Finite Blocklength Covert Communications in Interweave Cognitive Radio Networks
Rui Xu, Daoxing Guo, Bangning Zhang, Guoru Ding
Abstract
This letter investigates finite blocklength covert communications in interweave cognitive wireless networks. Based on our current knowledge, this letter formulates an analytical model of interweave finite blocklength covert communications for the first time. First, under the condition that each channel use in a block satisfyies the independent and non-identical distribution, we derive the KL divergence between two distributions corresponding to null hypothesis <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\cal H_{0}}$ </tex-math></inline-formula> and alternative hypothesis <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\cal H_{1}}$ </tex-math></inline-formula> , and obtain the KL divergence in the considered scenario. Then, we formulate an optimization problem to maximize effective throughput and obtain the optimal transmit power and transmission blocklength, revealing the tradeoff between covert transmission and sensing. In contrast to many existing results, our examination shows that the optimal transmission blocklength is not the maximum, which is optimal in the finite blocklength covert communications system.