Smoothing of binary codes, uniform distributions, and applications
Madhura Pathegama, Alexander Barg

TL;DR
This paper characterizes when noise acting on binary codes results in nearly uniform distributions, identifies explicit code families achieving this, and explores applications in secrecy and error correction.
Contribution
It provides explicit conditions and code constructions for asymptotic uniformity under noise, linking smoothing to security and error correction in information theory.
Findings
Explicit code families achieve asymptotic uniformity under Bernoulli noise.
Nested Reed-Muller codes guarantee strong secrecy in wiretap channels.
Connection established between smoothing and error correction in binary channels.
Abstract
The action of a noise operator on a code transforms it into a distribution on the respective space. Some common examples from information theory include Bernoulli noise acting on a code in the Hamming space and Gaussian noise acting on a lattice in the Euclidean space. We aim to characterize the cases when the output distribution is close to the uniform distribution on the space, as measured by R\'enyi divergence of order . A version of this question is known as the channel resolvability problem in information theory, and it has implications for security guarantees in wiretap channels, error correction, discrepancy, worst-to-average case complexity reductions, and many other problems. Our work quantifies the requirements for asymptotic uniformity (perfect smoothing) and identifies explicit code families that achieve it under the action of the Bernoulli and ball…
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Taxonomy
TopicsWireless Communication Security Techniques · Cooperative Communication and Network Coding · Cryptography and Data Security
