MSE-Based Training and Transmission Optimization for MIMO ISAC Systems
Zhenyao He, Wei Xu, Hong Shen, Yonina C. Eldar, and Xiaohu You

TL;DR
This paper proposes novel MSE-based training and transmission schemes for MIMO ISAC systems that optimize sensing and communication performance simultaneously, using either instantaneous or statistical CSI for robust design.
Contribution
It introduces two innovative joint training and transmission schemes for MIMO ISAC systems that minimize combined MSEs, with solutions based on MM algorithms and low-complexity alternatives.
Findings
Radar performance significantly improved over existing methods.
Proposed schemes balance communication and sensing performance.
Robust designs effective with limited CSI feedback.
Abstract
In this paper, we investigate a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system under typical block-fading channels. As a non-trivial extension to most existing works on ISAC, both the training and transmission signals sent by the ISAC transmitter are exploited for sensing. Specifically, we develop two training and transmission design schemes to minimize a weighted sum of the mean-squared errors (MSEs) of data transmission and radar target response matrix (TRM) estimation. For the former, we first optimize the training signal for simultaneous communication channel and radar TRM estimation. Then, based on the estimated instantaneous channel state information (CSI), we propose an efficient majorization-minimization (MM)-based robust ISAC transmission design, where a semi-closed form solution is obtained in each iteration. For the second scheme, the…
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Taxonomy
TopicsAntenna Design and Optimization · Satellite Communication Systems
