Waveform Optimization for MIMO Joint Communication and Radio Sensing Systems with Imperfect Channel Feedbacks

In this paper, we study optimal waveform design to maximize mutual information (MI) for a joint communication and (radio) sensing (JCAS, a.k.a., radar-communication) multi-input multi-output (MIMO) downlink system. We consider a typical packet-based signal structure which includes training and data symbols. We first derive the conditional MI for both sensing and communication under correlated channels by considering the training overhead and channel estimation error (CEE). Based on the derived MI, we provide optimal waveform design methods for three scenarios, including maximizing MI for communication only and for sensing only, and maximizing a weighted sum MI for both communication and sensing. We also present extensive simulation results that provide insights on waveform design and validate the effectiveness of the proposed designs.

I. Introduction

A joint communication and (radio) sensing (JCAS, a.k.a., Radar-Communications) system that enables share of hardware and signal processing modules, can achieve efficient spectrum efficiency, enhanced security, and reduced cost, size, and weight [1], [2]. JCAS systems can have many potential applications in intelligent transportation that require both communication links connecting vehicles and active environment sensing functions [3]. For JCAS systems, it is crucial to use a waveform simultaneously performing both communication and sensing function, and help improve the availability of the limited spectrum resources. To this end, one of the main challenges in JCAS systems lies in designing optimal or adequate waveforms that serve both purposes of data transmission and radio sensing.