An Innovative Method for Improving the Performance of UAV‐SM‐NOMA for 6G Networks Over Generalized Fading Channels

ABSTRACT The emergence of 6G wireless communications has brought numerous challenges and opportunities for meeting the growing demands of enhanced system capacity, higher data rates, lower latency, improved security, and stringent quality of service (QoS) requirements. One promising solution to tackle these challenges involves utilizing unmanned aerial vehicles (UAVs) in conjunction with nonorthogonal multiple access (NOMA) and spatial modulation (SM). However, optimizing the performance of UAV‐based SM‐NOMA systems for both perfect and imperfect channel state information (CSI) over generalized fading channels ( α – μ , k – μ and η – μ ) while simultaneously considering multiple objectives is a complex task. To address these challenges, this paper proposes integrating the monarch butterfly optimization algorithm (MBOA) into UAV‐SM‐NOMA systems for 6G networks. Inspired by the foraging behavior of monarch butterflies, the MBOA aims to enhance UAV‐based SM‐NOMA systems' performance by optimizing resource allocation, increasing system sum rate, reducing outage probability (OP) and bit error rate (BER), improving spectrum efficiency (SE), and ensuring desirable signal‐to‐interference‐plus‐noise ratio (SINR) levels. Key findings include that the MBOA effectively improves performance metrics across generalized fading channels compared to existing UAV‐assisted NOMA and orthogonal multiple access (OMA) models. Simulation results confirm that the proposed UAV‐assisted SM‐NOMA model with MBOA significantly outperforms conventional approaches, demonstrating superior capacity, reliability, and efficiency in 6G network scenarios.