{"ID":2880544,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.13555","arxiv_id":"2508.13555","title":"Resource Allocation for Positive-Rate Covert Communications Using Optimization and Deep Reinforcement Learning","abstract":"We aim to achieve keyless covert communication with a positive-rate in Rayleigh block-fading channels. Specifically, the transmitter and the legitimate receiver are assumed to have either causal or non-causal knowledge of the \\ac{CSI} for both the legitimate and the warden channels, while the warden only knows the statistical distribution of the \\ac{CSI}. Two problem formulations are considered in this work: (a) Power allocation: maximizing the sum covert rate subject to a maximum power constraint, and (b) Rate allocation: minimizing the power consumption subject to a minimum covert rate constraint. Both problems are formulated based on recent information theoretical results on covert communication over state-dependent channels. When the \\ac{CSI} of each fading block is known non-causally, we propose a novel three-step method to solve both the power and rate allocation problems. In the case where the \\ac{CSI} is known causally, the power allocation problem can be formulated as \\ac{MDP} and be solved using a \\ac{DDQN} approach. Although the rate allocation problem under causal \\ac{CSI} does not directly conform to an \\ac{MDP} structure, it can be approximately solved using the \\ac{DDQN} trained for power allocation. Simulation results demonstrate the effectiveness of the proposed power and rate allocation methods and provide comprehensive performance comparisons across different allocation schemes.","short_abstract":"We aim to achieve keyless covert communication with a positive-rate in Rayleigh block-fading channels. Specifically, the transmitter and the legitimate receiver are assumed to have either causal or non-causal knowledge of the \\ac{CSI} for both the legitimate and the warden channels, while the warden only knows the stat...","url_abs":"https://arxiv.org/abs/2508.13555","url_pdf":"https://arxiv.org/pdf/2508.13555v2","authors":"[\"Yubo Zhang\",\"Hassan ZivariFard\",\"Xiaodong Wang\"]","published":"2025-08-19T06:25:36Z","proceeding":"cs.IT","tasks":"[\"cs.IT\",\"eess.SP\"]","methods":"[\"Reinforcement Learning\"]","has_code":false}