Energy Minimization for IRS-assisted UAV-empowered Wireless Communications

Abstract

Non-terrestrial wireless communications have evolved into a technology enabler for seamless connectivity and ubiquitous computing services in the beyond fifth-generation (B5G) and sixth-generation (6G) networks, aiming to provision reliable and energy efficient communications among aerial platforms and ground mobile users. This paper considers intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV)-empowered wireless communication, which exploits both the high mobility of UAV and passive beamforming gain brought by IRS. The energy minimization of rotary-wing UAV is formulated by jointly considering numerous quality of service (QoS) constraints with intricately coupled variables. To tackle the formulated challenging problem, a heuristic algorithm is proposed. First, we decouple it into several subproblems. Moreover, we jointly investigate offloading decisions of Internet of Thing (IoT) devices by the proposed enhanced differential evolution algorithm. Then, minorization-maximization algorithm (MMA) is utilized to solve the optimization of IRS phase shift-vector. Moreover, ant colony optimization (ACO) algorithm is proposed to optimize UAV flight route indicator matrix. Numerical results validate the effectiveness of the proposed algorithm. The results show that the proposed solution can remarkably decrease UAV flight distance while improving the network energy efficiency in comparison with numerous advanced algorithms.