Green 5G ultra-dense wireless heterogeneous networks:guidelines,techniques,and challenges

Yuzhou LI; Tao JIANG; Yang CAO; Zan LI

doi:10.11959/j.issn.1000-0801.2017197

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Green 5G ultra-dense wireless heterogeneous networks:guidelines,techniques,and challenges

Topic:5G | 更新时间：2024-06-05

- Green 5G ultra-dense wireless heterogeneous networks:guidelines,techniques,and challenges
- Telecommunications Science Vol. 33, Issue 6, Pages: 34-40(2017)
- 作者机构：
  
  1. 华中科技大学，湖北武汉 430074
  2. 西安电子科技大学，陕西西安 710071
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2017197
  CLC： TN929.5
- Published Online：2017-06，
  
  Published：20 June 2017
- 稿件说明：
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Yuzhou LI, Tao JIANG, Yang CAO, et al. Green 5G ultra-dense wireless heterogeneous networks:guidelines,techniques,and challenges[J]. Telecommunications science, 2017, 33(6): 34-40.
DOI：

Yuzhou LI, Tao JIANG, Yang CAO, et al. Green 5G ultra-dense wireless heterogeneous networks:guidelines,techniques,and challenges[J]. Telecommunications science, 2017, 33(6): 34-40. DOI： 10.11959/j.issn.1000-0801.2017197.

摘要

超密集无线异构网络被公认为是大幅提升无线网络容量、解决蜂窝网所面临的1 000倍数据量挑战最富有前景的一种5G组网技术。但是，与5G愿景背道而驰的是网络的超密集化部署在提升谱效的同时也极度地增大了系统的能耗，降低了通信能效。旨在利用超密集异构网络具有的全网管理能力和网络分集效应，从宏观的网络匹配与微观的资源聚合两方面探索超密集异构网络绿色演进的关键理论与技术。首先论述了绿色演进的基本理念，然后提出了利用负载自适应的基站开关控制、主动缓存和干扰感知的跨网资源分配三大关键技术来提升网络的能效，同时也讨论了每种技术在应用时所面临的挑战。

Abstract

Ultra-dense wireless heterogeneous network (Ud-HetNet) has been recognized as one of the most promising 5G network-organization techniques to significantly improve the wireless capacity and thus solve the 1 000× data challenge faced by cellular networks.However

counter to the expected 5G vision

although benefiting from the spectrum efficiency (SE) improvement

ultra-dense network deployment significantly increases system energy consumption and thus decreases network energy efficiency (EE).The key theories and techniques for energy-efficiently deploying Ud-HetNet were investigated from two aspects of macroscopic network matching and microscopic resource aggregation by exploiting their overall network management capabilities and network diversity effects.Specifically

the overall design guidelines for green evolution were introduced firstly

and then three techniques

namely load-aware base station on/off switching

proactive caching

and interference-aware cross-network resource allocation

were proposed to improve the network EE.Open issues and challenges that need to be further explored were also discussed.

关键词

Keywords

references

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