John G. Proakis

Adaptive maximum-likelihood sequence estimation for digital signaling in the presence of intersymbol interference (Corresp.)

An adaptive maximum-likelihood sequence estimator for a digital pulse-amplitude-modulated sequence in the presence of finite-duration unknown slowly time-varying intersymbol interference and additive white Gaussian noise is developed. Predicted performance and simulation results for specific channels are given.

An adaptive receiver for digital signaling through channels with intersymbol interference

A tutorial paper on an adaptive receiver that is suitable for high-speed digital signaling over slowly time-varying, band-limited channels which have impulse responses that are unknown at the receiver is presented. The receiver utilizes a steepest-descent technique for adjusting its parameters to existing channel conditions. A treatment of the speed of adaptation of the receiver is included.

Design of efficient coding and modulation for a Rayleigh fading channel

The design of a coding/modulation structure for digital communications over a Rayleigh fading channel, the structure of the corresponding decoder, and the error rate performance of the resulting system are considered. Emphasis is on the use of constant weight codes for constructing equal energy waveforms for transmission over the channel. The performance gains that are achieved by the integrated coding/modulation approach relative to conventional methods for obtaining diversity are illustrated via some examples. Of special interest is the use of a concatenated coding technique for forming codes of large distance and hence high diversity. A new decoding algorithm is applied to enable efficient decoding of the concatenated code. An example is included that shows a performance increase of several dB resulting from concatenation.

MLD and mse algorithms for adaptive detection of digital signals in the presence of interchannel interference

Adaptive mean-square error (mse) and maximum-likelihood detection (MLD) algorithms for a dual-channel digital communication system in the presence of interchannel interference and white Gaussian noise are presented. The mse algorithm forms estimates of the transmitted symbols from a linear combination of received symbols using weights that minimize the mse between transmitted and estimated symbols. The nonlinear MLD algorithm minimizes the probability of symbol error by maximizing the probability of the received signal samples on the two channels over ail possible transmitted symbol pairs. The probability of error is derived for the two algorithms when quadrature phase-shift keying (QPSK) is used as a modulation technique, and is compared with that of a dual-channel QPSK system having no compensation for the crosstalk.

An estimate of the upper bound on error probability for maximum-likelihood sequence estimation on channels having a finite-duration pulse response (Corresp.)

An estimate of an upper bound on performance in terms of probability of error is developed for maximum-likelihood sequence estimation over channels for which only the pulse response energy and duration are known. This bound is evaluated for channels with a pulse response duration up to 10 signaling intervals, and the related minimum-distance channel codes are presented.

Exact distribution functions of test length for sequential processors with discrete input data

In studies of sequential detection of radar signals, the parameter of primary interest is the length of the sequential test, denoted by n . Since this test length is a random variable, moments and/or probability distribution functions of n are desirable. A procedure is described in this communication for obtaining exact probability distribution functions P(n) and exact average values of n , E(n) , when the input to the sequential processor is discrete radar data (radar data in quantized form). This procedure is based upon the representation of the sequential test as a Markov process. The results are quite general in that they apply to multilevel quantization of the data. However, the procedure appears especially attractive when the number of levels is small as is usually the case when dealing with discrete radar data. The procedure for determining exact distribution functions and average values of n presented herein is compared with the Wald-Girshick approach for obtaining P(n) and E(n) , and the superiority of the former approach in computational convenience is indicated.

Set-partition Coding

The purpose of this two-part monograph is to present a tutorial on set partition coding, with emphasis and examples on image wavelet transform coding systems, and describe their use in modern image...

Correction to 'Adaptive Maximum-Likelihood Sequence Estimation for Digital Signaling in the Presence of Intersymbol Interference'

In the above correspondence, 1 Fig. 5 contains data on the error rate performance of adaptive maximum-likelihood sequence estimation (MLSE) and an adaptive decision-feedback equalizer (DFE) for the two channel characteristics A and B, shown in Fig. 4. Channel A is an equivalent discrete-time model consisting of the three terms go = 0.5, g1 = 1.0, g2 = OS, while channel B consists of the five terms go = 0.33, gl = 0.67, g2 = 1.0, 93 = 0.67, g4 = 0.33. The error rate performance of the DFE was obtained for binary signaling by Monte Carlo simulation on a digital computer. Suboptimum synchronization of the DFE output with the desired output resulted in a degradation in performance of the DFE. Consequently, the performance results previously reported1 show a larger gap between MLSE and DFE than is actually the case. Upon correction of the synchronization error in the DFE, the error rate performance results shown here in Fig. 1 were obtained. The error rate curves are plotted as a function of 10 log y, where y is the signal-to-noise ratio defined as