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5G能源效率的近期趋势与开放问题调查

A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G.

作者信息

Usama Muhammad, Erol-Kantarci Melike

机构信息

School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada.

出版信息

Sensors (Basel). 2019 Jul 15;19(14):3126. doi: 10.3390/s19143126.

DOI:10.3390/s19143126
PMID:31311203
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6679251/
Abstract

The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a resource efficient but also an energy efficient ecosystem has greatly been felt. The deployment of small cells has been envisioned as a promising answer for handling the massive heterogeneous traffic, but the adverse economic and environmental impacts cannot be neglected. Given that 10% of the world's energy consumption is due to the Information and Communications Technology (ICT) industry, energy-efficiency has thus become one of the key performance indicators (KPI). Various avenues of optimization, game theory and machine learning have been investigated for enhancing power allocation for downlink and uplink channels, as well as other energy consumption/saving approaches. This paper surveys the recent works that address energy efficiency of the radio access as well as the core of wireless networks, and outlines related challenges and open issues.

摘要

各行各业对即将到来的第五代(5G)网络的兴趣迅速增长,期望该网络支持更高的数据速率并提高服务质量。到目前为止,通过采用复杂的传输技术,包括大规模多输入多输出(MIMO)、毫米波(mmWave)频段,以及通过基站的先进基带处理单元将计算能力更靠近用户,这一需求已得到满足。网络的未来演进也被认为将为运营商开辟许多新的业务领域,人们强烈感受到不仅需要一个资源高效的生态系统,还需要一个节能的生态系统。小基站的部署被视为应对大量异构流量的一个有前景的解决方案,但不利的经济和环境影响不容忽视。鉴于全球10%的能源消耗归因于信息通信技术(ICT)行业,能源效率因此已成为关键性能指标(KPI)之一。为了增强下行链路和上行链路信道的功率分配以及其他能源消耗/节约方法,人们研究了各种优化途径、博弈论和机器学习。本文综述了近期针对无线接入以及无线网络核心的能源效率的研究工作,并概述了相关挑战和未解决的问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/0649c3e337f0/sensors-19-03126-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/66095183aeaa/sensors-19-03126-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/6ec15b12dd4c/sensors-19-03126-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/cc0ee6ac3618/sensors-19-03126-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/ccec6b9d79bb/sensors-19-03126-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/10f9072efd67/sensors-19-03126-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/b35adea6fcc9/sensors-19-03126-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/0649c3e337f0/sensors-19-03126-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/66095183aeaa/sensors-19-03126-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/6ec15b12dd4c/sensors-19-03126-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/cc0ee6ac3618/sensors-19-03126-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/ccec6b9d79bb/sensors-19-03126-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/10f9072efd67/sensors-19-03126-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/b35adea6fcc9/sensors-19-03126-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cb2/6679251/0649c3e337f0/sensors-19-03126-g007.jpg

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