Spatio-Temporal Power Optimization for MIMO Joint Communication and Radio Sensing Systems With Training Overhead

In this paper, we study optimal spatio-temporal power mask 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). Then, we derive a lower bound for the CEE and optimize the energy arrangement between the training and data signals to minimize the CEE. Based on the optimal energy arrangement, we provide optimal spatio-temporal power mask design for three scenarios, including maximizing MI for communication only and for sensing only, and maximizing a weighted sum MI for both communication and sensing. Extensive simulations validate the effectiveness of the proposed designs.

Automated summary

This paper studies optimal spatio-temporal power mask design to maximize mutual information for a joint communication and sensing MIMO system. By considering training overhead and channel estimation error, conditional mutual information is derived and energy allocation is optimized to minimize the error. Three scenarios of optimal power mask design are provided and verified through extensive simulations.