Principles of Digital Communication and Coding
Principles of Digital Communication and Coding
Information Theory and Reliable Communication
Information Theory and Reliable Communication
Convex Optimization
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
A robust metric for soft-output detection in the presence of class-a noise
IEEE Transactions on Communications
Fundamental performance limits of communications systems impaired by impulse noise
IEEE Transactions on Communications
On reliable communications over channels impaired by bursty impulse noise
IEEE Transactions on Communications
Robust multiuser detection in non-Gaussian channels
IEEE Transactions on Signal Processing
An adaptive spatial diversity receiver for non-Gaussianinterference and noise
IEEE Transactions on Signal Processing
Analysis of Narrowband Communication Systems Impaired by MB-OFDM UWB Interference
IEEE Transactions on Wireless Communications
Joint Erasure Marking and Viterbi Decoding Algorithm for Unknown Impulsive Noise Channels
IEEE Transactions on Wireless Communications
Coded diversity on block-fading channels
IEEE Transactions on Information Theory
Analysis of low-density parity-check codes for the Gilbert-Elliott channel
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
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It has been widely acknowledged that the aggregate interference at the receiver for various practical communication channels can often deviate markedly from the classical additive white Gaussian noise (AWGN) assumption due to various ambient phenomena. Moreover, the physical nature of the underlying interference generating process in such cases can lead to a bursty behaviour of the interfering signal, implying that it is highly likely that consecutive symbols are affected by similar noise levels. In this paper, we devise and analyze detection techniques, in conjunction with a convolution code, for such interference channels that possess non-negligible memory by considering optimum and sub-optimum decoding metrics. In particular the inherent memory in the noise process is modeled as a firstorder Markov chain, whose state selects the variance of the instantaneous Gaussian noise, leading to a Markov-Gaussian channel model. Analytical expressions are obtained for the cutoff rate, which is an ensemble code parameter, and the bit error rate for a convolutionally coded system, that are subsequently employed for an extensive evaluation of the various metrics considered. Furthermore, the interleaving depth is considered as a design parameter and its effect on performance is analyzed over a range of noise scenarios.