LAUSR

The proliferation of unmanned aerial vehicles (UAV), i.e., drones, in communication systems has recently attracted both industry and academia. This is mainly due to their flexible capabilities and features, which can support a wide range of communication applications. More specifically, drones can offer better coverage, better capacity, and a many-fold quality-of-service enhancement. Accordingly, recent communication technologies have been integrated with drones to support the unprecedented communication requirements of beyond fifth-generation (B5G) and 6G networks. Upon these bases, this paper sought to investigate the potential capabilities of multi-antenna drones in an uplink transmission cognitive radio (CR) indoor environment. With such an integrated system, a set of multiple-antenna drones communicates with a CR BS through the opportunistic utilization of the available channels without affecting the primary user’s activities. In particular, this paper proposes an adaptive power channel assignment (APCA) protocol that aims to minimize the per-drone transmit power under a set of relevant CR-related and quality-of-service constraints. The constraints include the minimum rate requirements, the probability of success, per-antenna power, the minimum SNR, and relevant CR-related constraints. Furthermore, this paper attempts to mathematically prove that the formulated optimization problem is convex, thus, the optimal solution can be attained. Accordingly, the conventional convex algorithms are adopted to solve the problem and obtain the solution. The proposed APCA protocol is capable of selecting the channel that requires the minimum power. To investigate the performance of the proposed APCA protocol, we compare its performance against that of the conventional equal-power allocation. Simulation results reveal that the proposed APCA protocol significantly improves system performance in terms of the overall transmit power.