This paper presents an explicit channel code design for covert communications in the Binary Symmetric Channel. The proposed architecture is composed of the serial concatenation of a linear code and a graph-based non-linear code baptized as moderate-density non-linear code. This non-linear code encompasses pulse position modulation as a particular case. In order to guarantee covertness, a scrambling sequence that is not known to the warden is employed.

This paper aims at computing tight upper bounds for the maximum a posteriori threshold of low-density parity check codes in the asymptotic blocklength regime for the transmission over binary-input memoryless symmetric-output channels. While these bounds are already known, we propose a novel derivation based on a completely different approach: based solely on the concept of the chain rule and the conditional entropy, resorting to the concentration theorem for the code ensemble to compute the syndrome entropy with low complexity employing density evolution.

This paper introduces a joint bit loading and power allocation algorithm for systems combining bit-interleaved coded modulation (BICM) with multicarrier transmission. The proposed algorithm maximizes the mutual information, so it can be regarded as a generalization of mercury/waterfilling policy that incorporates bit loading. The followed approach relies on irregular modulation and power to cast the problem in the framework of convex optimization. This allows to derive the optimum solution without resorting to greedy algorithms, embedding the bit loading in the definition of an equivalent constellation such that the complexity increase with respect to mercury/waterfilling is negligible. While irregular modulation plays a key role in algorithm definition, it is proved that only a few subcarriers employ it and it is shown that a practical low complexity algorithm can be obtained with minimal losses that does not use irregular modulation.

Waterfllling and mercury/waterfilling power allocation policies maximize the mutual information of independent parallel Gaussian-noise channels under an average power constraint for Gaussian signals and for practical discrete constellations respectively. In this paper, the same criterion is considered for joint power allocation and bit loading in more general scenarios where suboptimum receivers introduce a mutual information loss. The proposed approach provides the optimum solution without resorting to greedy algorithms and has nearly the same complexity as the original mercury/waterfilling.