Efficient Near-Optimal Codes for General Repeat Channels
Francisco Pernice, Ray Li, Mary Wootters

TL;DR
This paper develops explicit, efficient coding schemes for a broad class of repeat channels, achieving near-capacity rates with linear or quasi-linear encoding and decoding times, and introduces a novel 'approximate balance' property for codewords.
Contribution
It constructs near-capacity codes for all square-integrable repeat channels with efficient encoding and decoding, extending previous work and introducing a new 'approximate balance' technique.
Findings
Codes achieve rates arbitrarily close to channel capacity.
Encoding and decoding are linear or quasi-linear in time.
The 'approximate balance' property is of independent interest.
Abstract
Given a probability distribution over the non-negative integers, a -repeat channel acts on an input symbol by repeating it a number of times distributed as . For example, the binary deletion channel () and the Poisson repeat channel () are special cases. We say a -repeat channel is square-integrable if has finite first and second moments. In this paper, we construct explicit codes for all square-integrable -repeat channels with rate arbitrarily close to the capacity, that are encodable and decodable in linear and quasi-linear time, respectively. We also consider possible extensions to the repeat channel model, and illustrate how our construction can be extended to an even broader class of channels capturing insertions, deletions, and substitutions. Our work…
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Taxonomy
TopicsAdvanced biosensing and bioanalysis techniques · DNA and Biological Computing · Quantum-Dot Cellular Automata
