Energy-Efficient Resources Allocation With Millimeter-Wave Massive Mimo in Ultra Dense Hetnets by Swipt and Comp

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Date

2021

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Institute of Electrical and Electronics Engineers Inc.

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Green Open Access

No

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Abstract

Ultra-dense HetNets (UDN)-based Millimeter-Wave (mmWave) massive MIMO is considered a promising technology for 5th generation (5G) wireless communications systems since it can offer massively available bandwidth and improve energy efficiency (EE) substantially. However, in UDN, the power consumption of the system increases sharply with the increase of network density. In this paper, we investigate the optimization of the EE in the mmWave massive MIMO systems with UDN. To develop the functions of massive MIMO, we first propose a system model where the massive MIMO harvests electromagnetic energy from the environment employing simultaneous wireless information and power transfer (SWIPT) technology, implemented at the base station (BS). Then, the EE optimization problem is formulated for 5G mmWave massive MIMO systems within the UDN. Considering the nonconcave feature of the objective function, an iterative EE algorithm is developed, based on Dinkelbach method. To utilize the role of coordinated multi-point transmission and reception (CoMP) for improving the EE, a coordinated user(UE)-BS association algorithm-based CoMP with maximum energy efficiency (MaxEE) is proposed. The simulation results demonstrate that the proposed algorithm has a substantially faster convergence rate and is very effective, compared with existing methods.

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Keywords

5G mobile communication, Antennas, CoMP, Energy efficiency, Massive MIMO, Millimeter-Wave Communcation, Optimization, Power demand, Resource management, SWIPT BS, Ultra dense HetNet, Wireless communication, Millimeter-Wave Communcation, Optimization, SWIPT BS, Resource management, Wireless communication, CoMP, Energy efficiency, 5G mobile communication, Power demand, Antennas, Massive MIMO, Ultra dense HetNet

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Fields of Science

02 engineering and technology, 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering

Citation

WoS Q

Q1

Scopus Q

Q1
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OpenCitations Citation Count
34

Source

IEEE Transactions on Wireless Communications

Volume

20

Issue

Start Page

4435

End Page

4451
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CrossRef : 6

Scopus : 47

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Mendeley Readers : 19

SCOPUS™ Citations

47

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Web of Science™ Citations

42

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Page Views

4

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Downloads

140

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