H-CRAN绿色演进：节能技术、性能折衷与挑战解析

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本文主要探讨了绿色异构云无线接入网络（H-CRAN）在无线网络绿色演进中的重要性。H-CRAN作为一种灵活且可扩展的架构，它通过集中化网络功能和云计算的优势，提高了网络效率（Energy Efficiency, EE）。然而，这种优势的提升往往伴随着服务质量（Quality of Service, QoS）如吞吐量（SE, Spectral Efficiency）、公平性以及延迟等方面的妥协。为了在H-CRAN中实现节能传输和卓越QoS的平衡，作者提出了研究性能折衷方案的必要性。文章首先聚焦于绿色技术的应用，旨在提出一系列潜在的技术手段，这些技术能够有效利用H-CRAN的特性来降低能耗。这些方法可能包括但不限于：动态功率控制、频谱管理和资源调度的优化算法，以及能效的网络架构设计，如网络功能虚拟化和云计算的节能策略。接着，作者深入探讨了三种关键的性能折衷方案：EE-SE折衷，意味着在保持一定能源效率的同时，寻求最大的带宽利用率；EE-fairness折衷，旨在确保所有用户得到相对公平的服务，即使在节能模式下也能保持服务质量均衡；以及EE-延迟折衷，关注的是在满足能量效率的前提下，尽可能减少服务响应时间。每个折衷方案都需要精细的模型构建和系统仿真，以评估其实际效果并确定最佳实践。文章还指出了在实施这些绿色技术时面临的挑战，例如，如何在动态环境中实时调整资源分配，确保网络的快速适应性；如何设计智能网络控制机制，实现能效与服务质量的动态平衡；以及如何进行大规模的网络规划，兼顾长期的能效和经济效益。这些问题的解决对于H-CRAN的绿色运营至关重要，它们涉及到了诸如机器学习、自适应算法、网络拓扑优化等多个领域的交叉研究。本文通过对绿色技术的挖掘、性能折衷方案的分析以及未来研究挑战的阐述，为H-CRAN的绿色运营提供了理论基础和实践指导，旨在推动无线网络向着更加节能、高效和公平的方向发展。这将有助于运营商在满足不断增长的移动数据需求的同时，减轻对环境的影响，为未来的无线通信系统树立了可持续发展的典范。

IEEE Communications Magazine • November 2017

AbstrAct

As a ﬂexible and scalable architecture, hetero-

geneous cloud radio access networks (H-CRANs)

inject strong vigor into the green evolution of

current wireless networks. But the brutal truth is

that EE improves at the cost of other indices such

as SE, fairness, and delay. It is thus important to

investigate performance trade-oﬀs for striking ﬂex-

ible balances between energy-efficient transmis-

sion and excellent QoS guarantees under this new

architecture. In this article, we ﬁrst propose some

potential techniques to energy-eﬃciently operate

H-CRANs by exploiting their features. We then

elaborate the initial ideas of modeling three fun-

damental trade-oﬀs, namely EE-SE, EE-fairness, and

EE-delay trade-offs, when applying these green

techniques, and present open issues and challeng-

es for future investigation. These related results

are expected to shed light on green operation

of H-CRANs from adaptive resource allocation,

intelligent network control, and scalable network

planning.

IntroductIon

bAckground And MotIvAtIon

The dramatic increase in the number of smart-

phones and tablets with ubiquitous broadband

connectivity has triggered an explosive growth

in mobile data traﬃc [1]. Cisco forecasts that the

amount of global mobile data traﬃc will increase

7-fold from 2016 to 2021, the majority of which

are generated by energy-hungry applications such

as mobile video [1]. This is also referred to as

the well-known 1000× data challenge in cellu-

lar networks. Meanwhile, the number of devices

connected to the global mobile communication

networks will reach 100 billion in the future, and

that of mobile terminals will surpass 10 billion by

2020 [2].

Although unprecedented opportunities for

the development of wireless networks are creat-

ed by the massive traﬃc amount and connected

devices, a concomitant crux is that this growth

skyrockets the energy consumption (EC) and

greenhouse gas emissions in the meantime. From

statistical data, the information and communi-

cation technology (ICT) industry is responsible

for 2 percent of worldwide CO

emissions and

2–10 percent of global EC, of which more than

60 percent is directly attributed to radio access

networks (RANs) [3]. In this regard, 5G wireless

communication networks are anticipated to pro-

vide spectral eﬃciency (SE) and energy eﬃciency

(EE) growth by a factor of at least 10 and 10 times

longer battery life of connected devices [2].

concept of H-crAns

To meet the 1000× data challenge, heteroge-

neous networks (HetNets), composed of a diverse

set of small cells (e.g., microcells, picocells, and

femtocells) overlaying the conventional macro-

cells, have been introduced as one of the most

promising solutions [2]. However, the ubiquitous

deployment of HetNets is accompanied by the

following shackles:

• Severe interference: The spectrum reuse

among cells incurs severe mutual interfer-

ence, which may significantly reduce the

expected system SE and also decrease the

network EE.

• Unsatisfactory EE: The densely deployed

small cells lead to escalated EC and thus

reduced EE, and also increases capital expen-

ditures (CAPEX) and operational expendi-

tures (OPEX).

• No computing-enhanced coordination cen-

ters: There are no centralized units with

strong computing abilities to globally coor-

dinate multi-tier interference and execute

cross-RAN optimization, which dramatically

limits cooperative gains among cells.

• Inflexibility and unscalability: Fragmented

base stations (BSs) result in inflexible and

unscalable network control and operations,

thus leading to redundant network planning

and inconvenient network upgrade.

To overcome these challenges faced by Het-

Nets, cloud RANs (C-RANs), new centralized

cellular architectures armed with powerful cloud

computing and virtualization techniques, have

been put forward in parallel to coordinate inter-

ference and manage resources across cells and

RANs [4]. In C-RANs, a large number of low-cost

low-power remote radio heads (RRHs), connect-

ing to the baseband unit (BBU) pool through the

fronthaul links, are randomly deployed to enhance

the wireless capacity in hotspots. Consequently,

the combination of HetNets and C-RANs, known

Green Heterogeneous Cloud Radio Access

Networks: Potential Techniques,

Performance Trade-offs, and Challenges

Yuzhou Li, Tao Jiang, Kai Luo, and Shiwen Mao

green coMMunIcAtIons And coMputIng networks

The authors ﬁrst propose

some potential tech-

niques to energy-efﬁcient-

ly operate H-CRANs by

exploiting their features.

They then elaborate the

initial ideas of model-

ing three fundamental

trade-offs, namely EE-SE,

EE-fairness, and EE-delay

trade-offs, when applying

these green techniques,

and present open issues

and challenges for future

investigation.

Yuzhou Li, Tao Jiang, and Kai Luo are with Huazhong University of Science and Technology; Shiwen Mao is with Auburn University.

Digital Object Identiﬁer:

10.1109/MCOM.2017.1600807

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