Joint Visual Coverage and Energy Consumption Optimization for UAV-Aided 5G-and-Beyond Communications

With the rapid advancement in cellular technologies, integrating unmanned aerial vehicles (UAVs) into 5G and beyond becomes a promising solution to enabling UAV-related services, which poses a pressing need for ubiquitous wireless coverage and effective onboard energy management. Joint optimization of coverage and energy, however, remains understudied, especially in the scenario of 5G and beyond, i.e., extended wireless coverage with limited onboard energy. In this article, we propose a novel approach to optimizing the configuration of a team of UAVs to cover an arbitrary 3-D surface, including their transmit power, 3-D locations, and number. Here, the discussed problem is formu- lated as a multiobjective optimization problem (MOP), whose goal is to simultaneously maximize visual coverage (VC) and minimize energy consumption (EC). To optimally solve this MOP, we analy- tically derive the closed-form expression of VC and maximize VC by jointly optimizing the transmit power and 3-D location of a UAV. The transmit power and 3-D location of a UAV are further updated by minimizing the EC arising from aerial movement and wireless transmission. Given the optimized VC and EC of an indi- vidual UAV, the optimal number of UAVs is obtained by finding the best tradeoff between minimum VC and total EC, subject to a given set of constraints on transmit power, signal-to-interference- plus-noise ratios, outage probabilities, sensing distances, and onb- oard energy. Simulation results validate the effectiveness of the proposed approach, revealing that energy efficiency (EE) remains high with an extended coverage area.