# Hybrid Hierarchical DRL Enabled Resource Allocation for Secure Transmission in Multi-IRS-Assisted Sensing-Enhanced Spectrum Sharing Networks

arXiv: https://arxiv.org/abs/2312.01071 · HTML: https://mlsanity.com/paper/2312.01071/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2023.

## Built on by (most cited first, 6 of 6)

- [Improve the Training Efficiency of DRL for Wireless Communication Resource Allocation: The Role of Generative Diffusion Models](https://mlsanity.com/paper/2502.07211/) (2025)
- [Trustworthy AI-Driven Dynamic Hybrid RIS: Joint Optimization and Reward Poisoning-Resilient Control in Cognitive MISO Networks](https://mlsanity.com/paper/2604.01238/) (2026)
- [A Hierarchical DRL Approach for Resource Optimization in Multi-RIS Multi-Operator Networks](https://mlsanity.com/paper/2410.12320/) (2024)
- [IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocation](https://mlsanity.com/paper/2411.01821/) (2024)
- [DRL-Based Resource Allocation for Energy-Efficient IRS-Assisted UAV Spectrum Sharing Systems](https://mlsanity.com/paper/2510.17877/) (2025)
- [When Critics Disagree: Adaptive Reward Poisoning Attacks in RIS-Aided Wireless Control System](https://mlsanity.com/paper/2605.20037/) (2026)

## Abstract (arXiv)

Secure communications are of paramount importance in spectrum sharing networks due to the allocation and sharing characteristics of spectrum resources. To further explore the potential of intelligent reflective surfaces (IRSs) in enhancing spectrum sharing and secure transmission performance, a multiple intelligent reflection surface (multi-IRS)-assisted sensing-enhanced wideband spectrum sharing network is investigated by considering physical layer security techniques. An intelligent resource allocation scheme based on double deep Q networks (D3QN) algorithm and soft Actor-Critic (SAC) algorithm is proposed to maximize the secure transmission rate of the secondary network by jointly optimizing IRS pairings, subchannel assignment, transmit beamforming of the secondary base station, reflection coefficients of IRSs and the sensing time. To tackle the sparse reward problem caused by a significant amount of reflection elements of multiple IRSs, the method of hierarchical reinforcement learning is exploited. An alternative optimization (AO)-based conventional mathematical scheme is introduced to verify the computational complexity advantage of our proposed intelligent scheme. Simulation results demonstrate the efficiency of our proposed intelligent scheme as well as the superiority of multi-IRS design in enhancing secrecy rate and spectrum utilization. It is shown that inappropriate deployment of IRSs can reduce the security performance with the presence of multiple eavesdroppers (Eves), and the arrangement of IRSs deserves further consideration.