This paper investigates sensing, communication, security, and energy efficiency of the heterogeneous integrated sensing and communication networks under challenging operational conditions. We focus on scenarios in which communication performance, security, and sensing accuracy are degraded by interference, eavesdropping, and imperfect channel state information. To this end, we analyze communication and sensing signals within ISAC framework as well as the communication signals of a multicast network based on \emph{rate-splitting multiple access} (RSMA). Then, sensing signal-to-cluster-plus-noise ratio, communication rate, security rate, and \emph{security energy efficiency} (SEE) are evaluated. To simultaneously enhance these system performances, we propose a targeted optimization framework aimed at maximizing SEE. This framework characterizes the sensing-security trade-off by jointly optimizing the transmit \emph{beamforming} (BF) vectors and the echo BF vector to construct green interference using the echo signal, as well as common and private streams generated by RSMA. Particularly, the joint design improves the security rate and reduces power consumption, thereby enabling a higher SEE. Given the non-convex nature of the optimization problem, we present an alternative approach that leverages Taylor series expansion, majorization-minimization, semi-definite programming, and successive convex approximation techniques. Specifically, we decompose the original non-convex and intractable optimization problem into three simplified sub-optimization problems, which are iteratively solved using an alternating optimization strategy. Simulations provide comparisons with state-of-the-art schemes, highlighting the superior efficiency, robustness, and scalability of the proposed joint multi-BF optimization scheme based on RSMA and green interference in improving system performances.

翻译：本文研究了异构集成感知与通信网络在挑战性运行条件下的感知、通信、安全与能效性能。我们重点关注通信性能、安全性和感知精度因干扰、窃听及不完善信道状态信息而降低的场景。为此，我们分析了ISAC框架内的通信与感知信号，以及基于速率分割多址接入（RSMA）的多播网络通信信号。随后，评估了感知信簇噪比、通信速率、安全速率与安全能效（SEE）。为同时提升这些系统性能，我们提出了一个以最大化SEE为目标的优化框架。该框架通过联合优化发射波束赋形（BF）向量与回波BF向量以利用回波信号构建绿色干扰，以及优化RSMA生成的公共流与私有流，从而刻画感知-安全权衡关系。特别地，该联合设计提升了安全速率并降低了功耗，从而实现更高的SEE。鉴于该优化问题的非凸特性，我们提出了一种基于泰勒级数展开、主化最小化、半定规划与逐次凸近似技术的替代方法。具体而言，我们将原始非凸且难处理的优化问题分解为三个简化的子优化问题，并采用交替优化策略进行迭代求解。仿真结果与现有先进方案进行了对比，凸显了所提出的基于RSMA与绿色干扰的联合多BF优化方案在提升系统性能方面具有更优的效能、鲁棒性与可扩展性。