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Journal Article Low Dimensional Multiuser Detection Exploiting Low User Activity
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Authors
Junho Lee, Seung-Hwan Lee
Issue Date
2013-06
Citation
Journal of Communications and Networks, v.15, no.3, pp.283-291
ISSN
1229-2370
Publisher
한국통신학회
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1109/JCN.2013.000051
Project Code
13PI1800, Research on wireless transmission techniques for enhancing QoE performance of smart mobile services, Lee Seung-Hwan
Abstract
In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD. © 2011 JCN.
KSP Keywords
Binary Phase Shift Keying, Compressed sensing, Interference cancellation, Large-scale multiple antenna systems, Low-Power, Low-dimensional, Maximum a posteriori probability, Multiple input multiple output(MIMO), Multiuser detection, Number of users, Simulation study