Joint energy-efficient resource allocation, subcarrier assignment, and SIC ordering for mmWave-enabled NOMA-UAV networks

Abstract

Recently, unmanned aerial vehicles (UAV) offer an effective approach to guarantee the quality of service, increase network throughput, and meet the demanding performance requirements of applications in integrated wireless networks. We presented an efficient radio resource management algorithm for mmWave-enabled NOMA-UAV networks that applies UAV-cells to guaranty the essential coverage and capacity. This paper introduced a joint carrier allocation and power optimisation approach to maximise the total downlink throughput. A matching algorithm is also introduced to achieve optimal carrier allocation, which first matches the user with the best carrier. Then the Dinkelbach-like algorithm is used to optimise resource allocation and meet users' QoS requirements. We examined the system energy efficiency and the total system data rate, along with other key performance indicators. Simulation results show that the proposed algorithm can achieve higher energy efficiency compared to the existing algorithms.