Optimizing spectrum and energy efficiency in IRS-enabled UAV-ground communications

As an essential prospective technology to fulfill the 6G ubiquitous connectivity, unmanned aerial vehicle (UAV) has seen extensive adoption to provide demanding services in a variety of emergency rescue scenes and non-terrestrial network contexts. Due to the complex radio wave propagation environment and the on-board energy anxiety, high-performance and energy-efficient UAV-ground transmission has become a challenging issue to be addressed. While many research efforts have been dedicated to intelligent reflecting surface (IRS) enabled UAV-ground communications, where the IRS is leveraged to adaptively adjust the electromagnetic characteristics of arrived signals to enhance the communication quality, the channel model considered is not consistent with the actual scenario. Besides, the dynamic trajectory for achievable data rate enhancement may not always be energy-efficient. Motivated by this, we consider both spectrum efficiency maximization and energy efficiency maximization for UAV-ground communications in the urban region with no direct line-of-sight transmission through designing the phase shift, user scheduling, and dynamic trajectory. To solve the two maximization problems, we propose the three-stage alternating optimization framework to find the corresponding optimal solutions via a series of mathematical derivation transformations. Finally, numerical results confirm the effectiveness of our proposal in improving spectrum and energy efficiency compared to other benchmarks.