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Resource Allocation for Positive-Rate Covert Communications Using Optimization and Deep Reinforcement Learning

Yubo Zhang, Hassan ZivariFard, Xiaodong Wang

TL;DR

A novel three-step method to solve both the power and rate allocation problems in Rayleigh block-fading channels and provides comprehensive performance comparisons across different allocation schemes.

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.

Resource Allocation for Positive-Rate Covert Communications Using Optimization and Deep Reinforcement Learning

TL;DR

A novel three-step method to solve both the power and rate allocation problems in Rayleigh block-fading channels and provides comprehensive performance comparisons across different allocation schemes.

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.

Paper Structure

This paper contains 30 sections, 63 equations, 7 figures, 1 algorithm.

Figures (7)

  • Figure 1: Covert communication over DMC.
  • Figure 2: Sum covert rates under non-causal power allocation schemes.
  • Figure 3: Feasibility probabilities of non-causal rate allocation schemes.
  • Figure 4: Power consumptions under non-causal rate allocation schemes when they are all feasible.
  • Figure 5: Sum covert rates under causal power allocation schemes.
  • ...and 2 more figures