2023/06/04 by Xue Ye, Xue, Ye, An Liu +7
Engineering · #Wireless Body Area Networks #IoT Networks and Protocols #Advanced MIMO Systems Optimization
paper · pdf · doi:10.48550/arxiv.2306.02436
In massive machine-type communications, data transmission is usually considered sporadic, and thus inherently has a sparse structure. This paper focuses on the joint activity detection (AD) and channel estimation (CE) problems in massive-connected communication systems with low-resolution analog-to-digital converters. To further exploit the sparse structure in transmission, we propose a maximum posterior probability (MAP) estimation problem based on both sporadic activity and sparse channels for joint AD and CE. Moreover, a majorization-minimization-based method is proposed for solving the MAP problem. Finally, various numerical experiments verify that the proposed scheme outperforms state-of-the-art methods.