UAV Assisted NOMA System in Data Collection Wireless Sensor Network

The 5G cellular network introduces significant advancements in communication systems, especially in support of the rapidly expanding Internet of Things (IoT). Among emerging technologies, Unmanned Aerial Vehicles (UAVs) have become highly effective for data collection and delivery in IoTbased Wireless Sensor Networks (WSNs), thanks to their flexibility and mobility. However, this development demands communication techniques with higher spectral efficiency. NonOrthogonal Multiple Access (NOMA) is a promising solution, enabling higher sum rates and massive device connectivity-key requirements in 5 G networks. Integrating NOMA into UAVassisted WSNs holds great potential but poses challenges, particularly in user grouping and power allocation due to UAV mobility. This research proposes a UAV-assisted WSN communication system using NOMA to improve performance through effective sensor grouping, UAV positioning, and power control strategies. The initial phase involves designing a WSN and implementing a UAV data collection route using a Genetic Algorithm. NOMA is then integrated and evaluated via simulations focusing on system sum rate. Performance comparisons between NOMA and Orthogonal Multiple Access (OMA) systems will be conducted to analyze efficiency gains. This study aims to enhance WSN communication reliability and efficiency, supporting its real-world implementation in various IoT applications.