نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار دانشکده مهندسی فناوری های نوین، دانشگاه تخصصی فناوریهای نوین آمل، آمل، ایران.
2 کارشناسی ارشد شبکه های مخابراتی، دانشکده مهندسی فناوری های نوین، دانشگاه تخصصی فناوری های نوین آمل، آمل، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
In the present era, given the rapid growth of communication technologies and the need for smart networks, novel techniques such as Power Line Communication (PLC) and Orthogonal Frequency Division Multiplexing (OFDM) have been introduced as effective solutions for improving data transmission security and reducing infrastructure costs. This paper examines communication systems based on power lines using Orthogonal Frequency Division Multiple Access (OFDMA) techniques, which play a crucial role in network management, with the aim of enhancing data transmission security and minimizing interference effects. To evaluate the proposed system model, an optimization problem is formulated and analyzed using mathematical optimization models and the NOMAD and CVX tools in MATLAB. The analysis focuses on key performance parameters, including the number of subcarriers and users, distance, data rate constraints, total power, and noise. Therefore, to analyze the proposed system model, comprehensively, we investigate the minimum required secrecy rate for users in the presence of eavesdroppers. The optimization results demonstrate a significant improvement in the performance of PLC-based communication systems and an increase in data transmission rates.
کلیدواژهها [English]
Yavari, M., & Akbari, A. H. (2023). Service level and profit maximisation in order acceptance and scheduling problem with weighted tardiness. International Journal of Industrial and Systems Engineering, 43(3), 331-362. https://doi.org/10.1504/IJISE.2023.129138
Akbari, A. H., & Jafari, M. (2025). Development of a Deep Reinforcement Learning Algorithm in a Dynamic Cellular Manufacturing System Considering Order Rejection, Case Study: Stone Paper Factory. Engineering Management and Soft Computing, 10(2), 204-222. doi: 10.22091/jemsc.2025.11853.1230
Jabbari, M., Rezaeenour, J., & Akbari, A. H. (2023). A Feature Selection Method Based on Information Theory and Genetic Algorithm. Sciences and Techniques of Information Management, 9(3), 32-7. doi: 10.22091/stim.2023.8708.1877
Tavakkoli-Moghaddam, R., Akbari, A. H., Tanhaeean, M., Moghdani, R., Gholian-Jouybari, F., & Hajiaghaei-Keshteli, M. (2024). Multi-objective boxing match algorithm for multi-objective optimization problems. Expert Systems with Applications, 239, 122394. https://doi.org/10.1016/j.eswa.2023.122394
Yavari, M., Marvi, M., & Akbari, A. H. (2020). Semi-permutation-based genetic algorithm for order acceptance and scheduling in two-stage assembly problem. Neural Computing and Applications, 32, 2989-3003. https://doi.org/10.1007/s00521-019-04027-w
Tanhaeean, M., Tavakkoli-Moghaddam, R., & Akbari, A. H. (2022). Boxing match algorithm: A new meta-heuristic algorithm. Soft Computing, 26(24), 13277-13299. https://doi.org/10.1007/s00500-022-07518-6
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