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General Information
    • ISSN: 1793-8244 (Print)
    • Abbreviated Title:  J. Adv. Comput. Netw.
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Professor Haklin Kimm
    • Executive Editor: Ms. Cherry Chan
    • Abstracting/ Indexing: EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Editor-in-chief
Professor Haklin Kimm
East Stroudsburg University, USA
I'm happy to take on the position of editor in chief of JACN. We encourage authors to submit papers on all aspects of computer networks.

JACN 2015 Vol.3(4): 291-294 ISSN: 1793-8244
DOI: 10.18178/JACN.2015.3.4.184

The Analysis and Comparison of Energy Efficiency Based on Downlink Massive MIMO System

Zhenzhen Gao, Junxuan Wang, and Yi Li

Abstract—In order to improve the cellular energy efficiency, and without sacrificing the quality of service (QoS) at the user, we minimize the total power consumption. In the paper, under the downlink massive MIMO system, a large number of antennas at base station use to serve multi-users within the same cell. The article derives signal dynamic transmitted power, this problem has shown having a hidden convex optimization, we utilize convex optimization to solve the solutions effectively, and propose optimization algorithm that dynamically assigns energy to users, reduces the loss of energy. Under the same conditions and assumptions, we analyze and compare the performance of conventional maximum ratio transmission (MRT) and zero-forcing (ZF) scheme with optimization algorithm. The simulation results show that they are consistent with the theoretical results, and show the performance of optimization algorithm is better than the ZF, ZF better than the MRT under the same conditions.

Index Terms—Maximal-ratio-transmission (MRT), zero-forcing (ZF), optimization algorithm, massive MIMO, downlink transmission power.

The authors are with Xi'an University of Posts and Telecommunications, xi’an, China (e-mail: 2193195749@qq.com).

[PDF]

Cite:Zhenzhen Gao, Junxuan Wang, and Yi Li, "The Analysis and Comparison of Energy Efficiency Based on Downlink Massive MIMO System," Journal of Advances in Computer Networks vol. 3, no. 3, pp. 291-294, 2015.

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