Information Rates of Channels With Additive White Cauchy Noise

Information transmission over discrete-time channels with memoryless additive noise obeying a Cauchy, rather than Gaussian, distribution, are studied. The channel input satisfies an average power constraint. Upper and lower bounds to such additive white Cauchy noise (AWCN) channel capacity are established. In the high input power regime, the gap between upper and lower bounds is within 0.5 nats per channel use, and the lower bound can be achieved with Gaussian input. In the lower input power regime, the capacity can be asymptotically approached by employing antipodal input. It is shown that the AWCN decoder can be applied to additive white Gaussian noise (AWGN) channels with negligible rate loss, while the AWGN decoder when applied to AWCN channels cannot ensure reliable decoding. For the vector receiver case, it is shown that a linear combining receiver front end loses the channel combining gain, a phenomenon drastically different from AWGN vector channels.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-11-20
DOI
https://doi.org/10.1109/lcomm.2024.3502753
Citations
1
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.35

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article

Information Rates of Channels With Additive White Cauchy Noise

Shuqin Pang, Wenyi Zhang
1 citations
IEEE Communications Letters
Quantum Computing Algorithms and Architecture
0.35
article

Information Rates of Channels With Additive White Cauchy Noise

Shuqin Pang, Wenyi Zhang
article en
1 citations

Abstract

Information transmission over discrete-time channels with memoryless additive noise obeying a Cauchy, rather than Gaussian, distribution, are studied. The channel input satisfies an average power constraint. Upper and lower bounds to such additive white Cauchy noise (AWCN) channel capacity are established. In the high input power regime, the gap between upper and lower bounds is within 0.5 nats per channel use, and the lower bound can be achieved with Gaussian input. In the lower input power regime, the capacity can be asymptotically approached by employing antipodal input. It is shown that the AWCN decoder can be applied to additive white Gaussian noise (AWGN) channels with negligible rate loss, while the AWGN decoder when applied to AWCN channels cannot ensure reliable decoding. For the vector receiver case, it is shown that a linear combining receiver front end loses the channel combining gain, a phenomenon drastically different from AWGN vector channels.

IEEE Communications LettersVol. 29(1)
University of Science and Technology of China (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 32%
Quantum Computing Algorithms and Architecture
0.35
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