Robust Waveform Design for Integrated Sensing and Communication

TL;DR

This paper develops a robust waveform design approach for integrated sensing and communication systems that accounts for channel uncertainties, providing a conservative performance trade-off characterization.

Contribution

It introduces a novel framework for robust waveform design under channel uncertainty, addressing non-convex, high-dimensional optimization challenges with an efficient approximation method.

Findings

The robust design improves the lower bound of the true Pareto frontier.

Simulation results validate the effectiveness of the proposed approach.

The method characterizes the sensing-communication trade-off under uncertainty.

Abstract

Integrated sensing and communication (ISAC), which enables hardware, resources (e.g., spectra), and waveforms sharing, is becoming a key feature in future-generation communication systems. This paper investigates performance characterization and waveform design for ISAC systems when the underlying true communication channels are not accurately known. With uncertainty in a nominal communication channel, the nominal Pareto frontier of the sensing and communication performances cannot represent the true performance trade-off of a real-world operating ISAC system. Therefore, this paper portrays the robust (i.e., conservative) Pareto frontier considering the uncertainty in the communication channel. To be specific, the lower bound of the true (but unknown) Pareto frontier is investigated, technically by studying robust waveform design problems that find the best waveforms under the worst-case channels. The robust waveform design problems examined in this paper are shown to be non-convex and high-dimensional, which cannot be solved using existing optimization techniques. As such, we propose a computationally efficient solution framework to approximately solve them. Simulation results show that by solving the robust waveform design problems, the lower bound of the true but unknown Pareto frontier, which characterizes the sensing-communication performance trade-off under communication channel uncertainty, can be obtained.