Adaptive Security Solutions for NOMA Networks: The Role of DDPG and RIS-Equipped UAVs
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Abstract
In this work, we apply the Deep Deterministic Policy Gradient (DDPG) technique to improve the security of a non-orthogonal multiple access (NOMA) downlink network by enabling use of a reconfigurable intelligent surface (RIS) equipped unmanned aerial vehicles (UAV). Our main objective is to prevent eavesdroppers from accessing the network while preserving seamless communication for authorized users. The system is made up of a UAV integrated with an RIS which is essential for optimizing signal paths, and a Base Station. Our work aims to maximize secrecy rates for all users under possible eavesdropping scenarios by dynamically adjusting the RIS’s phase shifts and power allocations. This method not only shows how flexible and successful the DDPG algorithm is at protecting wireless communications when used in conjunction with an RIS but it also highlights how much the algorithm has advanced secure communication systems.
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