Neural-net-based receiver structures for single- and multiamplitude bandlimited signals in CCI and ACI channels

TitleNeural-net-based receiver structures for single- and multiamplitude bandlimited signals in CCI and ACI channels
Publication TypeJournal Article
Year of Publication1997
AuthorsBouras, D. P., P. T. Mathiopoulos, and D. Makrakis
JournalIEEE Transactions on Vehicular Technology
Volume46
Pagination791–798
ISSN0018-9545
Abstract

This paper presents analysis and performance-evaluation results for several neural-network-based nondecision-feedback receiver structures, which improve the performance of bandlimited single- and multiamplitude signals transmitted over additive interference channels, such as cochannel interference (CCI) and adjacent channel interference (ACI). In particular, we propose, analyze, and evaluate a training algorithm for Ngquist-filtered single- and multiamplitude signals, based upon a novel nonuniform signal-sampling technique. We also introduce a novel nonlinear activation function for multiamplitude signals and evaluate its performance via computer simulation and in conjunction with various bandlimited signaling formats, detection techniques, and neural-network structures. Bit-error rate (BER) performance-evaluation results of the proposed neural-network receivers for coherent and noncoherent detection of Nyquist- and Butterworth-filtered single- and multiamplitude signals have shown performance improvements in the presence of CCI and ACI.

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