Optimal Routing and Link Configuration for Covert Heterogeneous Wireless Networks
🤖 AI Summary
In multi-modal wireless networks (WiFi/LoRa/Cellular/Zigbee), covert communication faces challenges including multiple colluding eavesdroppers, uncertain channel-state statistics, and stringent full-covertness requirements. Method: This paper proposes a joint routing and multi-interface link configuration framework for covert communication. It introduces the first polynomial-time optimal algorithm that jointly optimizes coverage and covertness, integrating combinatorial optimization, covert communication modeling, and stochastic robust optimization to enable robust decision-making under multiple adversaries. Contribution/Results: The framework provides theoretical guarantees on maximizing end-to-end covert throughput while strictly bounding the adversary’s detection probability. Numerical experiments demonstrate a 2.3× improvement in covert throughput over single-modal baselines and sustain >98% detection-avoidance probability under multi-adversary settings.
Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Multi-Radio Communication
Stealth Connectivity
Multi-Adversary Environment
Innovation
Methods, ideas, or system contributions that make the work stand out.
Stealth Communication
Multi-Adversary Eavesdropping
Optimal Path Algorithm
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