Cognitive UAV-Aided URLLC and mMTC Services: Analyzing Energy Efficiency and Latency

The integration of unmanned aerial vehicles (UAVs) into spectrum sensing cognitive communication networks can offer many benefits for massive connectivity services in 5G communications and beyond; hence, this work analyses the performance non-orthogonal multiple access-based UAV-assisted ultra-reliable low-latency (URLLCs) machine-type (mMTC) services. An mMTC service requires better energy efficiency connection probability, whereas a URLLC minimising latency. In particular, UAV operates as an secondary transmitter to ground base station by sharing unlicensed wireless spectrum. To address these issues, we derive analytical expressions throughput, efficiency, latency mMTC/URLLC-UAV device. We also formulate optimisation problem maximisation satisfy needs throughput solve it using Lagrangian method Karush-Kuhn-Tucker conditions. algorithm is presented jointly optimising transmission powers users. derived are then used evaluate proposed system model. numerical results show that improves satisfies requirement