WILEY Backhauling Fronthauling for Future Wireless Systems User Manual
BACKHAULING/
FRONTHAULING FOR
FUTURE WIRELESS
SYSTEMS
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BACKHAULING/
FRONTHAULING FOR
FUTURE WIRELESS
SYSTEMS
Edited by
Kazi Mohammed Saidul Huq and Jonathan Rodriguez
Instituto de Telecomunicações, Aveiro, Portugal
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This edition first published 2017
© 2017 John Wiley & Sons, Ltd.
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Library of Congress Cataloging‐in‐Publication Data
Names: Huq, Kazi Mohammed Saidul, editor. | Rodriguez, Jonathan, editor.
Title: Backhauling/fronthauling for future wireless systems / edited by Kazi Mohammed Saidul Huq,
Jonathan Rodriguez.
Description: Chichester, UK ; Hoboken, NJ : John Wiley & Sons, 2017. |
Includes bibliographical references and index.
Identifiers: LCCN 2016026831 (print) | LCCN 2016042959 (ebook) | ISBN 9781119170341 (cloth) |
ISBN 9781119170358 (pdf) | ISBN 9781119170365 (epub)
Subjects: LCSH: Wireless communication systems.
Classification: LCC TK5103.2 .B33 2017 (print) | LCC TK5103.2 (ebook) | DDC 384.5–dc23
LC record available at https://lccn.loc.gov/2016026831
A catalogue record for this book is available from the British Library.
Cover image: Gettyimages/Petrovich9
Set in 11/13pt Times by SPi Global, Pondicherry, India
10 9 8 7 6 5 4 3 2 1
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Contents
List of Contributors ix
Preface xi
Acknowledgements xiii
1 Introduction: The Communication Haul Challenge 1
Kazi Mohammed Saidul Huq and Jonathan Rodriguez
1.1 Introduction 1
References 7
2 A C‐RAN Approach for5G Applications 9
Kazi Mohammed Saidul Huq, Shahid Mumtaz and Jonathan Rodriguez
2.1 Introduction 9
2.2 From Wired toWireless Backhaul/Fronthaul Technologies 11
2.3 Architecture forCoordinated Systems According
toBaseline 3GPP 12
2.4 Reference Architecture forC‐RAN 15
2.4.1 System Architecture forFronthaul‐based C‐RAN 15
2.4.2 Cloud Resource Optimizer 16
2.5 Potential Applications forC‐RAN‐based Mobile Systems 20
2.5.1 Virtualization ofD2D Services 20
2.5.2 Numerical Analysis 21
2.6 Conclusion 24
References 27
3 Backhauling 5G Small Cells withMassive‐MIMO‐Enabled
mmWave Communication 29
Ummy Habiba, Hina Tabassum and Ekram Hossain
3.1 Introduction 29
3.2 Existing Wireless Backhauling Solutions for5G Small Cells 31
3.3 Fundamentals ofmmWave andMassive MIMO Technologies 32
3.3.1 MmWave Communication 32
3.3.2 MU‐MIMO withLarge Antenna Arrays 33
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vi Contents
3.4 MmWave Backhauling: State oftheArt andResearch Issues 34
3.4.1 LOS mmWave Backhauling 35
3.4.2 NLOS mmWave Backhauling 36
3.4.3 Research Challenges forBackhauling in5G Networks 37
3.5 Case Study: Massive‐MIMO‐based mmWave BackhaulingSystem 40
3.5.1 System Model 41
3.5.2 Maximizing User Rate 44
3.5.3 Matching Theory forUser Association 45
3.5.4 Numerical Results 48
3.6 Conclusion 51
Acknowledgement 51
References 51
4 Fronthaul foraFlexible Centralization inCloud Radio Access Networks 55
Jens Bartelt,
Dirk Wübben, Peter Rost, Johannes Lessmann andGerhardFettweis
4.1 Introduction 55
4.2 Radio Access Network Architecture 57
4.3 Functional Split Options 58
4.4 Requirements ofFlexible Functional Splits 60
4.4.1 Split A 61
4.4.2 Split B 62
4.4.3 Split C 63
4.4.4 Split D 64
4.4.5 Summary andExamples 64
4.5 Statistical Multiplexing inaFlexibly Centralized Network 67
4.5.1 Distribution ofFH Data Rate per Base Station 67
4.5.2 Outage Rate 68
4.5.3 Statistical Multiplexing onAggregation Links 69
4.6 Convergence ofFronthaul andBackhaul Technologies 73
4.6.1 Physical Layer Technologies 73
4.6.2 Data/MAC Layer Technologies 75
4.6.3 Network Layer Technologies 77
4.6.4 Control andManagement Plane 78
4.7 Enablers ofaFlexible Functional Split 78
4.8 Summary 80
Acknowledgement 82
References 82
5 Analysis andOptimization forHeterogeneous Backhaul Technologies 85
Gongzheng Zhang, Tony Q. S. Quek, Marios Kountouris, Aiping Huang
andHangguan Shan
5.1 Introduction 85
5.2 Backhaul Model 88
5.2.1 Network Model 88
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Contents vii
5.2.2 Delay Model 89
5.2.3 Cost Model 92
5.3 Backhaul Packet Delay Analysis 93
5.3.1 Mean Backhaul Packet Delay 93
5.3.2 Delay‐limited Success Probability 95
5.3.3 Performance Evaluation 97
5.4 Backhaul Deployment Cost Analysis 101
5.5 Backhaul‐aware BS Association Policy 103
5.5.1 Mean Network Packet Delay 103
5.5.2 BS Association Policy 107
5.5.3 Numerical Results 109
5.6 Conclusions 115
References 115
6 Dynamic Enhanced Inter‐cell Interference Coordination
StrategywithQuality ofService Guarantees for
Heterogeneous Networks 119
Wei‐Sheng Lai, Tsung‐Hui Chang, Kuan‐Hsuan Yeh and Ta‐Sung Lee
6.1 Introduction 119
6.2 System Model andProblem Statement 121
6.2.1 Network Environments 121
6.2.2 QoS Constraint 124
6.2.3 Problem Statements 125
6.3 Dynamic Interference Coordination Strategy 126
6.3.1 SMDP Analysis 126
6.3.2 Admission Control withaQoS Constraint 128
6.3.3 Joint Dynamic eICIC andAdmission Control for
SumRateMaximization 129
6.3.4 Joint Dynamic eICIC andAdmission Control for
ProportionalFairness Maximization 130
6.4 Numerical Results 132
6.5 Conclusion 140
References 140
7 Cell Selection forJoint Optimization oftheRadio Access
and Backhaul inHeterogeneous Cellular Networks 143
Antonio De Domenico, Valentin Savin and Dimitri Ktenas
7.1 Introduction 143
7.2 System Model andProblem Statement 145
7.2.1 Joint RAN/BH Capacity 146
7.2.2 Problem Statement 151
7.3 Proposed Solutions 151
7.3.1 Evolve 151
7.3.2 Relax 154
7.3.3 Practical Implementation oftheProposed Algorithms 156
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viii Contents
7.4 Simulation Results 157
7.5 Conclusion 165
References 165
8 Multiband andMultichannel Aggregation forHigh‐speed Wireless
Backhaul: Challenges andSolutions 167
Xiaojing Huang
8.1 Introduction 167
8.2 Spectrum forWireless Backhaul 170
8.2.1 Microwave Band andChannel Allocation 170
8.2.2 Millimetre‐wave Band andUsage Trend 171
8.3 Multiband andMultichannel Aggregation 172
8.3.1 Band andChannel Aggregation Overview 172
8.3.2 System Architecture 174
8.3.3 Subband Aggregation andImplementations 177
8.3.4 Full SDR Approach forBand andChannel Aggregation 183
8.4 Spectrally Efficient Channel Aggregation 185
8.4.1 System Overview 185
8.4.2 Frequency‐domain Multiplexing Without aGuard Band 186
8.4.3 Digital IF Signal Generation andReception 188
8.4.4 High-performance OFDM Transmission 188
8.5 Practical System Examples 189
8.5.1 CSIRO Ngara Backhaul 190
8.5.2 CSIRO High‐speed E‐band Systems 191
8.6 Conclusions 194
References 194
9 Security Challenges forCloud Radio Access Networks 195
Victor Sucasas, Georgios Mantas and Jonathan Rodriguez
9.1 Introduction 195
9.2 Overview ofC‐RAN Architecture 196
9.3 Intrusion Attacks intheC‐RAN Environment 197
9.3.1 Entry Points forIntrusion Attacks 198
9.3.2 Technical Challenges forIntrusion Detection
Counter‐mechanisms 201
9.3.3 Insider Attacks 203
9.4 Distributed Denial ofService (DDoS) Attacks Against C‐RAN 205
9.4.1 DDoS Attacks Using Signalling Amplification 206
9.4.2 DDoS Attacks Against External Entities Over
the Mobile Network 207
9.4.3 DDoS Attacks fromExternal Compromised IP Networks
OvertheMobile Network 208
9.5 Conclusions 209
References 209
Index 213
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List of Contributors
Jens Bartelt
Technische Universität Dresden, Vodafone Chair MNS, Dresden, Germany
Tsung-Hui Chang
School of Science and Engineering, The Chinese University of Hong Kong,
Shenzhen,CUHK (SZ), China
Antonio De Domenico
CEA, LETI, MINATEC, Grenoble, France
Gerhard Fettweis
Technische Universität Dresden, Vodafone Chair MNS, Dresden, Germany
Ummy Habiba
The Department of Electrical and Computer Engineering, University of Manitoba,
Canada
Ekram Hossain
The Department of Electrical and Computer Engineering, University of Manitoba,
Canada
Aiping Huang
College of Information Science and Electronic Engineering, Zhejiang University,
China
Xiaojing Huang
Faculty of Engineering and Information Technology, University of Technology
Sydney (UTS), Australia
Kazi Mohammed Saidul Huq
Instituto de Telecomunicações, Aveiro, Portugal
Marios Kountouris
Mathematical and Algorithmic Sciences Lab, France Research Centre, Huawei
Technologies, France
Dimitri Ktenas
CEA, LETI, MINATEC, Grenoble, France
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x List of Contributors
Wei-Sheng Lai
Department of Electrical and Computer Engineering, National Chiao Tung
University, Hsinchu, Taiwan
Ta-Sung Lee
Department of Electrical and Computer Engineering, National Chiao Tung
University, Hsinchu, Taiwan
Johannes Lessmann
NEC Laboratories Europe, Heidelberg, Germany
Georgios Mantas
Instituto de Telecomunicações, Aveiro, Portugal
Shahid Mumtaz
Instituto de Telecomunicações, Aveiro, Portugal
Tony Q. S. Quek
Information Systems Technology and Design Pillar, Singapore University of
Technology and Design, Singapore
Jonathan Rodriguez
Instituto de Telecomunicações, Aveiro, Portugal
Peter Rost
Nokia Networks, Munich, Germany
Valentin Savin
CEA, LETI, MINATEC, Grenoble, France
Hangguan Shan
College of Information Science and Electronic Engineering, Zhejiang University,
China
Victor Sucasas
Instituto de Telecomunicações, Aveiro, Portugal
Hina Tabassum
The Department of Electrical and Computer Engineering, University of Manitoba, Canada
Dirk Wübben
University of Bremen, Department of Communications Engineering, Bremen, Germany
Kuan-Hsuan Yeh
ASUSTeK Computer Inc., Taipei, Taiwan
Gongzheng Zhang
College of Information Science and Electronic Engineering, Zhejiang University,
China
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Preface
In a mobile communication system, the segment that connects the core to the access
networks is termed the ‘backhaul’. The edges of any telecommunication network are
connected through backhauling. The importance of backhaul research is spurred by
the need for increasing data capacity and coverage to cater for the ever‐growing
population of electronic devices–smartphones, tablets and laptops–which is foreseen to hit unprecedented levels by 2020. The backhaul is anticipated to play a critical
role in handling large volumes of traffic, its handling capability driven by stringent
demands from both mobile broadband and the introduction of heterogeneous networks
(HetNets). Backhaul technology has been extensively investigated for legacy mobile
systems, but is still a topic that will dominate the research arena for next generation
mobile systems; it is clear that without proper backhauling, the benefits introduced by
any new radio access network technologies and protocols would be overshadowed.
Traditionally, the backhaul segment connects the RAN (radio access network) to
the rest of the network where the baseband processing takes place at the cell site.
However, with the onset of next generation networks, the notion of ‘fronthaul
access’ is also gaining momentum. The future technology roadmap points towards
SDN (software‐defined networks) and network virtualization as means of effectively
sharing resources on demand between different mobile operators, thus taking a
step towards reducing the operational and capital expenditure in future networks.
Moreover, the baseband processing will be centralized, allowing the operators tocompletely manage interference through coordinated resource‐management strategies. In
fact, 3GPP are today visualizing a C‐RAN (cloud-RAN) architecture, where the
evolved base stations are connected to the C‐RAN unit through communication
hauls, to what is referred to as the ‘fronthaul network’. Traditionally, fibre‐optic
technology is used to roll out the deployment of base stations; however, this comes
along with inherent limitations, including cost and lack of availability at many small
sites. This provides the impetus for radio solutions that can handle large volumes of
traffic on the fronthaul access, triggering the research community at large to find
alternative and advanced solutions that can supersede fibre.
The current work on backhaul and fronthaul technology is fragmented, and still
in its infancy. There are still giant steps to be taken towards developing concrete
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xii Preface
solutions to provide a modern communication haul for next generation networks,
which is also commonly referred to as 5G. This book aims to be the first of its kind to
hinge together the related discussions on the fronthaul and backhaul access under the
umbrella of 5G networks, which we will often refer to as the ‘communication haul’.
We aim to discuss these pivotal building blocks of the communication infrastructure
and provide a view of where it all started, where we are now in terms of LTE/LTE‐A
networking and the future challenges that lie ahead for 5G. In addition, this book
presents a comprehensive analysis of different types of backhaul/fronthaul technologies
while introducing innovative protocol architectures.
In the compilation of this book, the editors have drawn on their vast experience in
international research and being at the forefront of the communication haul research
arena and standardization. This book aims to be the first to talk openly about next
generation communication hauls, and will hopefully serve as a useful reference not
only for postgraduate students to learn more about this evolving field, but also to
stimulate mobile communication researchers towards taking further innovative strides
in this field and marking their legacy in the 5G arena.
Kazi Mohammed Saidul Huq
Jonathan Rodríguez
Instituto de Telecomunicações, Aveiro, Portugal
Acknowledgements
This book is the first of its kind tackling the research challenge on the communication
haul for legacy and emerging mobile communication networks, and the authors hope
that it will serve as a source of inspiration for researchers to drive new breakthroughs
on this topic. The inspiration for this book stems from the editors’ vast experience at the
forefront of European research on backhaul/fronthaul architecture for future wireless
systems, including the E-COOP project (UID/EEA/50008/2013), an interdisciplinary
research initiative funded by the Instituto de Telecomunicações (Portugal). However,
this work would not be complete if it weren’t for those who contributed along the
way. The editors would first like to thank all the collaborators that have contributed
with chapters toward the compilation of this book, providing complementary ideas
towards building a complete vision of the communication haul. Moreover, a heartfelt
acknowledgement is due to the members of the 4TELL Research Group at the Instituto
de Telecomunicações who contributed with useful suggestions and revisions.
Furthermore, the editors would like to acknowledge the Fundação para a Ciência e a
Tecnologia (FCT‐ Portugal) for the grant (reference number: SFRH/BPD/110104/2015)
that supported this work.
Kazi Mohammed Saidul Huq
Jonathan Rodríguez
Instituto de Telecomunicações, Aveiro, Portugal
1
Introduction: The Communication
Haul Challenge
Kazi Mohammed Saidul Huq and Jonathan Rodriguez
Instituto de Telecomunicações, Aveiro, Portugal
1.1 Introduction
Nowadays, the mobile Internet is a pervasive phenomenon that is changing social
trends and playing a pivotal role in creating a digital economy. This, in part, is driven
by advancements in semiconductor technology, which are enabling faster and more
energy‐compliant devices, such as smartphones, tablets and sensor devices, among
others. However, a truly smart digital world is still in its infancy and the current trends
are set to continue, leading to an unprecedented rise in mobile data traffic and
intelligent devices. In fact, according to an Ericsson report [1], a typical laptop will
generate 11 GB, a tablet 3.1 GB and a smartphone 2 GB per month by the end of 2018.
These figures represent the changing communication paradigm, where the end user
will not only receive data but generate data; in other words, the end user will become
a ‘prosumer’ running data‐hungry applications, for example, high‐definition wireless
video streaming, machine‐to‐machine communication, health‐monitoring applications
and social networking. Therefore, existing technology requires a radical engineering
design upgrade in order to compete with ever‐growing user expectations and to
accommodate the foreseen increase in traffic. The change will be driven by
market expectations, and the new technology being considered is fifth generation
(5G) communications [2].
Experts anticipate that 5G will deliver and meet the expectations of a new era in
wireless connectivity, and will play a key role in enabling this so‐called digital world.
Backhauling/Fronthauling for Future Wireless Systems, First Edition.
Edited by Kazi Mohammed Saidul Huq and Jonathan Rodriguez.
© 2017 John Wiley & Sons, Ltd. Published 2017 by John Wiley & Sons, Ltd.
2 Backhauling/Fronthauling for Future Wireless Systems
In contrast to legacy fourth generation (4G) systems, the widely accepted consensus
on the 5G requirement includes [3, 4]:
• Capacity: 1000x increase in area capacity;
• Latency: Less than 1 millisecond (ms) round trip time (RTT) latency;
• Energy: 100x improvement in energy efficiency in terms of Joules/bit;
• Cost: 10–100x reduction in cost of deployment;
• Mobility: Mobility support and always‐on connectivity of users that have high
throughput requirements.
To achieve these targets, all the key mobile stakeholders, such as operators, vendors
and the mobile research community, are contriving to reengineer the mobile
architecture in order to support higher‐speed data connectivity.
Small‐cell technology is an emerging deployment that is providing promising
results in terms of delivering fast connectivity due to the small distance between the
base station (BS) and the end user, whilst reducing energy consumption. Market use
cases of small cells such as the indoor femto cell have already become a success story,
so the question is, can we extrapolate the femto cell paradigm to the outdoor world?
In fact, current trends are suggesting that this is the way forward, with multi‐tier heterogeneous networks being a new design addition to the LTE‐Advanced standard
[5,6]. Here, multi‐tier radio networks (small‐cell tiers) play a pivotal role, coupled
with network coexistence approaches to reduce the interference between tiers.
Moreover, mobile technology will continue to evolve in this direction with the hyper‐
dense deployment of small cells providing hotspot islands of high data connectivity
coverage zones. This context will ask new questions from the research community in
terms of how to tunnel this traffic from the local serving base station towards the core
network. Typically, in legacy networks, the segment of the network that interconnects
the BS to the RAN (radio access network) to the EPC (evolved packet core) is called
the backhaul. Fibre optic lines or microwave links have fulfilled this role, with
limitations in terms of deployment cost and limited coverage area. However, mobile
technology is heading towards an era of virtualization and software‐defined
networking, where radio resources are allocated from a common pool to different
providers, and their management is centralized. This new era is, in fact, reflecting
parallels in the cloud computing world, with the onset of cloud services. Emerging
mobile networks are heading towards a C‐RAN (cloud radio access network) approach
[7, 8], where RRUs (remote radio units) and a centralized processing RAN core work
in synergy to provide coordinated scheduling, or, in other words, interference
management. This paradigm is changing the perception of the communication haul in
the network, from backhauling to incorporating both a back and fronthaul segment. In
this context, the backhaul dictates how the information is parried from the base
stations to the core network, whilst the fronthaul refers to the connectivity segment
between the C‐RAN core network and the small cell. Figure1.1 shows definitions of
BBU
(a)
(b)
X2 Sync
Layer 3
Layer 2
Layer 1
MME = Mobility management entity
SGW = Serving gateway
PGW = Packet data gateway
EPC = Evolved packed core
UE
UE
UE
UE
UE
UE
BS 1
BS 2
BS N
RRU 1
RRU 2
RRU N
RAN fronthaul
RAN fronthaul
RAN fronthaul
RAN backhaul
RAN backhaul
RAN backhaul
Aggregation switch Router
Aggregation point
BBU N
BBU 2
BBU 1
X2 Sync
Layer 3
Layer 2
Layer 1
BBU pool cloud
MME
Transpor t backhaul
PGW
SGW
Core network (EPC)
MME
Transpor t backhaul
PGW
SGW
Core network (EPC)
Figure1.1 Communication haul segments of (a) legacy and (b) emerging C‐RAN mobile network
4 Backhauling/Fronthauling for Future Wireless Systems
the backhaul and fronthaul segments pertaining to legacy and emerging C‐RAN
architectures.
The future enhanced communication haul (be it backhaul or fronthaul) for 5G is
expected to be deployed around 2020 in order to support the exponential growth in
wireless data that is forecast over the next decade. Therefore, there is substantial
market interest in the development of ground‐breaking backhaul and fronthaul
solutions that can not only enhance today’s networks, but also provide a coherent
interference management approach in emerging technologies such as C‐RAN and
beyond. This communication haul challenge provided the inspiration for this book
and its title: Backhauling/Fronthauling for Future Wireless Systems.
The book intends to bring together all mobile stakeholders, from academia and
industry, to identify and promote technical challenges and recent results related to
smart backhaul/fronthaul research for future communication systems such as 5G. It
provides an overview of current approaches to backhauling legacy communication
systems and explains the rationale for deploying future smart and efficient backhauling/fronthauling infrastructure from architectural, technical and business points of
view using real‐life applications and use cases. The book is intended to inspire
researchers, operators and manufacturers to render ground‐breaking ideas in the
newly emerging discipline of smart backhauling/fronthauling over future, ultra‐dense
wireless systems. Moreover, detailed security challenges are presented to analyse the
performance of smart backhauling/fronthauling for future wireless. It is clear that
smart backhauling/fronthauling deployment can offer a palette of interesting colours
capable of painting new business opportunities for mobile stakeholders for next
generation wireless communication systems. This is the first book of its kind on smart
backhauling/fronthauling for future wireless systems which updates the research
community on the communication haul roadmap, reflecting current and emerging
features emanating from the 3GPP group.
To guide the reader through this adventure, the book has the following layout. In
Chapter 2, a reference architecture for the future radio communication haul is
presented from a 5G perspective. 5G networks are anticipated to obtain Shannon‐
level and beyond throughput and almost zero latency. However, there are several
challenges to solve if 5G is to outperform legacy mobile platforms; one of these is the
design of the communication ‘haul’. Traditionally, the backhaul segment connects the
radio access network (RAN) to the rest of the network where the baseband processing
takes place at the cell site. However, in this chapter, we will use the concept of
‘ fronthaul access,’ which is recently gaining significant interest since it has the potential to support remote baseband processing based on adopting a cloud radio access
network (C‐RAN) architecture that aims to mitigate (or coordinate) interference in
operator‐deployed infrastructures; this eases significantly the requirements in
interference‐aware transceivers. To do this, we provide a reference architecture
that also includes a network and protocol architecture and proposes a so‐called
‘cloud resource optimizer’. This integrated solution will be the enabler for
Introduction: The Communication Haul Challenge 5
RAN‐as‐a‐Service, not only paving the way for effective radio resource management,
but opening up new business opportunities for virtual mobile service providers.
Emerging channel transmission approaches and the possibility of using higher
frequency bands, such as massive MIMO and millimetre‐wave (mmWave), respectively, are of paramount importance for future wireless systems and for the communication haul. Chapter3 introduces the fundamentals with regard to massive MIMO and
mmWave communication, and their suitability for small‐cell backhauling and
fronthauling. Furthermore, a performance analysis model for wireless backhauling
ofsmall cells with massive MIMO and mmWave communication is outlined. Using
this model, some numerical results on the performance of massive‐MIMO‐ and/or
mmWave‐based wireless backhaul networks are presented.
C‐RAN promises considerable benefits compared to decentralized network
architectures. Centralizing the baseband processing enables smaller radio access
points as well as cooperative signal processing and ease of upgrade and maintenance.
Further, by realizing the processing not on dedicated hardware, but on dynamic and
flexible general‐purpose processors, cloud‐based networks enable load balancing
between processing elements to enhance energy and cost efficiency. However,
centralization also places challenging requirements on the fronthaul network in terms
of latency and data rate. This is especially critical if a heterogeneous fronthaul is
considered, consisting not only of dedicated fibre but also of, for example, mmWave
links. A flexible centralization approach can relax these requirements by adaptively
assigning different parts of the processing chain either to the centralized baseband
processors or the base stations based on the load situation, user scenario and the availability of the fronthaul links. This not only reduces the requirements in terms of
latency and data rate, but also couples the data rate to the actual user traffic.
In Chapter 4, a comprehensive overview of different decentralization approaches
is given, and we analyse their specific requirements in terms of latency and data
rate. Furthermore, we demonstrate the performance of flexible centralization and
providedesign guidelines on how to set up the fronthaul network to avoid over‐ or
under‐dimensioning.
Heterogeneous backhaul deployment using different wired and wireless
technologies is a potential solution to meet the demand in small‐cell and ultra‐dense
networks. Therefore, it is of cardinal importance to evaluate and compare the
performance characteristics of various backhaul technologies in order to understand
their effect on the network aggregate performance and provide guidelines for system
design. In Chapter5, the authors propose relevant backhaul models and study the
delay performance of various backhaul technologies with different capabilities and
characteristics, including fibre, xDSL, mmWave and sub‐6 GHz. Using these models,
the authors aim to optimize the base station (BS) association so as to minimize the
mean network packet delay in a macro‐cell network overlaid with small cells.
Furthermore, the authors model and analyse the backhaul deployment cost and show
that there exists an optimal gateway density that minimizes the mean backhaul cost
6 Backhauling/Fronthauling for Future Wireless Systems
per small‐cell base station. Numerical results are presented to show the delay
performance characteristics of different backhaul solutions. Comparisons between
the proposed and traditional BS association policies show the significant effects of
backhaul on network performance, which demonstrates the importance of joint
system design and optimization for both the radio access and backhaul networks.
The small‐cell network (also called a HetNet) has been recognized as a potential
solution to offer better service coverage and higher spectral efficiency. However, the
dense deployment of small cells could cause inter‐cell interference problems and
reduce the performance gains of HetNets. Various techniques have been developed
in 4G for tackling inter‐cell interference. In particular, the inter-cell interference
coordination (ICIC) technique can coordinate the data transmission and interference
in two neighbouring cells. In Chapter6, the authors consider a HetNet consisting of
macro‐cell networks overlaid with small‐cell networks that access the same spectrum
simultaneously. Here, the HetNet architecture assumes macro cells and small cells
interconnected via a high‐speed fronthaul/backhaul connection. In particular, due to
the mobility of wireless subscribers, the load and data traffic are different in every
active macro and small cell. The conventional static enhanced ICIC (eICIC) mechanism cannot ensure that adapting the almost blank subframes (ABS) duty cycle
corresponds to the dynamic network condition. Only the dynamic eICIC mechanism
is suitable for this non‐static network traffic. Therefore, the authors aim to develop a
dynamic interference coordination strategy for eICIC for maximizing system utilities
under given QoS constraints. In contrast to the traditional eICIC mechanism, the
proposed method does not add any backhaul requirements. Computer simulations
show that the performance in various scenarios of the dynamic eICIC mechanism
with QoS requirements is better than a static eICIC approach and the conventional
dynamic eICIC mechanism.
Cell selection for joint optimization considering backhauling technology is needed
for future wireless systems. In this regard, Chapter 7 provides a comprehensive
analysis for joint optimization considering the backhaul in terms of cell selection.
This chapter considers heterogeneous cellular networks, where clusters of small cells
are locally deployed to create hotspot regions inside the macro‐cell area. Most of
theresearch on this topic has focused on mitigating co‐channel interference; however,
the wireless backhaul has recently emerged as an urgent challenge to enable ubiquitous
broadband wireless services in small cells. In realistic scenarios, the backhaul may
limit the amount of signalling that can be exchanged amongst neighbouring cells,
which aims to coordinate their operations in real time; furthermore, in highly loaded
cells (such as hotspots), the backhaul can limit the data rate experienced by the end
users. Here, the authors develop a novel cell‐association framework, which aims to
balance the users amongst heterogeneous cells to improve the overall radio and
backhaul resource usage and increase the system performance. The authors describe
the relationship between cell load, resource management and backhaul capacity
constraints. Then, the cell‐selection problem is expressed as a combinatorial
Introduction: The Communication Haul Challenge 7
optimization problem and two heuristic algorithms–called Evolve and Relax–are
presented to solve this dilemma. The analysis shows that Evolve converges to a near‐
optimal solution, leading to notable improvements with respect to the classic SINR‐
based association scheme in terms of throughput and resource utilization efficiency.
High‐speed and long‐range wireless backhaul is a cost‐effective alternative to a fibre
network. The ever‐increasing demand for high‐speed broadband services mandates
higher spectral efficiency and wider bandwidth to be adopted in the wireless backhauls. As wireless mobile networks evolve toward 5G, employing higher‐order modulation and performing multiband and multichannel aggregation for wireless backhauling
have become industry trends. However, commercially available wireless backhaul
systems do not meet the stringent requirements for both high speed and long range at
the same time. In Chapter8, the various system architectures for multiband and multichannel aggregation are discussed. The challenges for achieving high‐speed wireless
transmission in multiband and multichannel systems are addressed. These challenges
include: how to improve spectrum efficiency and power efficiency; how to prevent
inter‐channel interference; and how to ensure low latency in order to ensure resilient
packet delivery and load balancing.
Despite the significant benefits of C‐RAN technology in 5G mobile communication systems, C‐RAN technology has to face multiple inherent security challenges
associated with virtual systems and cloud computing technology, which may
hinder its successful establishment in the market. Thus, it is critical to address
these challenges in order for C‐RAN technology to reach its full potential and
foster the deployment of future 5G mobile communication systems. Therefore,
Chapter9 presents representative examples of possible threats and attacks against
the main components in the C‐RAN architecture in order to shed light on the
security challenges of C‐RAN technology and provide a roadmap to overcome the
security bottleneck.
In conclusion, we firmly believe this book will serve as a useful reference for early‐
stage researchers and academics embarking on this radio communication haul
odyssey, but beyond that, it targets all major 5G stakeholders who are working at the
forefront of this technology to provide inspiration towards rendering ground‐breaking
ideas in the design of new communication hauls for next‐generation systems.
References
[1] Ericsson (2013) Mobility report, June.
[2] Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K. and Zhang, J. C.
(2014) What Will 5G Be? IEEE Journal on Selected Areas on Communication, 32(6), 1065–1082.
[3] Huawei Technologies Co. (2013) 5G: A technology vision. White paper.
[4] Osseiran, A., Boccardi, F., Braun, V., Kusume, K., Marsch, P., Maternia, M., Queseth, O., Schellmann,
M., Schotten, H., Taoka, H., Tullberg, H., Uusitalo, M. A., Timus, B. and Fallgren, M. (2014)
Scenarios for 5G mobile and wireless communications: The vision of the METIS project. IEEE
Communications Magazine, 52(5), 26–35.
8 Backhauling/Fronthauling for Future Wireless Systems
[5] Parkvall, S., Dahlman, E., Furuskär, A., Jading, Y., Olsson, M., Wanstedt, S. and Zangi, K. (2008)
‘LTE Advanced–Evolving LTE towards IMT‐Advanced,’ Vehicular Technology Conference, 21–24
September, pp. 1–5.
[6] 3GPP (2011) ‘Feasibility Study for Further Advancements for E‐UTRA (LTE‐Advanced) (Release
10),’ TR 36.912, V10.0.0, March.
[7] China Mobile Research Institute (2011) ‘C‐RAN: The Road Towards Green RAN’. Technical report,
April. Available at: http://labs.chinamobile.com/cran/wp‐content/uploads/CRAN_white_paper_
v2_5_EN.pdf.
[8] Checko, A., Christiansen, H. L., Yan, Y., Scolari, L., Kardaras, G., Berger, M. S. and Dittmann, L.
(2015) Cloud RAN for Mobile Networks–A Technology Overview. IEEE Communications Surveys
Tutorials, 17(1), 405–426.
www.ebook3000.com
2
A C‐RAN Approach for5G
Applications
Kazi Mohammed Saidul Huq, Shahid Mumtaz and Jonathan Rodriguez
Instituto de Telecomunicações, Aveiro, Portugal
2.1 Introduction
Nowadays mobile Internet is a pervasive phenomenon. In the last decade, this
phenomenon, along with the market drive for novel software applications spurred by
the availability of smartphone handsets, has led to an unprecedented increase in data
traffic. Researchers and experts predict that this upward trend will continue as the 5G
community envisions new usage scenarios that involve connecting people, machines
and applications through a mobile infrastructure. For this reason, the current technology requires a radical change to cater for this new tidal wave of mobile data, which
has led us to the fifth generation (5G) communications era [1]. 5G will be expected to
deliver a new era of wireless broadband connectivity, shaped by emerging use cases
that aim to interconnect devices (the Internet of Things– IoT), enhance quality of
experience (QoE) for the end user in terms of traditional mobile connectivity and be
the main platform for addressing critical emergency infrastructures. 5G will play a
role in the digitalization of Europe, and key targets include: increasing the peak data
rate by 100 times, enhancing network capacity by 1000 times, increasing energy
efficiency by 10 times and reducing latency by 30 times [2], all of which represent
significant and challenging design requirements in contrast to the legacy 4G system.
To achieve these targets, mobile stakeholders (such as operators, carriers and manufacturers) are contriving to incorporate macro cells and small cells into the design of
the radio access infrastructure. This has forced system designers to reconsider the
Backhauling/Fronthauling for Future Wireless Systems, First Edition.
Edited by Kazi Mohammed Saidul Huq and Jonathan Rodriguez.
© 2017 John Wiley & Sons, Ltd. Published 2017 by John Wiley & Sons, Ltd.
10 Backhauling/Fronthauling for Future Wireless Systems
existing backhaul design of legacy 4G radio networks and to consider both a new
backhaul and fronthaul design for ultra‐dense heterogeneous networks (HetNets).
5G networks are increasingly perceived as carriers to support a fully fledged, data‐
centric application rather than voice‐centric applications. Hence, one of the principal
dilemmas operators are coming across nowadays is how to transform the existing
1
backhaul/fronthaul
infrastructure into an Internet Protocol (IP)‐based backhaul/fronthaul solution for hyper‐dense small‐cell deployment. With regard to the hauling of
data, the continued use of fibre will give rise to the same problems as experienced
today, which are mainly economic but also involve restrictions on deployment due to
the geographical locations of transceiver cell sites. Millimetre‐wave (mmWave) backhaul/fronthaul is an option, but technological and regulatory challenges are yet to be
addressed for its successful deployment. Another emerging solution is to exploit the
interworking and joint design of open access and backhaul/fronthaul network
architecture for hyper‐dense small cells based on cloud radio access networks
(C‐RANs) [3]. This requires smart backhauling/fronthauling solutions that optimize
their operations jointly with the access network optimization protocol. The availability, convergence and economics of smart backhauling/fronthauling systems
arethe most important factors in selecting the appropriate backhaul/fronthaul technologies for multiple radio access technologies (including small cells, relays and distributed antennas) and heterogeneous types of excessive traffic in the future cellular
network. However, in this chapter, we will use the concept of ‘fronthaul access’,
which is recently gaining significant interest since it has the potential to support
remote baseband processing based on adopting a C‐RAN architecture that aims
to mitigate (or coordinate) interference in operator‐deployed infrastructures; this
eases significantly the requirements in interference‐aware transceivers. Under the
umbrella of a C‐RAN scenario, we introduce the notion of a ‘cloud resource optimizer’, which requires reengineering the medium access control (MAC) to provide a
unified solution. The emergence of wireless fronthaul solutions widens the appeal for
small‐cell deployments, because a fibre‐only solution–the technology typically used
for fronthaul–is too expensive or just not available at many small‐cell sites. Moreover,
we will also present a few ideas of potential applications for C‐RAN‐based mobile
systems such as virtualization of device‐to‐device (D2D) services.
Following the introduction, this chapter is organized as follows. In Section2.2, we
provide a brief overview of different types of backhauling/fronthauling technologies,
and in particular, guide the interested reader through the transition from existing to
emerging communication haul technologies. In Section2.3, we present network and
protocol architecture for the baseline 3GPP coordinated multi‐point (CoMP) system,
as a starting point, and then evolve this towards the emerging C‐RAN‐based
architecture in Section2.4, which is widely seen as the next step on the mobile evolutionary landscape and indeed one step towards the 5G communication platform.
1
The terms backhaul and fronthaul are used interchangeably in this chapter.
A C‐RAN Approach for5G Applications 11
Based on this platform, we develop an integrated solution for the cloud resource
optimizer, which defines a unified MAC. Section2.5 takes this design to the next
level by using device‐to‐device (D2D) communication as a use‐case application by
introducing a new small‐cell paradigm based on ‘on‐demand’ virtual small cells for
coping with the dynamic variations in mobile traffic throughout the day; which is also
an emerging scenario within the context of 5G. Finally, Section2.6 summarizes and
concludes this chapter.
2.2 From Wired toWireless Backhaul/Fronthaul Technologies
In this section we provide a brief summary of the different kinds of backhaul/fronthaul
technologies which are widely accepted and used by operators and service providers.
According to [4, 5] hauling technologies are divided into two major categories: wired
and wireless. Figure 2.1 shows the classification of backhaul technologies. For
example, in the case of the wired backhaul, copper cables are the conventional medium
whereas optical fibres are touted as an emerging hauling medium.
In wired backhaul, two types of physical media are widely used: copper cables and
optical fibres. Copper cables are the conventional hauling medium between base
transceiver stations (BTSs) and the base station controller (BSC) [4]. Currently,
copper cables are being replaced by optical fibres due to their higher rates and low
latency. Traditional copper‐based backhauling is used in digital subscriber line (DSL)
access networks [6]. The alternative to copper for mobile backhaul is fibre‐based
solutions that can provide almost unlimited capacity. The main fibre access options
include GPON (gigabit passive optical network), carrier Ethernet and point‐to‐point
(PTP) fibre [7].
There is another type of backhaul: wireless backhaul. This type of communication haul can be distinguished by the different frequency bands. Although the
channel traits are different in this type of backhaul owing to different bands, each
technology has its own merits and demerits. One very significant similarity amongst
these technologies over wired backhaul is fast and relatively cheap deployment. For
example, free space optics (FSO) use light to transmit data, but unlike relying on
fibre as a transmission medium, free space propagation is applied [8]. FSO links
Copper
Wired
Optical fibre
Backhaul/fronthaul
Wireless
Free space optics
Figure2.1 Different types of backhaul/fronthaul
SatelliteMicrowave mmWave Relaying
12 Backhauling/Fronthauling for Future Wireless Systems
also create nearly zero interference between each other; the reason being the narrow
beam width. Microwave communication haul technologies utilize different bands of
carrier frequencies, ranging from 6 GHz to 42 GHz [5]. Microwave uses licensed
spectrum which, in turn, enhances deployment time and cost [9]. Recently, a new
paradigm is emerging under the wireless backhaul category: millimetre‐wave
(mmWave) technology [10]. The explosive developments in circuit technologies
have led to mmWave now being considered a viable option, and indeed foreseen as
shaping next‐ generation small‐cell wireless backhaul. There are three types of
frequency bands available for mmWave –60, 70/80 and 90 GHz [10]. These high
carrier frequencies can enable multi‐Gbps data rates [5]. As the 60 GHz band is
unlicensed and the higher bands only require an easy and inexpensive licensing
process, the links can be deployed much faster and at lower cost [11]. The relay
backhaul is another alternative, and is mainly used in the access link. Its inherent
advantage isthat relays use the same transmission technology and licences as the
access link.However, they also have similar shortcomings in terms of range (up to
a few kilometres), capacity (a few hundred Mbps) and interference [5]. Satellite
backhaul provides an answer for certain terrain where no other backhaul technologies are viable to deploy [4]. In general, T1/E1 is the physical transmission medium
over satellite links for cellular backhaul [12].
2.3 Architecture forCoordinated Systems According
toBaseline 3GPP
The C‐RAN incorporates both a joint signal processing capability and the resource
optimization of data belonging to different users which conventional coordinated
3GPP techniques cannot carry out due to high complexity and signal overhead during
coordination. Data and signalling are exchanged between different base stations
(BSs) through links which are usually capacity limited. This sometimes makes the
signalling exchange infeasible. In this section, we describe network and protocol
architecture of a coordinated system according to 3GPP.
Figure2.2 shows the network architecture of a coordinated 3GPP system. This
baseline scenario is based on BS cooperation, which recently attracted much interest
from the research community. In the 3GPP LTE‐Advanced, it is referred to as
coordinated multi‐point (CoMP) transmission and is being studied actively in LTE
release 11 [13].
The inter‐BS cooperation has been presented as an effective approach to mitigate
inter‐cell interference and hence improve cell edge throughput performance. Among
the several categories of CoMP technologies [14], we focus only on downlink joint
transmission (JT) CoMP in this chapter. In JT CoMP, downlink data can be simultaneously transmitted from multiple BSs to user equipment (UE). It is well known
that the cell‐edge performance is dramatically improved by JT CoMP. However,
A C‐RAN Approach for5G Applications 13
UE
RRC IP
RLC MAC
Cell
1
BS
S1 S1
Layer 3
Layer 2
Layer 1PHY
Uu
X2-AP
SCTP
RRC IP
MAC
RLC
PHY
EPC
X2
GTP-U
UDP
RRC
IP
RLC MAC
PHY
Uu
Figure2.2 Network architecture of baseline 3GPP CoMP system
Cell
UE
1
1
BS
1
UE
X2
BS
Cell
2
2
Figure2.3 Depiction of a JT CoMP use case
UE
BS
2
RRC
RLC MAC
Cell
Layer 3
Layer 2
Layer 1 PHY
IP
2
theperformance of JT CoMP can be degraded in the absence of a high‐speed and
low‐latency backhaul network [15].
This scenario is based on a distributed approach, where each BS has its own layers
of LTE protocol stack (i.e., physical (PHY), medium access control (MAC), radio link
control (RLC), packet data convergence protocol (PDCP)) and each BS scheduler
controls its own UE in the cell. The BSs are connected via an IP‐based X2 interface,
which acts as an asynchronous communication link for managing JT CoMP operation; this interface is also used for distributing downlink data between BSs. These BSs
are attached to the core network via the S1/S5 interface. Moreover, we assume that
two BSs are synchronized by a global positioning system (GPS).
To understand the underlying mechanics of CoMP, Figure 2.3 illustrates a JT
CoMP use case, where a user migrates between cells in an LTE network. Assume that
the UE is located at the cell centre in cell
receiving a downlink signal from BS
between cell
and cell2, the UE automatically triggers JT CoMP to improve the
1
performance at the cell edge by receiving a downlink signal from BS
. Finally, when the UE moves to cell2, the UE automatically terminates JT CoMP
BS
1
operation and BS
becomes the communication link.
2
, initially. The UE is attached to BS1 and
1
. However, as the UE moves to the cell edge
1
in addition to
2
14 Backhauling/Fronthauling for Future Wireless Systems
UE
EPC
Data
Local sch
Resource
management
Co-ord sch
PDCP
RLC
MAC
PHY
Data
X2
resource
management
Co-ordinated
signalling
X2
Data forwarding
ControlMAC Synchronization
Figure2.4 Protocol architecture of baseline 3GPP CoMP system
PDCP
RLC
MAC
PHY
Local sch
Resource
Co-ord sch
management
Figure2.4 shows the protocol architecture to realize the simultaneous transmission
scheme based on the LTE standard. The UE reports two kinds of reference signal
received power (RSRP) messages to BS
the difference between RSRP
and RSRP2 (in dBm) is smaller than the predefined
1
: RSRP1 from BS1 and RSRP2 from BS2. If
1
CoMP threshold, then JT CoMP is started; if the difference exceeds the predefined
CoMP threshold, then JT CoMP is terminated.
When JT CoMP is triggered, the scheduler in BS
part in BS
to make sure that the radio resources are available for JT CoMP (see the
2
will first check with its counter-
1
heavy black line in Figure2.4). During JT CoMP, the downlink data are processed in
the following manner (see black arrows). First, PDCP, RLC and MAC are applied
tothe downlink data in BS
At the same time, the scheduler in BS
and the MAC protocol data unit (MAC‐PDU) is created.
1
provides the joint transmission time as well as
1
control information regarding MCS (modulation and coding scheme), radio resource
to be used and antenna mapping for the MAC‐PDU. The joint transmission time and
A C‐RAN Approach for5G Applications 15
the control information are then attached to the MAC‐PDU and duplicated; one of
them is sent to PHY in BS
and other is sent to PHY in BS2 via the X2 interface. The
1
PHY processing is carried out at both BSs in parallel. Finally, the MAC‐PDU is
simultaneously transmitted from the two synchronized BSs at the specified joint
transmission time.
To transport a MAC‐PDU from BS
to BS2, the MAC‐PDU is encapsulated by the
1
GTP tunnelling protocol. The joint transmission time and the control information that
should be attached to this MAC‐PDU are included in a MAC‐control element (MAC‐
CE) in the MAC‐PDU.
2.4 Reference Architecture forC‐RAN
To overcome the limitations of CoMP, a holistic architectural change is expected via
connecting the BSs to central clouds. Unlike the baseline CoMP scenario described in
the previous section, in the C‐RAN most of the signalling takes place in the cloud and
is shared among sites in a pool of virtualized baseband processing units (BBUs). Due
to the fact that fewer BBUs are required in the C‐RAN compared to the traditional
architecture (legacy 3GPP scenario), C‐RAN also has the potential to reduce the cost of
network operation. This type of network architecture also improves scalability and
makes BBU maintenance easier. Different operators can share this cloud BBU pool,
which allows some to rent the RAN as a cloud service. Since BBUs from different sites
are co‐located in one pool, they can communicate with lower delays. This brings to the
forefront many other advantages, since existing mechanisms introduced in LTE‐A to
increase spectral efficiency, interference management and throughput, such as enhanced
inter‐cell interference coordination (eICIC) and CoMP, are greatly facilitated here.
2.4.1 System Architecture forFronthaul‐based C‐RAN
Emerging scenarios in cell deployment are heading towards the notion of cloud radio.
In this section we provide the reference system model for the C‐RAN scenario with
the description of its components. C‐RAN is a novel mobile technology that separates baseband processing units (BBUs) from radio front‐ends such as remote radio
units (RRUs). In this technology, BBUs of several BSs are positioned in a central
entity to form aBBUpool where the radio front‐ends of those BSs are deployed at
the cell sites [16–18]. Therefore, this new framework unfolds a new paradigm for
algorithms/ techniques that require centralized and cooperative processing. However,
the deployment of this new technology faces several potential research challenges,
which include latency, efficient fronthaul design and radio resource management for
a converged network.
Fronthaul enables a C‐RAN architecture in which all the BBUs are placed at a
distance from the cell site. The fronthaul transports the unprocessed RF signal from
16 Backhauling/Fronthauling for Future Wireless Systems
the antennas to the remote BBUs. While the fronthaul requires higher bandwidth,
lower latency and more accurate synchronization than the backhaul, it does support
more efficient use of RAN resources; when coupled with legacy interference and
mobility management tools, this can significantly minimize interference in the structured part of the network, including multi‐tier cell interference.
The general system model of the fronthaul‐based C‐RAN scenario is illustrated in
Figure 2.5, and consists of three main components [18], namely: (i) a centralized
BBU pool, (ii) remote radio units (RRUs) with antennas and (iii) a transport link, that
is a fronthaul network which connects the RRUs to the BBU pool. The RRU provides
the interface to the fibre as well as performing digital processing, digital‐to‐analogue
conversion, analogue‐to‐digital conversion, power amplification and filtering [16].
The distance between the RRU and the BBU can be extended up to 40 km, where the
ceiling range emanates from the processing and propagation delay. Optical fibre,
mmWave and microwave connections can be used. In the downlink, the RRUs transmit
the RF signals to the UEs, or in the uplink the RRUs carry the baseband signals from
the UEs to the BBU pool for further processing. The BBU pool is composed of BBUs
which operate as virtual base stations to process baseband signals and optimize
thenetwork resource allocation for one RRU or a set of RRUs. The fronthaul links
can constitute different technologies, namely wired (fiber → ideal) and wireless
(mmWave → non‐ideal). One can easily add or update any number of BBUs in
thiscloud depending on the needs and cell planning of the network operator. This C‐
RAN‐based architecture is also more energy efficient than the CoMP‐based scenario
due to reduced power consumption at the cell sites. In the C‐RAN network architecture,
no additional power is needed in cell sites other than for RRU operation.
By enabling joint processing in the cloud, key research challenges emerge related
to joint provisioning of resources between the different BBUs. This leads us to the
design of a so‐called ‘cloud resource optimizer’.
2.4.2 Cloud Resource Optimizer
In this section we present the proposed cloud resource optimizer for the C‐RAN.
Interconnections and functions split between BBUs and RRUs are depicted in
Figure 2.6. Unlike a CoMP resource management module, where all the resource
management entities are separated for different BSs, this resource optimizer unifies
all the resource management operation including allocation, interference management
and signalling for different BBUs in the cloud pool. Inside this cloud resource optimizer, the PHYs from different RRUs are merged into one common MAC, control
(Ctrl) and Synchronization (Sync) entity. This operation prompts us to develop a new
MAC approach for this cloud‐based system. The MAC works as an enabler between
different types of radio access technologies (RAT) such as LTE (IMT technology) and
WiFi (non‐IMT technology).
Microwave/mmWave
mmWave/optical fibre
Fronthaul
BBU N
BBU 2
BBU 1
X2 Sync
Layer 3
Layer 2
Layer 1
Fronthaul
BBU pool cloud
MME
Copper
PGW
SGW
Core network (EPC)
Fronthaul
RRU 1
RRU 2
RRU N
Figure2.5 Operator’s perspective on the fronthaul‐based C‐RAN scenario
18 Backhauling/Fronthauling for Future Wireless Systems
2
1
EPC
Data
PDCP
RLC
Unified MAC
MAC Ctrl Sync
Cloud Resource Optimizer
PHY
I/Q I/Q
RRU
PHY
RRU
Figure2.6 Architecture of the cloud resource optimizer
We consider a novel, unified MAC frame for our C‐RAN scenario in Figure2.7,
unlike in legacy CoMP where each RAN has its own MAC. The shift in engineering
design to introduce the presence of a global MAC entity will not only improve the
efficiency (both spectrum and energy) of the system, but take a step towards reducing
the overall interference in the network. This unified MAC will be a modified version
of an existing LTE MAC frame described in [19].
As can be seen in Figure2.7, there are several MAC‐CEs in both the downlink and
uplink MAC. Following Table1 and Table2 from the 36.321 standard [19] (shown
here in Tables2.1 and 2.2), we can see the logical channel ID (LCID) types of MAC
header. The parts indicated by the bold rectangle emphasize the LCID values for the
various MAC‐CEs.
We define a new MAC‐CE for this purpose. We use the reserved element field for
specifying the unified frame, and this is indexed in the MAC‐PDU sub‐header by an
LCID value equal to 11001 in the uplink. The new element is called a unified frame
and is appended to the existing LCID values, such as the common control channel
(CCCH), cell radio network temporary identifier (C‐RNTI) and the padding.
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