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

• Published in: Results in engineering Vol. 23; p. 102740
• Main Authors: A, Nivetha, K S, Preetha
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-09-2024; Elsevier
• Subjects: Cybertwin; Non-orthogonal multiple access; Optimization; Power allocation; Secrecy capacity analysis; Cybertwin; Non-orthogonal multiple access; Secrecy capacity analysis; Power allocation; Optimization
• ISSN: 2590-1230; 2590-1230
• DOI: 10.1016/j.rineng.2024.102740

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.
•The sixth-generation (6G) communication network has high data density and is powered by an Internet of Everything (IoE), it is anticipated to have use cases across multiple areas namely smart cities, healthcare, Smart transportation, and agriculture.•The proposed methodology introduces bio-meta-heuristic optimization algorithms, specifically Grey Wolf Optimization and hybrid Grey Wolf Optimization with Krill Herd Optimization for NOMA power allocation.•The secrecy capacity analysis and throughput analysis were demonstrated for secure data transmission between a Cyber twin host and server, evaluating the system's ability to transmit information securely while minimizing the risk of eavesdropping or unauthorized access.•The methodology employs power domain multiplexing in NOMA, utilizing varying power levels based on individual users' channel conditions to maximize system capacity.•Simulation results comparison is done for simple NOMA power allocation, hybrid GWO-NOMA, and hybrid GWO-KWO-based NOMA. The analysis demonstrates superior efficiency in hybrid GWO-KWO-based power allocation.