Meta-algorithmic optimized power allocation in cybertwin-based sixth generation cooperative communication system

Abstract

The sixth-generation (6G) communication paradigm, powered by an Internet of Everything (IoE), promises unprecedented data density and transformative applications across various sectors like smart cities, healthcare, transportation, and agriculture. This study explores an emerging hybrid cybertwin-enabled 6G cooperative network architecture, focusing on secrecy capacity analysis. The approach involves Base Stations (BS) employing Non-Orthogonal Multiple Access (NOMA) techniques to transmit data to cybertwin hosts and servers via direct wireless links with Nakagami-m fading. Additionally, a Power Line Communication (PLC) link, subjected to Rayleigh fading, supplements the wireless link for communication between cybertwin hosts and servers. Bio-meta-heuristic optimization algorithms are introduced to optimize NOMA power allocation, specifically Grey Wolf Optimization (GWO) and a hybrid of Grey Wolf Optimization with Krill Herd Optimization (KHO). The system's capability to ensure secure data transmission while mitigating eavesdropping risks is assessed through thorough secrecy capacity and throughput analyses. Simulation results highlight the efficacy of the hybrid GWO-KHO-based NOMA power allocation scheme, showcasing superior efficiency over traditional methods. This study contributes novel insights into optimized power allocation and efficiency in cybertwin-enabled 6G networks, underscoring the significance of hybrid optimization approaches in future communication systems.