Wang, Junyuan, Zhu, Huiling, Gomes, Nathan J., Wang, Jiangzhou (2018) Frequency Reuse of Beam Allocation for Multiuser Massive MIMO Systems. IEEE Transactions on Wireless Communications, (99). ISSN 1536-1276. (doi:10.1109/TWC.2018.2793227) (KAR id:66663)
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Official URL: https://doi.org/10.1109/TWC.2018.2793227 |
Abstract
Abstract—Massive multiple-input-multiple-output (MIMO)
has become a promising technique to provide high-data-rate
communication in fifth-generation (5G) mobile systems, thanks to
its ability to form narrow and high-gain beams. Among various
massive MIMO beamforming techniques, the fixed-beam scheme
has attracted considerable attention due to its simplicity. In this
paper, we focus on a fixed-beam based multiuser massive MIMO
system where each user is served by a beam allocated to it. To
maximize the sum data rate, a greedy beam allocation algorithm
is proposed under the practical condition that the number of
radio frequency (RF) chains is smaller than the number of users.
Simulation results show that our proposed greedy algorithm
achieves nearly optimal sum data rate. As only the sum data rate
is optimized, there are some “worst-case” users who could suffer
from strong inter-beam interference and thus experience low
data rate. To improve the individual data rates of the worst-case
users while maintaining the sum data rate, an adaptive frequency
reuse scheme is proposed. Simulation results corroborate that our
proposed adaptive frequency reuse strategy can greatly improve
the worst-case users’ data rates and the max-min fairness among
served users without sacrificing the sum data rate.
Item Type: | Article |
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DOI/Identification number: | 10.1109/TWC.2018.2793227 |
Uncontrolled keywords: | Frequency reuse, beam allocation, achievable data rate, worst-case users, massive multiple-input-multiple output MIMO |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Huiling Zhu |
Date Deposited: | 09 Apr 2018 09:47 UTC |
Last Modified: | 04 May 2024 03:11 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/66663 (The current URI for this page, for reference purposes) |
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