Unified framework for outage-constrained rate maximization in secure ISAC under various sensing metrics

TL;DR

This paper presents a unified optimization framework for secure ISAC systems that maximizes secrecy rates while satisfying diverse sensing constraints, effectively managing outage probabilities and outperforming existing methods.

Contribution

It introduces a flexible, convergent optimization framework that integrates sensing requirements and secrecy objectives into a single problem for secure ISAC.

Findings

Achieves higher secrecy rates under various sensing constraints.

Effectively controls secrecy outage probabilities.

Demonstrates superiority over existing methods through extensive simulations.

Abstract

Integrated sensing and communication (ISAC) is poised to redefine the landscape of wireless networks by seamlessly combining data transmission and environmental sensing. However, ISAC systems remain susceptible to eavesdropping, especially under uncertainty in eavesdroppers' channel state information, which can lead to secrecy outages. On the other hand, diverse and complex sensing performance requirements further complicate resource optimization, often requiring custom solutions for each scenario. To this end, this paper introduces a unified optimization framework that holistically addresses both the worst-case user secrecy rate and the sum secrecy rate across multiple users. Besides putting the two commonly used objectives into a single but flexible objective function, the framework accurately controls secrecy outage probabilities while accommodating a broad spectrum of sensing constraints. To solve such a general problem, we integrate the sensing requirements into the objective function through an auxiliary variable. This enables efficient alternating optimization and the proposed approach is theoretically guaranteed to converge to at least a stationary point of the original problem. Extensive simulation results show that the proposed framework consistently achieves higher optimized secrecy rates under various sensing constraints compared to existing methods. These results underscore the proposed unified framework's superiority and versatility in secure ISAC systems.