2000 character limit reached
Enhancing Secrecy in UAV RSMA Networks: Deep Unfolding Meets Deep Reinforcement Learning (2310.01437v1)
Published 30 Sep 2023 in cs.CR, cs.ET, cs.NI, and eess.SP
Abstract: In this paper, we consider the maximization of the secrecy rate in multiple unmanned aerial vehicles (UAV) rate-splitting multiple access (RSMA) network. A joint beamforming, rate allocation, and UAV trajectory optimization problem is formulated which is nonconvex. Hence, the problem is transformed into a Markov decision problem and a novel multiagent deep reinforcement learning (DRL) framework is designed. The proposed framework (named DUN-DRL) combines deep unfolding to design beamforming and rate allocation, data-driven to design the UAV trajectory, and deep deterministic policy gradient (DDPG) for the learning procedure. The proposed DUN-DRL have shown great performance and outperformed other DRL-based methods in the literature.
- Y. Mao, O. Dizdar, B. Clerckx, R. Schober, P. Popovski, and H. V. Poor, “Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends,” IEEE Communications Surveys & Tutorials, vol. 24, no. 4, pp. 2073-2126, 2022.
- S. K. Singh, K. Agrawal, K. Singh, and C. P. Li, “Ergodic Capacity and Placement Optimization for RSMA-Enabled UAV-Assisted Communication,” IEEE Systems Journal, vol. 17, no. 2, pp. 2586-2589, 2023.
- A. H. A. El-Malek, M. A. Aboulhassan, A. M. Salhab, and S. A. Zummo, “Performance Analysis and Optimization of UAV-Assisted Networks: Single UAV With Multiple Antennas Versus Multiple UAVs With Single Antenna,” IEEE Systems Journal, pp. 1-12, 2023.
- X. Zhou, S. Yan, J. Hu, J. Sun, J. Li, and F. Shu, “Joint Optimization of a UAV’s Trajectory and Transmit Power for Covert Communications,” IEEE Transactions on Signal Processing, vol. 67, no. 16, pp. 4276-4290, 2019.
- Y. Luo, “Analysis and Research of Network Information Security Evaluation Model Based on Machine Learning Algorithm,” The 4th Eurasia Conference on IOT, Communication and Engineering (ECICE), 2022, pp. 193-196.
- A. B. M. Adam, L. Lei, S. Chatzinotas, and N. U. R. Junejo, “Deep Convolutional Self-Attention Network for Energy-Efficient Power Control in NOMA Networks,” IEEE Transactions on Vehicular Technology, vol. 71, no. 5, pp. 5540-5545, 2022.
- A. B. M. Adam, Z. Wang, X. Wan, Y. Xu, and B. Duo, “Energy-Efficient Power Allocation in Downlink Multi-Cell Multi-Carrier NOMA: Special Deep Neural Network Framework,” IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 4, pp. 1770-1783, 2022.
- R. Liu, R. Y. Li, M. D. Renzo, L. Hanzo, “A Vision and An Evolutionary Framework for 6G: Scenarios, Capabilities and Enablers,” https://arxiv.org/abs/2305.13887v3, https://doi.org/10.48550/arXiv.2305.13887.
- K. Guo, M. Wu, X. Li, H. Song, and N. Kumar, “Deep Reinforcement Learning and NOMA-Based Multi-Objective RIS-Assisted IS-UAV-TNs: Trajectory Optimization and Beamforming Design,” IEEE Transactions on Intelligent Transportation Systems, pp. 1-14, 2023.
- Y. Zhang, Z. Mou, F. Gao, L. Xing, J. Jiang, and Z. Han, “Hierarchical Deep Reinforcement Learning for Backscattering Data Collection With Multiple UAVs,” IEEE Internet of Things Journal, vol. 8, no. 5, pp. 3786-3800, 2021.
- A. B. M. Adam, X. Wan, M. A. M. Elhassan, M. S. A. Muthanna, A. Muthanna, N. Kumar, and M. Guizani, “Intelligent and Robust UAV-Aided Multiuser RIS Communication Technique With Jittering UAV and Imperfect Hardware Constraints,” IEEE Transactions on Vehicular Technology, vol. 72, no. 8, pp. 10737-10753, 2023.
- G. Xiong, T. Kim, D. J. Love, and E. Perrins, “Optimality Conditions of Performance-Guaranteed Power Minimization in MIMO Networks: A Distributed Algorithm and Its Feasibility,” IEEE Transactions on Signal Processing, vol. 69, pp. 119-135, 2021.
- N. Mumladze, “Solving eigenproblems with Neural Networks.” https://mediatum.ub.tum.de/doc/1632870/kwm0n4od0og42tg17pewgnx5s.pdf (accessed June 20 2023).
- X. Guo, Y. Chen, and Y. Wang, “Learning-Based Robust and Secure Transmission for Reconfigurable Intelligent Surface Aided Millimeter Wave UAV Communications,” IEEE Wireless Communications Letters, vol. 10, no. 8, pp. 1795-1799, 2021.
- B. Matthiesen, Y. Mao, A. Dekorsy, P. Popovski, and B. Clerckx, “Globally Optimal Spectrum- and Energy-Efficient Beamforming for Rate Splitting Multiple Access,” IEEE Transactions on Signal Processing, vol. 70, pp. 5025-5040, 2022.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.