Joint Optimization of Secrecy Rate and Energy Consumption for RSMA in SAGIN via MADRL

초록

Space-air-ground integrated networks (SAGIN) have gained significant attention as a key solution to address the challenges of limited spectrum resources and unstable user accessibility caused by the growing number of connected devices. However, the extensive coverage and multi-layered structure of SAGIN make it vulnerable to wiretapping that can compromise data integrity and pose significant challenges in managing energy consumption across all communication layers. To address these security challenges, this study explores an uplink physical layer security (PLS) within the rate-splitting multiple access (RSMA) framework for SAGIN. A joint optimization problem of secrecy rate and energy consumption subject to security and power constraints is formulated. To address this problem, we propose multi-agent deep reinforcement learning based algorithms, multi-agent twin delayed deep deterministic policy gradient (MATD3) and multi-agent deep Q-learning (MADQL). These algorithms aim to maximize a reward function which is designed based on the optimization model's objective, by controlling the transmit power of RSMA sub-signals and user-receiver associations. In addition, we employ fixed and adaptive penalty mechanisms in the proposed MATD3 and MADQL algorithms to avoid excessive restriction on exploration and instability during training. Extensive simulation results demonstrate that the proposed RSMA-MATD3 outperform existing multiple access schemes, including non-orthogonal multiple access (NOMA) and frequency division multiple access (FDMA), by achieving improved secrecy rates while maintaining similar energy consumption across various comparable metrics such as maximum transmit power constraint and number of user equipment (UE). Additionally, it is verified for both MATD3 and MADQL that the proposed adaptive penalty within the reward function enables higher secrecy rates at lower transmit power, while the fixed penalty achieves similar performance at higher transmit power.

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