Waveform Optimization with Multiple Performance Metrics for Broadband Joint Communication and Radar Sensing

TL;DR

This paper develops waveform optimization techniques for joint communication and radar sensing systems, balancing multiple performance metrics to enhance both functionalities simultaneously.

Contribution

It introduces novel waveform optimization problems for communication and radar, providing closed-form and iterative solutions for the integrated JCAS system.

Findings

Proposed a new lower bound for sum rate in communication.

Optimized radar metrics using mutual information and Cramer-Rao bound.

Validated solutions through numerical simulations.

Abstract

Joint communication and radar sensing (JCAS) integrates communication and radar/radio sensing into one system, sharing one transmitted signal. In this paper, we investigate JCAS waveform optimization underlying communication signals, where a base station detects radar targets and communicates with mobile users simultaneously. We first develop individual novel waveform optimization problems for communications and sensing, respectively. For communications, we propose a novel lower bound of sum rate by integrating multi-user interference and effective channel gain into one metric that simplifies the optimization of the sum rate. For radar sensing, we consider optimizing one of two metrics, the mutual information or the Cramer-Rao bound. Then, we formulate the JCAS problem by optimizing the communication metric under different constraints of the radar metric, and we obtain both closed-form solutions and iterative solutions to the non-convex JCAS optimization problem. Numerical results are provided and verify the proposed optimization solutions.