Optimized Power Allocation Algorithms for UAV-Based Agricultural Systems

Agriculture 5.0 is an emerging concept that builds on the integration of cutting-edge technologies to create smarter, more sustainable, and efficient farming systems. Integrating Unmanned Aerial Vehicles (UAVs) is a key enabler of precision agriculture, allowing real-time data collection, analysis, and decision-making to boost farming practices. UAVs provide a crucial function in this ecosystem, contributing to achieving Sustainable Development Goals (SDGs). Nevertheless, these vehicles encounter significant computing power, throughput, real-time delay, and battery capacity challenges. Addressing these challenges requires innovations in network design, power management, and communication technologies. To this end, we propose to deploy 6G’s Massive MIMO (Multiple Input Multiple Output) technology within a three-layered architecture for UAV-based smart agricultural systems. Our study focuses on the power allocation problem in both downlink and uplink transmissions, aiming to maximize throughput while ensuring fairness among different terminals. To achieve this, we deploy a downlink fairness-based algorithm (DFA) and a downlink hybrid algorithm (DHA). The first approach ensures fairness by optimizing the throughput of the weakest IoT terminal in the network, while the second approach balances throughput and fairness among IoT terminals. Additionally, we employ an uplink heuristic power control algorithm (UHPCA) to determine the optimal power allocation. The numerical results indicate that the proposed allocation algorithms achieve a better trade-off between throughput and fairness compared to conventional power allocation strategies in the literature.