Luận án tiến sĩ tiếng anh Investigations on key technologies for LTE network optimization

学校代码: 10286
分类号:
密 级:

TN929.5
技术保护一年（2016 年 1 月 1 日—2017 年 1 月 1 日）

U D C:

621.3

学 号:

129734

INVESTIGATIONS ON KEY TECHNOLOGIES
FOR LTE NETWORK OPTIMIZATION

研究生姓名：

PHAN NHU QUAN

导 师 姓 名：

潘志文 教授

申请学位类别

博士

一级学科名称

信息与通信工程

论文答辩日期 2015 年 12 月 16 日

二级学科名称

通信与信息系统

学位授予日期 20

答辩委员会主席

学位授予单位

陈明教授

评 阅 人

2015 年 12 月 25 日

东 南 大 学

年

月

日

博士学位论文

INVESTIGATIONS ON KEY TECHNOLOGIES
FOR LTE NETWORK OPTIMIZATION

专 业 名 称：信息与通信工程

研究生姓名：PHAN NHU QUAN

导 师 姓 名：潘志文

ii

教授



INVESTIGATIONS ON KEY TECHNOLOGIES FOR
LTE NETWORK OPTIMIZATION

A Dissertation Submitted to
Southeast University
For the Academic Degree of Doctor of Engineering

BY
PHAN NHU QUAN

Supervised by
Prof. PAN ZHI WEN

School of Information Science and Engineering

Southeast University
Dec 2015
iv


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摘要
随着无线互联网的快速发展，无线业务量呈指数倍增长，使得服务提供商必须不断
地对无线网络覆盖进行优化，提升网络的系统容量，以满足用户的服务需求。为达到上
述目标，可以采用的主要技术方法有：修改系统参数设置、收发站开/关、根据负载状
况调整发送功率、优化小区布局、依据地形或用户密度调整天馈单元、安装大规模天线、
调整天线参数如倾角等。
本论文主要研究基站天线倾角调整算法，以实现包括网络覆盖优化、网络容量提升
和网络负载均衡在内的无线网络性能优化。
本论文主要包括以下研究内容：
第一章介绍论文的研究背景和研究意义。介绍了 LTE 网络中的自组织网络技术及
其特性，包括自配置、自优化和自愈特性。详细阐述了自优化中的网络覆盖及容量优化
(CCO)和负载均衡(LB)优化及其特征，并指出覆盖及容量优化(CCO)和负载均衡(LB)是
本文研究的关键问题。此外，还详细介绍了天线方向图和天线倾角调整的基本原理。
第二章研究 LTE 网络的覆盖问题，提出基于 eNB 天线倾角(ATA)调整的网络覆盖
优化算法。覆盖优化算法的性能指标是 eNB 覆盖的移动台 (MS)数目，该数目由 MS 测
量到的参考信号接收功率(RSRP)决定。本章通过最大化 eNB 覆盖的 MS 数目优化网络
覆盖，提出一种基于改进粒子群优化(MPSO)算法的网络覆盖优化算法。在 MPSO 中存
在一群粒子，每个粒子对应一组天线倾角集合，适应度函数由被服务的 MS 数目决定，
进化速度为每次迭代中 ATA 的调整尺度。仿真结果表明，与固定倾角相比，得益于提
出的天线倾角优化算法，基站服务的 MS 数目增加了 7.2%，接收信号质量提升 20dBm，
并且系统吞吐量也得到了 55Mbps 的有效提升。
第三章研究 eNB 负载约束及用户速率需求对网络覆盖的影响，提出考虑网络负载
约束的网络覆盖优化算法。虽然按照前一章的方法调整 ATA 能够有效提升整个网络覆
盖，但在 eNB 负载约束下，一些 eNB 过载导致一些用户的服务无法得到满足。因此，
在第三章中，提出考虑网络负载约束的网络覆盖优化算法。定义无线网络的覆盖能力为
综合考虑移动台 RSRP 和 eNB 负载约束的被服务 MS 数目，通过优化网络负载约束下

被服务的 MS 数目优化网络覆盖。提出一种基于 MPSO 的覆盖优化算法，该算法考虑
网络负载约束，通过调整 eNB 的 ATA 来最大化 eNB 服务的用户数。仿真结果表明，得
益于提出的算法，每个 eNB 服务的用户数量显著增加，系统吞吐量得到了显著提升，
并且网络平均负载和带宽效率也得到了改善。
第四章研究 LTE 网络的负载均衡问题，通过优化 eNB 的 ATA 来实现 LTE 网络的
负载均衡。以简氏公平系数作为评价网络负载均衡的标准，本章提出了基于 MPSO 算
法的负载均衡算法，通过联合优化 eNB 的 ATA 获得 LTE 网络负载均衡。仿真表明，所
i


提出的负载均衡算法可以有效实现负载均衡，显著改善了呼叫阻塞率，并且明显地增加
了网络带宽效率。
第五章研究 LTE 网络覆盖和负载均衡的联合优化问题。如果不考虑负载均衡，仅
考虑网络负载约束，优化 eNB 的 ATA 可能会出现以下情况：某信道条件较差的用户接
入负载较重的 eNB 并在该 eNB 内占用过多的资源，然而该用户附近还有一个低负载
eNB 没有得到利用。这种情况会使得网络资源无法得到有效利用，出现小区间负载不均
衡的问题。在第五章中为了在改善 eNB 覆盖的同时保证 LTE 网络负载均衡，通过联合
考虑覆盖因子 (CF)和负载均衡指标(LBI)来实现 eNB 覆盖和负载均衡的联合优化，其中
覆盖因子反映 eNB 的覆盖能力，负载均衡指标通过简氏公平系数进行评估，反应网络
负载均衡能力。将覆盖和负载均衡问题联合建模为一个多目标优化函数，提出一种基于
MPSO 的 ATA 调整方案。仿真结果表明，所提方案在有效增加网络覆盖的同时，能显
著提升负载均衡和网络带宽效率，并且网络吞吐量也得到了有效改善。

关键词：LTE 网络，网络优化，天线倾角，覆盖优化，负载均衡，改进粒子群算法。

ii


ABSTRACT
The exponential increase in the traffic volume forces the services providers unavoidably

facing with constantly evolving the wireless network system to satisfy the user demands, such
as to optimize the coverage of Evolved Node Base Station (eNB), and increase the capacity of
the network. By changing the system parameters, or switching on/off the base transceiver
stations, or adjusting the transmission power, or suitably rearranging cell layout, or replacing
antenna elements according to the topographical or the user density in urban or rural areas, or
installing massive MIMO (Multiple Input Multiple Output) or adjusting the antenna parameters
such as ATA are important ways to achieve the above goals.
In this dissertation, we investigate the adjustment of antenna tilt angle of base station to
optimize the performance for LTE networks, including the coverage and capacity optimization
and load balancing.
The main works of this dissertation are follows:
In Chapter 1, the research background and research significance are introduced. The selforganizing networks technologies and its features including self-configuration, selfoptimization and self-healing in LTE network are also introduced. Self-optimization is detailed
including its use cases such as the Coverage and Capacity Optimization (CCO), and Load
Balancing (LB) optimization. CCO and LB are two key issues in this study. Also, the
fundamental of antenna pattern and its tilt angle are introduced.
In Chapter 2, the coverage problem in LTE networks is investigated and a network
coverage optimization algorithm based on the Antenna Tilt Angle (ATA) adjustment of the
eNBs is proposed. The number of Mobile Stations (MS) under the coverage of eNB is
determined by the Reference Signal Received Power (RSRP) measured from MS, and is
considered as the performance metrics for coverage optimization algorithm. In this chapter, the
network coverage is optimized by maximizing the number of MS under the coverage of eNBs
and a Modified Particle Swarm Optimization (MPSO) based tilt angle adjusting algorithm for
coverage optimization is proposed. In MPSO, a swarm of particles known as the set of ATAs is
available, the fitness function is defined as the total number of the served MSs, and the
evolution velocity corresponds to the tilt angles adjustment scale for each iteration cycle.
Simulation results show that compared with the fixed tilt angles, the number of served MSs by
base stations is significantly increased by 7.2%, the quality of received signal is considerably
improved by 20 dBm, and particularly the system throughput is also effectively increased by
55 Mbps benefiting from the proposed algorithm.
In Chapter 3, the effect of the load constraint and the requirements of MSs is investigated,

and a coverage optimization algorithm considering the load constraint of eNBs is proposed.
Although adjusting the ATA according to Chapter 2 can efficiently improve the network
coverage, but under the load constraint, the service requirements of some MSs might not be
met because of the overload of the eNBs. Therefore, the network coverage optimization
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algorithm considering the network load is proposed in Chapter 3. The coverage ability of the
wireless network is defined as the number of served MSs of eNBs considering both the RSRP
measured from the MSs and the load constraint of eNBs, and the network coverage is
optimized by optimizing the number of served MSs under the constraint of the network load.
An MPSO-based coverage optimization algorithm that adjusts the ATAs of eNBs considering
the network load to maximize the number of users served by eNBs is proposed. Simulation
results show that both of the number of served users by each eNB and the system throughput
are significantly increased. As well, the average load and the bandwidth efficiency of the network are improved benefiting from the proposed algorithm.
In Chapter 4, we investigate the problem of load balancing optimization. The load balance
of the LTE network is achieved by optimizing the ATAs of the eNBs. Jain’s fairness index is
used to evaluate the load balance of the network. An MPSO-based load balancing algorithm is
proposed. The load balance of the network is achieved by cooperatively optimizing the ATAs
of the eNBs. Simulations show that the proposed approach can efficiently improve load
balancing, and significantly improves the call blocking rate, the network bandwidth efficiency.
In Chapter 5, the joint coverage and load balancing optimization problem is investigated.
Without consideration of the load balancing, adjusting the ATAs of the eNBs with the
constraints of network load may result in the following problem: some users in the poor
channel condition access the heavy load eNB and occupy too many resources in the eNB,
however, the light load eNB nearby these users will be under used. This results in load
imbalance problem between eNBs. Therefore, to further improve the coverage of eNB, and
simultaneously guarantee the even distribution of load in the LTE networks, in Chapter 5, we
jointly optimize the coverage of eNB and load balancing by considering the Coverage Factor
(CF) and Load Balancing Index (LBI). The coverage factor represents the coverage ability of

eNB, and load balancing is represented by load balancing index such as Jain’s fairness index.
We formulate the coverage and load balancing problem as a multi-objective optimization
function, and an MPSO algorithm based ATAs adjusting scheme is proposed. Simulation
results show that our proposed algorithm can efficiently increase the network coverage. This
significantly improves the load balancing, and appreciably increases the network bandwidth
efficiency. Also, the system throughput is considerably improved benefiting from the proposed
algorithm.

Keywords: LTE Networks, Network Optimization, Antenna Tilt Angle, Coverage
Optimization, Load Balancing and Modified Particle Swarm Optimization.

iv


ACKNOWLEDGEMENT
After four years of effort and hard work, first and foremost, I would like to express my
sincere gratitude and my deepest appreciation to those who have given me their support and
love.
This dissertation would not have accomplished without my supervisor. For that reason, I
would like to express my sincere gratitude to my main advisor, Prof. Pan Zhiwen, for his
support, encouragement, assistance, patience, great and wide knowledge, and personal
guidance. They all have been of great value to me, so I am proud of to have him as my advisor.
I would also like to thank all the committee members of my dissertation: Prof. Liu Nan, Dr.
Jiang HuiLin, Dr. Bui ThiOanh and Dr. Li Pei, for the time they have spent on reading my
Ph.D. dissertation and their deeply understanding comments.
My thankfulness also goes to the National Mobile Communications Research Laboratory
members. It was an honor to me to be a part of such a wonderful department and community.
I would also like to thank and appreciate my beloved parents: my father and my mother for
their teachings, encouragement, assistance, support, patience, continued unconditional love,
constant source of motivation and prayers for me to become a successful and better person.

I am also thankful to my beloved siblings: my brothers for always being my great role
models and setting high standards for me. I would also like to express my passion to my sisters,
for being always loving, kind and supportive. I am very happy with having such wonderful
family members.
Finally, and most importantly, I would also like to thank my wife, Vu thiThuTrang for her
understanding, unconditional support, always lifting my spirit, and great patience over all these
years. Specially, I would like to thank my beloved kids, Phan thiThuyDuong and Phan
TrungKien for being funny and lighting up my life. I could have never successfully completed
my academic dream without their love.

DEDICATION
I would like to dedicate this doctoral dissertation to my parents, brothers, sisters, my wife,
my daughter and my son who have given me their love, encouragement and support throughout,
for which my mere expression of thanks likewise does not suffice.

v


vi


TABLE OF CONTENTS
摘要 ................................................................................................................................................... iv
Abstract .............................................................................................................................................. iii
Acknowledgement ............................................................................................................................... v
Dedication ........................................................................................................................................... v
Table of Contents ............................................................................................................................... vii
List of Figures..................................................................................................................................... ix
List of Tables ...................................................................................................................................... xi
List of Abbreviations ........................................................................................................................ xiii

Chapter 1. Introduction ........................................................................................................................ 1
1.1.

Background .......................................................................................................................... 1

1.2.

Introduction To Self-Organizing Networks ........................................................................... 1

1.2.1.

Architecture of LTE system .......................................................................................... 1

1.2.2.

Overview of SON ......................................................................................................... 2

1.2.3.

Base Station Antenna and ATA ..................................................................................... 8

1.2.3.1.

Introduction .............................................................................................................. 8

1.2.3.2.

Antenna Parameters .................................................................................................. 9

1.2.3.3.

Antenna Radiation Pattern ........................................................................................11

1.3.

Thesis Motivation ................................................................................................................13

1.4.

Recent Progresses in Related Areas .....................................................................................14

1.4.1.

Coverage and Capacity Optimization ...........................................................................14

1.4.2.

Load Balancing ............................................................................................................16

1.4.3.

PSO algorithm .............................................................................................................18

1.5.

Contributions .......................................................................................................................19

1.6.

Dissertation Outline .............................................................................................................20

Chapter 2. An MPSO-Based Antenna Tilt Angle Adjusting Scheme for LTE Coverage Optimization ..23
2.1.

Introduction .........................................................................................................................23

2.2.

System Model and Problem Formulation .............................................................................24

2.2.1.

Antenna Down Tilt Angle ............................................................................................25

2.2.2.

Path-loss ......................................................................................................................26

2.2.3.

Shadow Fading Model .................................................................................................26

2.2.4.

The Number of MSs Served by eNB ............................................................................27

2.3.

MPSO Based ATA Adjusting Algorithm .............................................................................29

2.3.1.

Overview of Particle Swarm Optimization (PSO) .........................................................29

2.3.2.

MPSO Based ATA Adjusting Algorithm ......................................................................30
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2.4.

Simulation Results ............................................................................................................... 33

2.5.

Conclusions ......................................................................................................................... 39

Chapter 3. Coverage Optimization of LTE Networks Based on Antenna Tilt Adjusting Considering
Network Load ..................................................................................................................................... 41
3.1.

Introduction ......................................................................................................................... 41

3.2.

System Model and Problem Formulation ............................................................................. 43

3.2.1.

The Number of Users Served by eNB with the Constraint of Network Load ................. 43

3.3.

MPSO-Based ATA Adjusting Algorithm ............................................................................. 46

3.4.

Simulation Results ............................................................................................................... 49

3.5.

Conclusions ......................................................................................................................... 55

Chapter 4. Load Balancing Optimization Based on Tilt Adjusting in LTE Networks ........................... 57
4.1.

Introduction ......................................................................................................................... 57

4.2.

System Model ..................................................................................................................... 58

4.2.1.

System Model .............................................................................................................. 58

4.2.2.

Link Model .................................................................................................................. 58

4.3.

Problem Formulation ........................................................................................................... 60

4.4.

Algorithm ............................................................................................................................ 60

4.5.

Simulation Result and Analysis ........................................................................................... 63

4.6.

Conclusions ......................................................................................................................... 68

Chapter 5. Joint Load Balancing and Coverage Optimizing Based on Tilt Adjusting in LTE Networks 69
5.1.

Introduction ......................................................................................................................... 69

5.1.1.

Handover Procedure .................................................................................................... 70

5.1.2.

Load Balancing Mechanism ......................................................................................... 70

5.2.

System Model ..................................................................................................................... 72

5.2.1.

System Model .............................................................................................................. 72

5.2.2.

Link Model .................................................................................................................. 73

5.3.

Problem Formulation ........................................................................................................... 75

5.4.

Algorithm ............................................................................................................................ 75

5.5.

Simulation Result and Analysis ........................................................................................... 79

5.6.

Conclusions ......................................................................................................................... 85

Chapter 6: Conclusion and Future Work ............................................................................................. 87
6.1.

Conclusion .......................................................................................................................... 87

6.2.

Future Work ........................................................................................................................ 88

Bibliography ....................................................................................................................................... 89
Publication ......................................................................................................................................... 99
PATENT ............................................................................................................................................ 99
viii


LIST OF FIGURES
Figure 1. 1: Architecture of LTE Network ............................................................................................ 2
Figure 1. 2: Self-Organizing Network Features..................................................................................... 3
Figure 1. 3: Antenna Radiation Patterns ............................................................................................... 9
Figure 1. 4: Mechanical Tilt [20] .........................................................................................................10
Figure 1. 5: Electrical Tilt [20] ............................................................................................................10
Figure 1. 6: Illustration of Tilt Angle ...................................................................................................10
Figure 1. 7: Modeling of Horizontal Pattern ........................................................................................11
Figure 1. 8: Modeling of Vertical Pattern ............................................................................................12
Figure 2. 1: System Model ..................................................................................................................24
Figure 2. 2: The Relationship between Antenna Main Lobe and Tilt Angle..........................................25
Figure 2. 3: Fundamental of antenna tilt angle calculation ...................................................................25
Figure 2. 4: The Simulation System.....................................................................................................35
Figure 2. 5: Comparison of served MSs number and antennas of eNBs. (a) 0; (b) 6; (c) 16; (d) with
tilts adjusted by MPSO........................................................................................................................36
Figure 2. 6: CDF of MSs RSRP...........................................................................................................36
Figure 2. 7: (a) User’s SINR with Fixed Tilt 6; (b) Users’ SINR with Adjusted Tilt by MPSO; (c) CDF

of Users’ SINR ...................................................................................................................................37
Figure 2. 8: The Convergence of Solution ...........................................................................................37
Figure 2. 9: (a) Users’ Throughput; and (b) System Throughput ..........................................................37
Figure 2. 10: RSRP Distribution of Scenario after Adjusting ATA ......................................................38
Figure 2. 11: SINR Distribution of Scenario after Adjusting ATA .......................................................38
Figure 3. 1: System Model ..................................................................................................................43
Figure 3. 3: The Simulation System (7 eNBs at the center of 19 wrap-around eNBs) ...........................51
Figure 3. 4: The Served User Number Before and After Adjusting ATA without and with Considering
the Network Load ...............................................................................................................................51
Figure 3. 5: CDF of Users’ RSRP........................................................................................................52
Figure 3. 6: CDF of Users’ SINR ........................................................................................................52
Figure 3. 7: The Convergence of Solution ...........................................................................................52
Figure 3. 8: Users’ Throughput and System Throughput ......................................................................53
Figure 3. 9: The Average Load of the Network ....................................................................................53
Figure 3. 10: The Bandwidth Efficiency of the Network ......................................................................53
Figure 3. 11: RSRP Distribution of Scenario after Adjusting ATA ......................................................54
Figure 3. 12: SINR Distribution of Scenario after Adjusting ATA .......................................................54
Figure 4. 1: System Model ..................................................................................................................58
Figure 4. 2: The Simulation System of 19 wrap-around cells ...............................................................65
Figure 4. 3: Effect of Arrival Rate on Average Load............................................................................66
Figure 4. 4: The Relationship between Arrival Rate and Bandwidth Efficiency....................................66
Figure 4. 5: The Relationship between Arrival Rate and Load Balancing Index ...................................67
Figure 4. 6: The Relationship between Arrival Rate and Block Probability ..........................................67
Figure 4. 7: The Relationship between Arrival Rate and Total Users ...................................................68
Figure 5. 1: Operational Principle of Adjusting CIO to Handover User ................................................71
Figure 5. 2: Operational Principle of Adjusting ATA to Handover User...............................................72
Figure 5. 3: System Model ..................................................................................................................73
Figure 5. 4: The Simulation System (7 eNBs at the center of 19 wrap-around eNBs) ...........................82
Figure 5. 5: Effect of α on Call Blocking Rate .....................................................................................82

ix


Figure 5. 6: The Convergence of the Algorithm................................................................................... 82
Figure 5. 7: The Effect of α on LBI ..................................................................................................... 83
Figure 5. 8: Users’ Throughput and System Throughput...................................................................... 83
Figure 5. 9: Average Load of System .................................................................................................. 83
Figure 5. 10: Bandwidth Efficiency..................................................................................................... 84
Figure 5. 11: Coverage Factor ............................................................................................................. 84
Figure 5. 12: Load Balancing Index .................................................................................................... 84

x


LIST OF TABLES
Table 1. 1: Example of Self-Configuration ........................................................................................... 4
Table 2. 1: The pseudo-code of algorithm............................................................................................32
Table 2. 2: Setting of the System Parameters .......................................................................................33
Table 3. 1: The Operation of the Algorithm .........................................................................................48
Table 3. 2: System Simulation Parameters ...........................................................................................49
Table 4. 1: The Operation of the Algorithm .........................................................................................62
Table 4. 2: Setting of the System Parameters .......................................................................................64
Table 5. 1: The Operation of the Algorithm .........................................................................................77
Table 5. 2: Setting of the System Parameters .......................................................................................79

xi


xii

LIST OF ABBREVIATIONS
2D

2 Dimensional

3D

3 Dimensional

3G

the Third Generation (Cellular Systems)

3GPP

the 3 rd Generation Partnership Project

4G

the Fourth Generation

AAS

Adaptive Antenna System

ATA

Antenna Down-Tilt Angle

BSC

Base Station Controller

BTS

Base Transceiver Station

CAPEX

Capital Expenditure

CBR

Call Blocking Rate

CCO

Coverage and Capacity Optimization

CDF

Cumulative Distribution Function

CDR

Call Dropping Ratio

CF

Coverage Factor

CP

Cyclic Prefix

DAS

Distributed Antennas Systems

DL

Down-Link

DNS

Domain Name System

eNB

Evolved Node Base Station

EPC

Evolved Packet System

E-UTRAN

Evolved UMTS Terrestrial Radio Access Network

FDD

Frequency Division Duplexing

FFT

Fast Fourier Transform

GBR

Guaranteed Bit Rate

GERAN

GSM EDGE Radio Access Network

GW

Gateway

GSM

Global System for Mobile Communications

HARQ

Hybrid Automatic Retransmission Request
xiii

HLR

Home Location Register

HO

Handover

HPBW

Half Power Beam-Width

HSS

Home Subscriber Server

IP

Internet Protocol

ISD

Inter-Site Distance

ISI

Inter-Symbol Interference

LB

Load Balancing

LHCP

Left Hand Circular Polarization

LBI

Load Balancing Index

LMR

Land Mobile Radio

LTE

Long Term Evolution

LTE-A

Long Term Evolution-Advanced

MDT

Mechanical Down-Tilt

MIMO

Multiple Input Multiple Output

MLB

Mobility Load Balancing

MME

Mobility Management Entity

MRO

Mobility Robustness Optimization

MPSO

Modified Particle Swarm Optimization

NMS

Network Management System

OAM

Operation Administration and Maintenance

OFDM

Orthogonal Frequency Division Multiple

OFDMA

Orthogonal Frequency Division Multiple Access

OMC

Operation and Maintenance Center

OPEX

Operation Expenditure

QAM

Quadrature Amplitude Modulation

QPSK

Quadrature Phase-Shift Keying

PCRF

Policy charging and Rules Function

P GW

Packet Data Network Gateway

PRB

Physical Resource Block
xiv

PSO

Particle Swarm Optimization

QoS

Quality of Service

RACHO

Random Access Channel Optimization

RAT

Radio Access Technology

RET

Remote Electrical Tilt

RNC

Radio Network Controller

RHCP

Right Hand Circular Polarization

RSRP

Reference Signal Received Power

SAE

System Architecture Evolution

SC-FDMA

Single Carrier Frequency Division Multiple Access

S-GW

Serving Gateway

SGSN

Serving GPRS Support Node

SINR

Signal to Interference plus Noise Ratio

SON

Self-Organizing Network

TDD

Time Division Duplexing

TNL

Transport Network Load

UE

User Equipment

UL

Up-Link

UMTS

Universal Mobile Telecommunications System

UTRAN

UMTS Terrestrial Radio Access Network

VET

Variable Electrical-Tilt

xv


xvi

Chapter 1. Introduction

CHAPTER 1. INTRODUCTION
1.1. Background
LTE is the next step in the GSM evolutionary path beyond 3G technology, and it is
strongly positioned to be the dominant global standard for 4G cellular networks. LTE also
represents the first generation of cellular networks to be based on a flat IP architecture and is
designed to seamlessly support a variety of different services, such as broadband data, voice,
and multicast video. Its design incorporates many of the key innovations of digital
communication, such as MIMO and OFDMA, that mandate new skills to plan, build, and
deploy an LTE network [1].
LTE has key features as follows [2]:
(1) Flexible bandwidth: 1.4/3/5/10/15/20 MHz;
(2) Support FDD and TDD.
(3) 4x4 MIMO, multi-user collaborative MIMO;
(4) Beam forming in the downlink;
(5) Modulation: OFDM with QPSK, 16 QAM, 64 QAM;
(6) OFDMA downlink, SC-FDMA uplink;
(7) HARQ transmission;
(8) Short frame sizes of 10ms and 1ms, faster feedback and better efficiency at high speed;
(9) Persistent scheduling to reduce control channel overhead for low bit rate voice
transmission;
(10) IP based flat network architecture.

1.2. Introduction To Self-Organizing Networks
1.2.1. Architecture of LTE system
The great challenge of the limits of current 3G networks are the trend of ever increasing
transmission bandwidths, hence, in 2005 the Third Generation Partnership Project (3GPP)

standardization body decided to start work on next generation wireless network designs that are
only based on packet-switched data transmission. In order to guarantee the competitiveness of
3G for the next 10 years and beyond, LTE is the latest version in the mobile network technology tree that is being implemented within the 3GPP. Time Division Duplex (TDD) and Frequency Division Duplex (FDD) both are supported by LTE. Nevertheless, LTE also supports a
flexible and scalable bandwidth e.g., 1.25, 5, 10 and 20MHz. LTE also has a very flexible radio
interface [3, 4].
1


Investigations on Key Technologies for LTE Network Optimization, Ph.D. Thesis, Phan Nhu Quan

In order to differentiate NodeB from Universal Mobile Telecommunication System
(UMTS), the base station of LTE is designated to as Evolved Node Base station (eNB) per
3GPP standard. eNBs are designed more to be more intelligent than NodeB by removing Radio
Network Controller (RNC), transferring the functionality to eNB, and partly to the core network gateway. Through X2 interface, eNB can also carry out handovers as well they can communicate with each other directly. Through S1 interface, eNB connects to the gateway nodes
i.e., connection between radio network and core network based on Internet Protocol (IP). Serving Gateway (S-GW) and the Mobility Management Entity (MME) are two entities of the
gateway between core network and radio access networks. MME is the Control Plane (C-plane)
entity which is mainly in charge of session management signaling, mobility of User Equipment
(UE), selection of a gateway to the internet when mobile requests the IP address from the network and the location tracking of mobile devices. S-GW is in charge of User Plane (U-plane).
Both components can be implemented on the same hardware or separated. S11 interface is used
to communicate between MME and S-GW when we implement components separately. LTE
network architecture is illustrated in Fig.1.1.

Figure 1. 1: Architecture of LTE Network

1.2.2. Overview of SON
With the continuous development of wireless access to the internet, it needs to have a
competitive advantage in the mobile operations. A very promising approach is to maximize the
performance of the whole system, that not only provides better wireless access performance,
but also responds more effectively to network operation and maintenance [5]. Self-Organizing
Network (SON) is a long-term process of improving 3GPP (Third Generation Partnership

Project) network operation and a key factor to maintain its main objectives such as effectively
reducing operating expenses, improving network coverage, resource utilization and quality of
service. As every mobile network, LTE system also needs to manage. However, LTE network
itself will inevitably lead to the complexity of the operation and maintenance the network and
of new requirements: SON will open up a new path in the effective cost-saving issue for
operator.

2


Chapter 1. Introduction

Self-organizing network technology means to sense the surrounding environment changes
at any time and to make the appropriate action technology. Self-organizing network
technologies include three areas: self-configuration, self-optimization and self-healing [6].

Figure 1. 2: Self-Organizing Network Features

We can see from the Fig.1.2, self-organizing network technology works throughout the
entire network process, starting from the base station power has been on to the network stable
operation and abnormal situation.
In Self-configuration process, when a new base station is added to an existing network, the
system automatically processes to configure a series of parameters during the installation, so
that it can adapt to run in the current network environment. This is the preparation stage, i.e.
3