Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

TL;DR

This paper develops a robust transceiver design for covert integrated sensing and communications systems with imperfect CSI, using convex optimization techniques to enhance performance and covertness under uncertainty.

Contribution

It introduces a novel robust optimization framework employing S-procedure and Bernstein inequalities for joint beamforming and waveform design under CSI errors.

Findings

Improves radar and communication performance robustness.

Ensures covert operation under CSI uncertainties.

Demonstrates effectiveness through numerical simulations.

Abstract

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint trasceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems.