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  • Joint Active User Detection, Channel Estimation, and Data Detection for Massive Grant-Free Transmission in Cell-Free Systems

This content will become publicly available on September 25, 2024

Title: Joint Active User Detection, Channel Estimation, and Data Detection for Massive Grant-Free Transmission in Cell-Free Systems
Cell-free communication has the potential to significantly improve grant-free transmission in massive machine-type communication, wherein multiple access points jointly serve a large number of user equipments to improve coverage and spectral efficiency. In this paper, we propose a novel framework for joint active user detection (AUD), channel estimation (CE), and data detection (DD) for massive grant-free transmission in cell-free systems. We formulate an optimization problem for joint AUD, CE, and DD by considering both the sparsity of the data matrix, which arises from intermittent user activity, and the sparsity of the effective channel matrix, which arises from intermittent user activity and large-scale fading. We approximately solve this optimization problem with a box-constrained forward-backward splitting algorithm, which significantly improves AUD, CE, and DD performance. We demonstrate the effectiveness of the proposed framework through simulation experiments.  more » « less
Award ID(s):
1824379
NSF-PAR ID:
10490322
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Page Range / eLocation ID:
406 to 410
Format(s):
Medium: X
Location:
Shanghai, China
Sponsoring Org:
National Science Foundation
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