@inproceedings{d220f8068b2c44f5b27c2277f37b02a7,
title = "Information Geometry Approach for Ultra-Massive MIMO Signal Detection",
abstract = "In this paper, we propose an information geometry approach (IGA) for signal detection in ultra-massive multiple-input multiple-output (MIMO) systems. We formulate the signal detection as obtaining the marginals of the a posteriori probability distribution of the transmitted symbol vector. Then, a maximization of the a posteriori marginals (MPM) for signal detection can be performed. With the information geometry theory, we calculate the approximations of the a posteriori marginals. It is formulated as an iterative m-projection process. We then apply the central-limit-theorem (CLT) to simplify the calculation of the m-projection since the direct calculation of the m-projection is of exponential-complexity. With the CLT, we obtain an approximate solution of the m-projection, which is asymptotically accurate. Simulation results demonstrate that the proposed IGA is a promising and efficient method to implement the signal detector in ultra-massive MIMO systems.",
keywords = "Bayesian inference, Ultra-massive MIMO, information geometry, signal detection",
author = "Yan Chen and Jiyuan Yang and Xiqi Gao and Dirk Slock and Xia, \{Xiang Gen\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023 ; Conference date: 02-11-2023 Through 04-11-2023",
year = "2023",
doi = "10.1109/WCSP58612.2023.10404161",
language = "English",
series = "2023 IEEE 15th International Conference on Wireless Communications and Signal Processing, WCSP 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1185--1190",
booktitle = "2023 IEEE 15th International Conference on Wireless Communications and Signal Processing, WCSP 2023",
address = "United States",
}