel estimation is performed via correlation of the received signal with a suitably modulated replica of the transmitted midamble. Equalization is then obtained by means of a maximum likelihood sequence estimation (MLSE) scheme in the form of a so-called Viterbi equalizer. Our analysis provides theoretical results concerning the bit error rate (BER) attained by the receiver for a given stationary multipath channel model. Simulation results are also presented in order to integrate and validate the theory.     

Nonparametric trellis equalization in the presence of non-Gaussian interference

We consider the problem of trellis equalization of the intersymbol interference channel in the presence of thermal noise and cochannel interference (CCI). Conventional maximum-likelihood sequence estimation (MLSE) and maximum a posteriori probability (MAP) trellis equalizers treat the sum of noise and interference as additive white Gaussian noise, while CCI is generally a colored non-Gaussian process. We propose a novel nonparametric approach based on the estimation of the probability density function of the noise-plus-interference. Given the availability of a limited volume of data, the density is estimated by kernel-smoothing techniques. The use of a whitening filter in the presence of temporally colored disturbance is also addressed. Simulation results are provided for the global system for mobile communications (GSM), showing a significant performance improvement with respect to the equalizer based on the Gaussian assumption. Major advantages of the proposed strategy are its intrinsic robustness and general applicability to those cases where accurate modeling of the interference is difficult or a model is not available.     

A Homotopy-Controlled Mean Field Annealing Partially-Connected Neural Equalizer for Pan-European GSM System

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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.     

A comparison of GSM receivers for fading multipath channels withadjacent and co-channel interference

We evaluate and compare several data detection schemes used in GSM systems. In particular, we compare the performance of decision feedback equalization (DFE) and nonlinear data directed estimation (NDDE) to that of maximum likelihood sequence estimation (MLSE). Establishing the performance of the basic NDDE detector is a first step in investigating the applicability of block transmission techniques to GSM systems. Our simulation results, obtained both for fading multipath channels and adjacent- and co-channel interference scenarios, suggest that the NDDE offers certain performance advantages over the DFE, and the performance of both detectors is comparable to that of the MLSE for the SNR region of interest in practical systems. Thus, they both represent viable alternatives to the MLSE detector     

用于盲接收的turbo均衡与迭代信道估计

Turbo均衡是一种将信道均衡和差错控制译码联合迭代处理的均衡机制,与传统的均衡器相比,能在更低的信噪比条件下克服严重信道失真导致的符号间干扰(ISI)。该文提出一种用于盲接收的turbo均衡和迭代信道估计方案,不依赖于训练序列或发送符号的先验知识,采用初始盲均衡处理来启动迭代信道估计和turbo均衡。在该方案中,初始盲均衡算法的选择是十分关键的,它需要在恶劣的信道条件为后续迭代处理的启动提供足够的先验信息。该文根据turbo均衡的特点,选择了超指数算法作为初始盲均衡。仿真结果表明,该文提出的用于盲接收的turbo均衡方案是有效的。     

Application of Sequential Estimation Algorithm Based on Branch Metric to Frequency-Selective Channel Equalization

In this work, a sequential estimation algorithm based on branch metric is used as channel equalizer to combat intersymbol interference in frequency-selective wireless communication channels. The bit error rate (BER) and computational complexity of the algorithm are compared with those of the maximum likelihood sequence estimation (MLSE), the recursive least squares (RLS) algorithm, the Fano sequential algorithm, the stack sequential algorithm, list-type MAP equalizer, soft-output sequential algorithm (SOSA) and maximum-likelihood soft-decision sequential decoding algorithm (MLSDA). The BER results have shown that whilst the sequential estimation algorithm has a close performance to the MLSE using the Viterbi algorithm, its performance is better than the other algorithms. Beside, the sequential estimation algorithm is the best in terms of computational complexity among the algorithms mentioned above, so it performs the channel equalization faster. Especially in M-ary modulated systems, the equalization speed of the algorithm increases exponentially when compared to those of the other algorithms.     

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.     

Decision feedback sequence estimation for unwhitened ISI channelswith applications to multiuser detection

Decision feedback sequence estimation (DFSE), which is a reduced-complexity alternative to maximum likelihood sequence estimation (MLSE), can be used effectively for equalization of intersymbol interference (ISI) as well as for multiuser detection. The algorithm performs very well for whitened (minimum-phase) channels. For nonminimum-phase channels, however, the algorithm is not very effective. Moreover, DFSE requires a noise-whitening filter, which may not be feasible to compute for time-varying channels such as a multiuser direct-sequence code division multiple access (DS-CDMA) channel. Noise-whitening is also cumbersome for applications that involve bidirectional equalization such as the global system for mobile communication (GSM) system. In such conditions, it is desirable to use the Ungerboeck (1974) formulation for sequence estimation, which operates directly on the discrete-time unwhitened statistic obtained from conventional matched filtering. Unfortunately, DFSE based on matched filter statistics is severely limited by untreated interference components. We identify the anticausal interference components, using an error probability analysis. This leads us to a modified unwhitened decision feedback sequence estimator (MUDFSE) in which the components are canceled, using tentative decisions. We obtain approximate error probability bounds for the proposed algorithm. Performance results indicate that the modified algorithm, used on unwhitened channels with relatively small channel correlations, provides similar performance/complexity tradeoffs as the DFSE used on the corresponding whitened minimum-phase channels. The algorithm is especially attractive for multiuser detection for asynchronous DS-CDMA channels with long spreading codes, where it can achieve near-MLSE performance with exponentially lower complexity     

Multichannel MLSE equalizer with parametric FIR channelidentification

We propose a parametric finite impulse response (FIR) channel identification algorithm, apply the algorithm to a multichannel maximum likelihood sequential estimation (MLSE) equalizer using multiple antennas, and investigate the improvement in the overall bit error rate (BER) performance. By exploring the structure of the specular multipath channels, we are able to reduce the number of channel parameters to provide a better channel estimate for the MLSE equalizer. The analytic BER lower bounds of the proposed algorithm as well as those of several other conventional MLSE algorithms in the specular multipath Rayleigh-fading channels are derived. In the derivation, we consider the channel mismatch caused by the additive Gaussian noise and the finite-length channel approximation error. A handy-to-use simplified BER lower bound is also derived. Simulation results that illustrate the BER performance of the proposed algorithm in the global system for mobile communications (GSM) system are presented and compared to the analytic lower bounds     

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     

基于叠加训练序列和低复杂度频域Turbo均衡的时变水声信道估计和均衡

针对时变水声信道估计和均衡问题,该文提出基于叠加训练序列(ST)和低复杂度频域Turbo均衡(LTE)的时变水声信道估计和均衡(ST-LTE)算法。基于叠加训练序列方案,将训练序列和符号线性叠加,使得训练序列和符号信道信息一致;基于最小二乘算法,进行信道估计。基于频域训练序列干扰消除技术,在频域消除训练序列对符号的干扰;基于频域线性最小均方误差(LMMSE)均衡算法,通过先验、后验、外均值和方差的计算,实现低复杂度信道均衡(符号估计);基于Turbo均衡算法,软重构叠加训练序列和更新信道估计,进行均衡器和译码器的信息交换,利用编码冗余信息,大幅度提升信道均衡性能。进行仿真、水池静态通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率4.8 ksym/s,训练序列和符号的功率比为0.25:1)和胶州湾运动通信试验(通信频率12 kHz,带宽6 kHz,采样频率96 kHz,符号传输速率3 ksym/s,训练序列和符号的功率比为0.25:1),仿真和试验结果验证了所提算法的有效性。