One-shot achievability and converse bounds of Gaussian random coding in AWGN channels under covert constraint

The achievability and converse bounds on the throughput of covert communication over AWGN channels are investigated in this paper. By re-visiting [8], several new achievability bounds on maximal and average probability of error based on random coding scheme are presented, which leads to results on achievability bounds when the codewords are generated from Gaussian distribution and then selected from a subset under maximal power constraint. The bounds provide us the framework for analyzing the maximal throughput under covert constraint of total variation distance