Secrecy-Aware Altitude Optimization for Quasi-Static UAV Base Station Without Eavesdropper Location Information

Abstract

In this letter, the altitude of an unmanned aerial vehicle base station (UAV-BS) is optimized to maximize an average worst case secrecy rate (AWSR) without eavesdropper location information. The air-to-ground channels are modeled based on the derived line-of-sight probability under a general urban model with Poisson point process and Rayleigh distribution for the locations and heights of the buildings, respectively. To solve the AWSR maximization problem, which is intractable, we reformulate it by the first-order Taylor series approximation and apply the Davies-Swann-Campey algorithm to effectively find the solution of the modified AWSR maximization problem. Numerical results verify that the altitude of UAV-BS affects the secrecy rate significantly and that the proposed UAV-BS can improve the secrecy rate compared with a static terrestrial BS.