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.

翻译：安全通信在频谱共享网络中至关重要，这是由频谱资源的分配与共享特性所决定的。为深入探索智能反射面（IRS）在提升频谱共享与安全传输性能方面的潜力，本文研究了一种基于物理层安全技术的多智能反射面辅助感知增强宽带频谱共享网络。提出一种基于双重深度Q网络（D3QN）算法与软演员-评论家（SAC）算法的智能资源分配方案，通过联合优化IRS配对、子信道分配、次基站发射波束成形、IRS反射系数及感知时间，最大化次网络的安全传输速率。针对多个IRS大量反射单元导致的稀疏奖励问题，采用分层强化学习方法。引入一种基于交替优化（AO）的传统数学方案，以验证所提智能方案的计算复杂度优势。仿真结果表明，所提智能方案具有高效性，且多IRS设计在提升保密速率与频谱利用率方面具有显著优越性。研究显示，在多个窃听者存在的场景下，IRS的不当部署会降低安全性能，因此IRS的布局值得进一步考量。