Near-optimal Sampling to Optimize Communication Over Discrete Memoryless Channels
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Author/Creator ORCID
Date
2023-04-10
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Citation of Original Publication
M. A. Tope and J. M. Morris, "Near-optimal Sampling to Optimize Communication Over Discrete Memoryless Channels," 2023 57th Annual Conference on Information Sciences and Systems (CISS), Baltimore, MD, USA, 2023, pp. 1-6, doi: 10.1109/CISS56502.2023.10089651.
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Subjects
Abstract
This paper develops a strategy to minimize the
number of channel probes required to recover the components
of the channel law and maximize the reliable communication
rate across a discrete memoryless channel (DMC). Based on
the aggregate set of observed input-output pairs over time, the
algorithm sequentially probes subsets of channel input values. We
leverage a non-asymptotic probably approximately correct (PAC)
bounds to establish the rate of convergence towards channel
capacity as O(√log(log(N)) log(N)/N), where N is the number
of channel probes. For a discrete channel with |X| input values
and |Y| output values, the sampling strategy may reduce the
sample complexity by a factor of nearly min (|X|/|Y|,1) relative
to previous methods.