Optimal Routing and Link Configuration for Covert Heterogeneous Wireless Networks

TL;DR

This paper develops polynomial-time algorithms for optimal routing and link configuration in covert heterogeneous wireless networks with multiple interfaces, considering adversaries and channel uncertainties.

Contribution

It introduces the first polynomial-time algorithms for optimal route and link configuration in covert multi-interface wireless networks, including extensions for multiple adversaries and uncertain channel states.

Findings

Heterogeneous radio resources significantly improve covert communication capacity.

The proposed algorithms outperform alternative methods in numerical simulations.

Optimal configurations effectively balance covertness and network performance.

Abstract

Nodes in contemporary radio networks often have multiple interfaces available for communication: WiFi, cellular, LoRa, Zigbee, etc. This motivates understanding both link and network configuration when multiple communication modalities with vastly different capabilities are available to each node. In conjunction, covertness or the hiding of radio communications is often a significant concern in both commercial and military wireless networks. We consider the optimal routing problem in wireless networks when nodes have multiple interfaces available and intend to hide the presence of the transmission from attentive and capable adversaries. We first consider the maximization of the route capacity given an end-to-end covertness constraint against a single adversary and we find a polynomial-time algorithm for optimal route selection and link configuration. We further provide optimal polynomial-time algorithms for two important extensions: (i) statistical uncertainty during optimization about the channel state information for channels from system nodes to the adversary; and, (ii) maintaining covertness against multiple adversaries. Numerical results are included to demonstrate the gains of employing heterogeneous radio resources and to compare the performance of the proposed approach versus alternatives.