Wu, M., Guo, K., Li, X., Lin, Z., Yang, L., Tsiftsis, T. A., & Yuen, C. (2025). RIS-Assisted SATINs With RSMA and DRL: A Trade-Off Between Spectral, Secrecy, and Energy Efficiency. IEEE Transactions on Communications, 73(11), 12380–12395. https://doi.org/10.1109/tcomm.2025.3573454
Abstract:
Given the rapid growth of diverse communication demands, future large-scale satellite-aerial-terrestrial integrated networks (SATINs) need to simultaneously provide services to users while guaranteeing spectral efficiency, secrecy and energy efficiency. This paper addresses the problem of maximising secrecy energy efficiency (SEE) in SATINs, which can accurately describe the effective trade-off between security, spectral efficiency and transmit power. Particularly, we investigate a secure beamforming (BF) scheme in cognitive SATINs that employs rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) in the presence of multiple eavesdroppers (Eves) in a AAV-aided secondary network (SN). To optimize the SEE for secondary vehicle users while satisfying the constraints of primary users (PUs), we utilize deep reinforcement learning (DRL) to address the coupling between different optimized parameters based on the improved long short-term memory proximal policy optimization (LSTM-PPO) algorithm. The main innovation of this paper is to design a sophisticated reward function, action space, and state space according to each constraint to speed up the convergence. In addition, simulation results show that the proposed DRL-based optimization scheme exhibits significant advantages in terms of SEE compared with benchmark schemes, validating the effectiveness of this work.
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Funding Info:
This research / project is supported by the National Science Foundation of China - NA
Grant Reference no. : 62001517
This research / project is supported by the National Science Foundation of China - NA
Grant Reference no. : 62201592, 62471477
This research / project is supported by the Southeast University, China - Open research fund of National Mobile Communications Research Laboratory
Grant Reference no. : 2024D15
This research / project is supported by the Agency for Science, Technology and Research, Singapore - Manufacturing, Trade, and Connectivity Programmatic
Grant Reference no. : M22L1b0110
This research / project is supported by the National Research Foundation, Singapore and Infocomm Media Development Authority, Singapore - Future Communications Research & Development Programme
Grant Reference no. : FCP-NTU-RG-2024-025