Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 70, Issue 1, Pages 514-528Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.3046438
Keywords
Sensors; Training; Radar; MIMO communication; Channel estimation; Transmitters; MIMO radar; Joint communication and sensing; mutual information; training sequences; waveform design
Categories
Funding
- National Natural Science Foundation of China [61631003, 61790553]
- Beijing Natural Science Foundation [L192031]
- NSW Defence Innovation Network
- NSW State Government through Pilot Project [DINPP-19-20 10.01]
Ask authors/readers for more resources
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.
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available