Power Normalization Perspective for massive MIMO Network using MMSE Precoding Techniques

Author:

Eze Gerald Chukwudi ,Ahaneku, Mamilus A., ,Chijindu, Vincent C.

Abstract

This paper seeks ways to improve spectral efficiency (or throughput) while mitigating multi-user interferences for large-scale antenna arrays, massive multiple input multiple output (mMIMO) systems via the use of the minimum mean squared error (MMSE) precoding schemes. The impact of the power at the user equipment (UEs) being adjusted to meet the transmission power constraint of the BS otherwise known as power normalization on the performance of the single and multi-cell MMSE precoders (S-MMSE and M-MMSE) was studied. The choice of power normalization (matrix normalization or vector normalization) and how they can impact worse or better performances on S-MMSE and M-MMSE under three different channel estimates with respect to varying pilot reuse factors were simulated and analyzed. We considered a downlink mMIMO network model that accounts for the number of antennas and single-antenna UEs. Numerical results obtained after simulations depict that M-MMSE with vector normalization (VN) out-performs S-MMSE with vector/matrix normalization and M-MMSE with matrix normalization (MN) by having the highest average sum SE, throughput, and signal-to-interference plus noise ratio (SINR/SNR) for any number of antennas and UEs in the three-channel estimators. LS channel estimator performs the least when compared to EW-MMSE and MMSE channel estimators.

Publisher

RSIS International

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3