Finite Blocklength Analysis of Gaussian Random Coding in AWGN Channels under Covert Constraint

TL;DR

This paper analyzes the limits of Gaussian random coding in AWGN channels under covert constraints at finite blocklengths, providing new bounds and comparisons relevant for covert communication.

Contribution

It introduces more general achievability bounds for Gaussian random coding under covert constraints, extending previous results and comparing them with deterministic codebook bounds.

Findings

New achievability bounds for Gaussian random coding under covert constraints

Comparison showing advantages of random coding bounds over deterministic codebooks

Enhanced understanding of finite blocklength performance in covert AWGN communication

Abstract

This paper considers the achievability and converse bounds on the maximal channel coding rate at a given blocklength and error probability over AWGN channels. The problem stems from covert communication with Gaussian codewords. By re-visiting [18], we first present new and more general achievability bounds for random coding schemes under maximal or average probability of error requirements. Such general bounds are then applied to covert communication in AWGN channels where codewords are generated from Gaussian distribution while meeting the maximal power constraint. Further comparison is made between the new achievability bounds and existing one with deterministic codebooks.