Trellis-coded modulation with multidimensional constellations
IEEE Transactions on Information Theory
Detection of signals in correlated interference using a predictive VA
ICCS '02 Proceedings of the The 8th International Conference on Communication Systems - Volume 01
Coding for intersymbol interference channels-combined coding and precoding
IEEE Transactions on Information Theory
The intersymbol interference channel: lower bounds on capacity and channel precoding loss
IEEE Transactions on Information Theory
Calculation of shell frequency distributions obtained with shell-mapping schemes
IEEE Transactions on Information Theory
The V.34 high speed modem standard
IEEE Communications Magazine
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In this paper, we address the problem of optimally detecting signals in correlated noise using a predictive Viterbi algorithm (PVA). We derive expressions for the probability of error for both coded and uncoded systems employing the PVA, which are corrupted by coloured noise. As an application, the PVA is used in conjunction with a fractionally spaced linear equalizer (LE-PVA), thereby improving the bit-error-rate performance by as much as 11 dB, over the conventional decision feedback equalizer with estimated decisions, when the channel has spectral nulls. The LE-PVA is also about 1 dB better than the DFE that uses per-survivor processing. Simulation results also show that the performance difference between the LE-PVA and the decision feedback equalizer with correct decisions fed back (ideal DFE), is just 1 dB, even when the channel has spectral nulls. Simulation results are also presented for multipath fading channels, where we again demonstrate that the LE-PVA is just 1 dB inferior to the ideal DFE and about 1 dB better than the DFE using per-survivor processing. Thus, we clearly demonstrate the superiority of the LE-PVA over a practical DFE.