一种用于低复杂度和安全近场ISAC系统的双信念驱动贝叶斯-斯塔克尔伯格框架
A Dual Belief-Driven Bayesian-Stackelberg Framework for Low-Complexity and Secure Near-Field ISAC Systems
AI总结：
本文提出一种双信念驱动贝叶斯-斯塔克尔伯格框架，用于提升近场ISAC系统的安全性和效率，通过优化感知、波束成形和通信，实现高保密率和高成功率。
摘要：
在近场集成感知与通信（ISAC）系统中确保鲁棒安全性仍是一个关键挑战，由于动态信道条件、多窃听者威胁以及毫米波和太赫兹频率下的实时优化高计算负担。为了解决这些挑战，本文介绍了一种新的贝叶斯-斯塔克尔伯格框架，联合优化感知、波束成形和通信。双算法设计整合（i）适应性混合节点角色切换在安全传输和协作干扰之间（ii）基于信心的感知和波束成形用于基于置信度的资源分配。所提出的统一框架在保持线性计算复杂度的同时显著提高了对抗攻击的鲁棒性。在28至410GHz载波频率上的仿真结果表明，该方法实现了高达35%的保密率提升和超过98%的成功率，优于传统通信系统，且运行时间开销极小。这些发现强调了基于信念驱动的ISAC安全解决方案在下一代通信中低复杂度部署的可扩展性。
英文摘要：
Ensuring robust security in near-field Integrated Sensing and Communication (ISAC) systems remains a critical challenge due to dynamic channel conditions, multi-eavesdropper threats, and the high computational burden of real-time optimization at mmWave and THz frequencies. To address these challenges, this paper introduces a novel Bayesian-Stackelberg framework that jointly optimizes sensing, beamforming, and communication. The dual-algorithm design integrates (i) Adaptive Hybrid Node Role Switching between secure transmission and cooperative jamming (ii) Belief-Driven Sensing and Beamforming for confidence based resource allocation. The proposed unified framework significantly improves robustness against attacks while preserving linear computational complexity. Simulation results across carrier frequencies ranging from 28 to 410 GHz demonstrate that the method achieves up to a 35% increase in secrecy rates and a success rate exceeding 98%, outperforming conventional communication systems with minimal runtime overhead. These findings underscore the scalability of belief-driven ISAC security solutions for low-complexity deployment in next generation communications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
