DIRE DAWA UNIVERSITY
DIRE DAWA INSTITUTE OF TECHNOLOGY
SCHOOL OF ELECTRICAL & COMPUTER ENGINEERING
COMMUNICATION ENGINEERING
Thesis Title: HANDOVER PERFORMANCE OPTIMIZATION
IN LTE NETWORK
BY: 1. Yomiyu Wendimagegn ………….….… R/0797/08
2. Bizayene Negassi ………….…………...R/0203/08
3. Dechasa Abera …………………….……R/0795/08
4. Endeg Abeje.………….…….….……… R/0991/08
5. Iman Ali………...….……………….……R/2778/07
Advisor: Mr. Tadele A. (MSc)
A thesis submitted to the School of Electrical and Computer Engineering
In Fulfillment of the Requirements for the Degree of Bachelor of Science in
Communication Engineering
February 2021
Dire Dawa, Ethiopia
Declaration
We declare that this paper called “Handover Performance Optimization in LTE Network” is our
own work, except the references cited. We assure that nobody submitted this paper. This paper is
written for BSc degree program in Stream of Communication Engineering.
Student Name
1. Yomiyu wendimagegn
2. Bizayene Negassi
3. Dechasa Abera
4. Endeg Abeje
5. Iman Ali
Signature
____________________________
____________________________
____________________________
____________________________
____________________________
This thesis has been submitted for examination with my approval as a university advisor.
Name
Mr. Tadele A.
Signature
_________________
Date __________________
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Acknowledgment
First, we would like to thank God, who gives us the knowledge and wisdom to do this thesis. Next,
we would like to give our deepest gratitude to Mr. Tadele Abera. Even though he had a very busy
schedule, he did not hesitate to guide as in our project. We also would like to thank our friends who
gave as hardware component to do our thesis. Finally, we thank our parents who support us in any
way we need and who are the first responsible for us to be where we are today.
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Abstract
High-speed data applications over wireless networks have been growing rapidly in recent years.
With this increased use of wireless data, services in wireless networks require performance
guarantee. Therefore, this is driving the need for regular innovations in wireless technologies to
provide more and more capacity and higher quality of service (QoS). These higher performance
requirements have motivated Long-Term Evolution (LTE) network which is proposed by the Third
Generation Partnership Project (3GPP) to provide a smooth migration towards the fourth
generation (4G) network. Long Term Evolution-Advanced (LTE-A) is a major enhancement of the
LTE standard proposed by the 3GPP to meet the 4G mobile communication standards and it
provides improved performance related to data rate, coverage, capacity, but does not have fast and
seamless handover compared to legacy cellular systems.
Handover is a mechanism that transfers an on-going call or data session from one base station (BS)
to another BS or one sector to another sector within the same BS. Hard handover mechanism is
adopted to be used in 3GPP LTE and LTE-A in order to reduce the complexity of the LTE network
architecture. This mechanism comes with degradation in system performance such as higher
system delay and call drop. To overcome this problem an optimizer which is called Particle Swarm
Optimizer (PSO) is used. This optimizer helps to optimize the performance of handover by taking
the control parameters (handover margin and time-to-trigger) adaptively for different speed of user.
In this thesis, Concise understanding on handover optimization in LTE network have been
elaborately presented. Mathematical equation and mathematical model are used to simulate and
investigate the parameters that will increase the performance of LTE. The simulation have been
performed using Mat lab software to evaluate the users moving at different speed has obtained an
efficient reduction in all of the HO output parameters, at the end it has been shown that it has
achieved a better and efficient optimization. From the software results, we recommend that the
possible extension of this thesis on traffic load of target cell that operate under heavy traffic load
and also Pico-Micro, femto cells with the maximum of system throughput under Dynamic UE
characteristics need to be considered.
key words: HO, HOF, HOPP, HOO, HOF, HOPP, HOM, TTT, UE.
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Table of Contents
Declaration ........................................................................................................................................ I
Acknowledgment ............................................................................................................................. II
Abstract .......................................................................................................................................... III
List of table .................................................................................................................................... VI
List of Figure ................................................................................................................................. VII
Acronyms .....................................................................................................................................VIII
CHAPTER-ONE .............................................................................................................................. 1
INTRODUCTION ........................................................................................................................... 1
1.1 Back ground ............................................................................................................................... 1
1.2 Statement of the problem ....................................................................................................... 3
1.3 Objectives................................................................................................................................... 3
1.3.1 General objective ............................................................................................................ 3
1.3.2 Specific objectives .......................................................................................................... 3
1.4 Methodology .......................................................................................................................... 3
1.5 Scope of the Thesis ................................................................................................................ 5
1.6 Significance of the Thesis ...................................................................................................... 5
1.7 Organization of Thesis ........................................................................................................... 5
CHAPTER 2 .................................................................................................................................... 6
LITERATURE REVIEW ................................................................................................................ 6
CHAPTER-THREE ......................................................................................................................... 8
HANDOVER PERFORMANCE OPTIMIZATION IN LTE ......................................................... 8
3.1 Introduction ............................................................................................................................ 8
3.2 LTE and LTE-A Overview .................................................................................................... 8
3.3 LTE Technologies and evolutions ......................................................................................... 9
3.3.1 OFDM ........................................................................................................................... 10
3.3.2 SC-FDM ........................................................................................................................ 10
3.3.3 Turbo Channel Coding .................................................................................................. 11
3.3.4 MIMO ........................................................................................................................... 11
3.3.5 Link Adaptation ............................................................................................................ 12
Adaptive Modulation and Coding .............................................................................................. 13
3.4 LTE Network Architecture .................................................................................................. 14
3.4.1 User Equipment (UE).................................................................................................... 14
3.4.2 Evolved Packet Core (EPC) .......................................................................................... 15
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3.4.3 Evolved Universal Terrestrial Radio Access Network (E-UTRAN) ............................ 16
3.4.4 Evolved Packet System (EPS) Architecture ................................................................. 18
3.5 LTE Requirements ............................................................................................................... 19
3.6 LTE Physical Layer ............................................................................................................. 19
3.7 Handover .............................................................................................................................. 20
3.7.1 Types of handover ......................................................................................................... 20
3.7.2 Handover procedure ...................................................................................................... 21
3.7.3 Handover techniques ..................................................................................................... 22
3.7.4 Handover measurements ............................................................................................... 22
3.7.5 Handover control parameters ........................................................................................ 23
3.7.6 Necessity of Handover optimization ............................................................................. 24
3.8 Handover Initiation .............................................................................................................. 25
27
CHAPTER- FOUR ....................................................................................................................... 28
SYSTEM DESIGN AND ANALYSIS .......................................................................................... 28
4.1 Introduction .......................................................................................................................... 28
4.2 System Design...................................................................................................................... 28
4.2.1 Mathematical relationship under Dynamic UE speed ................................................... 28
4.2.2 Logical relationship case of user equipment speed ....................................................... 30
CHAPTER-FIVE ........................................................................................................................... 33
SIMULATION RESULT AND DISCUSSION ............................................................................ 33
5.1 Introduction .......................................................................................................................... 33
5.2 Simulation result and discussion .......................................................................................... 34
5.2.1 Relation between HOM and Speed of user ................................................................... 34
5.2.2 Relation between Handover Failure and Speed of user ................................................ 35
5.2.3 Relation between Handover Ping-Pong and Speed of user ........................................... 37
5.2.4 Relation between Handover Call drop and Speed of user ............................................ 39
CHAPTER SIX .............................................................................................................................. 41
CONCLUSION AND RECOMMENDATIONS FOR FUTURE WORK .................................... 41
6.1. Conclusion ...................................................................................................................... 41
6.2. Future scope .................................................................................................................... 41
Reference ............................................................................................................................... 42
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List of table
Table 1: LTE basic specification [33] ............................................................................................ 14
Table 3.2: handover procedures [41] ............................................................................................. 21
Table 4.1 Logical relationship of UE speed, HOM, TTT, HOPP, and HOF ................................. 31
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List of Figure
Figure 1.1 Methodology of the project ............................................................................................ 4
Figure 3.1: Scalable bandwidth in LTE [32].................................................................................... 9
Figure 3.2: Frequency- Time representation of an OFDMA signal [30] ....................................... 10
Figure 3.3: MIMO spatial multiplexing [34] ................................................................................. 12
Figure 3.4: MIMO Spatial Diversity [34] ...................................................................................... 12
Figure 3.5: E-UTRAN Architecture [37] ....................................................................................... 16
Figure 3.6: E-UTRAN protocol Stack ........................................................................................... 18
Figure 3.7: LTE Evolved Packet System (EPS) Architecture [33] ................................................ 18
Figure 3.8: Handover between two cells [46] ................................................................................ 25
Figure 3.9: Message chart of the LTE handover procedure ........................................................... 27
Figure 4.1: logical relation b/n HO KPI’s and HO parameters ...................................................... 31
Figure 4.3 Flow chart of System model ......................................................................................... 32
Figure 5.1: HOM value Vs Speed of user ...................................................................................... 34
Figure 5.2: Handover failure Vs Speed of user .............................................................................. 35
Figure 5.3: Optimization of handover failure at Different Speed of user ...................................... 36
Figure 5.4: Optimization of handover failure Vs Speed of user .................................................... 36
Figure 5.5: Handover ping-pong Vs Speed of user ........................................................................ 37
Figure 5.6: Optimization of handover Ping-pong at Different Speed of user ................................ 38
Figure 5.7: Optimization of handover ping-pong Vs Speed of user .............................................. 38
Figure 5.8: handover Call Drop Vs Speed of user ......................................................................... 39
Figure 5.9: Optimization of handover Call Drop at Different Speed of user ................................. 40
Figure 5.10: Optimization of handover Call Drop Vs Speed of user ............................................. 40
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Acronyms
1G
First Generation
2G
Second Generation
3G
Third Generation
3GPP
Third Generation Partnership Project
4G
Fourth Generation
AMC
Adaptive Modulation and Coding
AP
Application Part
BS
Base Station
BBC
Break-Before-Connect
CBB
Connect-Before-Break
CIR
Carrier-to-Interference Ratio
CN
Core Network
CP
Cyclic Prefix
DFT
Discrete Fourier Transform
eNodeB
enhanced NodeB
EPC
Evolved Packet Core
EPS
Evolved Packet System
E-SMLC
Evolved Serving Mobile Location Centre
E-UTRA
Evolved Universal Terrestrial Radio Access
E-UTRAN
Evolved Universal Terrestrial Radio Access Network
EWPHPO
Enhanced weighted Performance HO Parameter Optimization
FDD
Frequency Division Duplexing
FFT
Fast Fourier Transform
GMLC
Gateway Mobile Location Centre
HO
Handover
HOF
Handover Failure
HOM
Handover Margin
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HOPP
Handover Ping-Pong
HSS
Home Subscription Server
IP
ISI
Internet Protocol
Inter Symbol Interference
LTE
LTE-A
Long-Term Evolution
Long-Term Evolution-Advanced
MAC
Medium Access Control
MIMO
Multiple Input Multiple Output
MME
Mobility Management Entity
OFDM
Orthogonal Frequency Division Multiplex
OFDMA
Orthogonal Frequency Division Multiple Access
PCRF
Policy and Charging Rules Function
PDCP
Packet Data Convergence Protocol
PDN
Packet Data Network
PDU
Protocol Data Units
PGW
PDN Gateway
PHY
Physical Layer
PRB
Physical Resource Blocks
PSO
Particle Swarm Optimizer
QAM
Quadrature Amplitude Modulation
QPSK
Quadrature Phase Shift Keying
RAN
Radio Access Network
RLC
Radio Link Control
RNC
Radio Network Controller
RRC
Radio Resource Control
RSRP
Reference Signal Received Power
RSRQ
Reference Signal Received Quality
RSSI
Received Signal Strength Indicator
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RAT
Radio Access Technology
S-GW
Serving Gateway
SAE
System Architecture Evolution
SC-FDMA
Single Carrier-Frequency-Division Multiple Access
SINR
Signal to Interference plus Noise Ratio
SNR
Signal Noise Ratio
TDD
Time Division Duplexing
TE
Terminal Equipment
TTT
Time To Trigger
UE
User Equipment
USIM
Universal Subscriber Identity Module
VS
Versus
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CHAPTER-ONE
INTRODUCTION
1.1 Back ground
Since its invention, cell phone usage is constantly growing in the world. To support the growing
number of users, mobile network standards are constantly evolving. First generation mobile
networks are introduced in the 1980s. These networks are analog networks and could only provide
basic voice services. With the 1990s, second generation mobile networks are introduced. 2G
mobile networks are designed to be digital and could provide data services with SMS messages
beyond voice services. GSM was the most successful 2G mobile network standard. In the second
half of the 1990s, cellphone usage increased rapidly along with the growing popularity of the
Internet. To support the data services in the mobile networks, GPRS is introduced. To provide
better data services for the users, third generation mobile networks are introduced in the late 1990s.
3G provided remarkable data rate improvements over the 2G mobile networks. 2000s saw
explosion of data usages with the growing number of multimedia services on the Internet. To
handle this growth on the mobile networks, fourth generation mobile networks are introduced.
LTE, which is introduced in 2008, is a 4G network standard. It provides better capacity and data
rate over the previous mobile network standards and currently widely used in the world .
To provide better service to the growing number of users and handle the increasing data, the LTE
standard is constantly evolving . LTE-Advanced, which is a major update over LTE, is introduced
in 2011. LTE-Advanced has many improvements over the LTE . Following this evolution of
generations, the communication is cellular based. Cellular communication is a technology which
makes the mobile phones to communicate with each other, but end user that is the mobile phone
user doesn’t stay at a particular place rather moves from one place to another. It is the responsibility
of the cellular systems to retain efficient communication between the systems even when the user
is mobile .
Handoff or handover method is transferring of an active call or data session from one cell to another
. The transfer of a current communication channel to a new base station (BS) may be based upon
time slot, frequency band, or a code word. New BS assigns to the handed off call, if it has some
unoccupied channels. But if all of the channels are in use or all the channel are occupied at the
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handoff time then there are two possibilities: To drop the call or to delay it for a while. This liability
of cellular systems gives rise to the theory of handoff .
Generally, handoff is an important task in maintaining the continuity of call in cellular systems and
its failure can result in ongoing call termination. Thus handoff algorithms try to minimize the
number of handoffs which give poor performance in heavy traffic situations in cellular networks.
Several parameters are used to make the handover decision, some examples are Reference Signal
Received Power (RSRP), Received Signal Strength Indicator (RSSI), Reference Signal Received
Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), distance from BS and speed of
the user . There are three phases involved in both S1 and X2 handover procedures which are
preparation phase, execution phase, and completion phase [9, 10].
Handover in LTE is purely hard handover. The use of hard handover reduces the complexity of the
LTE network architecture. However, the hard handover may result inefficient LTE performance
(i.e. increasing number of handovers and increasing system delay). The main goal of handover
optimization is to reduce call drop, handover failure and ping-pong effect, therefore to get this
result it has to use the control parameters adaptively. If the control parameters are not tuned or are
not used adaptively it might not be able to get an efficient result for all of the handover key
performance indicators. For example, if it is only considering HOM and ignoring the others it
might be able to reduce HOF. However, it might cause an increase in HOPP. Also if it is not
considering the tuning of HOM in different speed of user it causes an increase in HOF. Therefore,
to fix the problems mentioned in the above it has used an optimizer called PSO, which has used
all of the handover control parameters adaptively for the dynamic UE characteristics to optimize
the performance of handover.
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1.2 Statement of the problem
Users expect to get uninterrupted, efficient and stable services in cellular network service. But
there are obstacles in wireless communication which prevents from maintaining the connection at
a defined level of QoS especially while a user is moving around. Fast and seamless handover
mechanisms are needed to achieve this target. Within 3GPP LTE only hard handover is supported
meaning that there is a short interruption in service when the handover is performed.
Hence the study is going to address the problem that occurs when it is not using the HOM and TTT
adaptively while considering the UE speed.
Thus to reduce call Drop, minimize handover failure, and reduce Ping-Pong effect it is very
important to take the handover control parameters adaptively under different speed of users.
1.3 Objectives
1.3.1 General objective
The main objective of this thesis is to optimize the performance of handover in LTE network.
1.3.2 Specific objectives
This thesis project is done specifically aims to achieve:
 Concise understanding on handover optimization in LTE network
 Mathematical modelling and system design
 Simulation using Mat lab
 Analyze the performance
1.4 Methodology
The methodologies to be used to achieve the objectives of the work will include gathering data’s
and understanding the problem clearly and trying to see if there are other solutions to fix the
problem. The employed methods to achieve the objectives of this thesis are done on these basic
steps:
Review of related materials: In this step, books, scientific journals, internet sources have been
reviewed and analyzed to have a clear and precise image of the work.
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Mathematical Modelling and system design: Mathematical equation and mathematical model
are used to simulate and investigate the parameters that will increase the performance of LTE.
Next selection and understanding of an Optimizer is performed.
Simulation using Mat lab: the model that is developed is simulated using PSO in MATLAB.
Comparison of output result: The performance of the handover with and without optimizer is
compared based on the results that are found.
Interpretation and documentation: The results are interpreted and discussed.
The following flow chart summarizes the procedures
Start
Data collection and analyzing
System modeling, parameter
definition
Simulation using matlab
Comparison of output result
Is the result good?
No
Yes
Interpretation and
documentation
End
Figure 1.1 Methodology of the project
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1.5 Scope of the Thesis
The scope of this thesis lies on the Handover performance optimization in LTE network.
Accounting the key performance indicators of handover such as Handover ping-pong, Handover
call drop, and Handover failure under the scenarios of Dynamic UE speed with adaptive Handover
control parameters. The optimization of handover under the consideration of Inter-cell interference
coordination with a maximization of system throughput.
1.6 Significance of the Thesis
The significance of this thesis is straightforward. It could quench the thirsty of great quality
services. Service provider has to provide high quality of service with very low cost and it is
necessary for the service provider to earn high profit from its services, so the company would gain
the profits it has required, and questions of the customers which had been asked for quit long will
be answered, by optimizing the performance of the handover they will be able to use data or voice
call without loss or interruption of service.
1.7 Organization of Thesis
This paper contains Six chapters. The first chapter describes a brief introduction about LTE and
handover and statement of the problem are identified, objectives are defined and the methodology
used is stated. The second chapter is all about literature review. the third chapter presents the
general overview of the Handover in Long Term Evolution technology. In the fourth chapter the
system model and system design are reported. In five four simulation results and discussions are
presented. At the end conclusion and recommendation for future work are covered in the six
chapter.
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CHAPTER 2
LITERATURE REVIEW
In [11] and [12], a soft handover algorithm is presented for TD-LTE system in the high-speed
railway specialized network which has a much better performance comparing with hard handover
algorithm but at the very expense of higher implementation complexity.
The authors in [13] have introduced a call admission control optimization algorithm based on
velocity and the real-timing attribute of the user’s service for Femtocell network, However, the
algorithm involved the detection and the judgment of the real timing attribute, which is
complicated and not suitable for a cost-effective implementation.
Ibraheem Shayea et al [14], have discussed on the advanced Handover techniques such as FSHO,
and SSHO which supports seamless handover, but suffer from some flaws such as Inter-cell
interference coordination, unreliability and some data lost during Handover.
Naha Hassan et al [15], have done on Optimization of control parameters using averaging of
Handover indicator and received power for minimizing ping-pong Handover in LTE, based on
RSRP parameter and achieved a reduction in Handover failure and Handover ping-pong, but they
do not consider the user speed.
The authors in [16-19] proposed adjusting only HOM without considering the impact of TTT, but
this may cause an increase in HOPP. In contrast, the authors in [17] proposed tuning only TTT and
ignoring the effect of HOM, but this may result in increased HO delay, which leads to increased
HOF.
In [20] the authors have done on Handover optimization scheme for LTE-Advance networks based
on AHP-TOPSIS and Q-learning by considering TTT, and has achieved an optimization up to
33%. However, they considered only time to trigger.
In [21] and [22] call blocking handover reduction techniques were proposed to increase the QoS.
Even though they considered TTT and HOM for Dynamic UE speed they performed their work by
considering guard channels to avoid handover call drop which has resulted in channel wastage.
But in this paper handover load balancing is performed to reduce call dropping.
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In [23] Adaptive Time-to-Trigger Scheme for Optimizing LTE Handover was proposed. Even
though, it is good that it took TTT adaptively to optimize the handover, HOM had to be considered
which our work has taken adaptive handover margin and TTT as well as handover offset.
The authors in [24] proposed to decrease frequent and ping-pong handovers, by increasing the
coverage range of femto cells using a lower handover offset. However, expanding the femto cells’
coverage range will reduce the HOM resulting in HOF increasement for the users moving at low
speed. In [25] the authors have worked on the minimization of HOF and HOPP by tuning
Hysteresis and TTT. However, they did not consider the UE speed.
In [26] the Authors have achieved a reduction in Handover failure. However, the effect of Time to
trigger was ignored. The Authors in [27] have achieved an improvement in handover performance
for the dynamic UE speed by finding optimum HOM. However, the values of HOM were optimum
rather being adaptive for the Dynamic UE speed, and the values of TTT that were taken were fixed
value. The author in [28] has proposed to minimize handover failure and handover ping-pong by
taking HOM and TTT adaptively for the dynamic UE speed. However, he did not consider the
target cell traffic-load.
It is clear from the above that some of the researchers have not yet been able to show an optimized
performance by considering both of the control parameters. Even though some of these have tried
to use both of the control parameters they did not consider the UE speed, and even some of them
tried to consider all of the HO control parameters under dynamic UE speed they ignore the effect
of target cell traffic load and dynamic UE speeds in a more realistic environment.
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CHAPTER-THREE
HANDOVER PERFORMANCE OPTIMIZATION IN LTE
3.1 Introduction
A cellular network or mobile network is a communication network where the last link is wireless
and the medium used to transmit data from the transmitter to the receiver is natural medium like
air and water. The network is distributed over land areas called cells, each served by at least one
fixed-location transceiver, known as a cell site or base station. This base station provides the cell
with the network coverage which can be used for transmission of voice, data and others. A cell
might use a different set of frequencies from neighboring cells, to avoid interference and provide
guaranteed service quality within each cell. When joined together these cells provide radio
coverage over a wide geographic area. This enables a large number of portable transceivers (e.g.,
mobile phones, pagers, etc.) to communicate with each other and with fixed transceivers and
telephones anywhere in the network, via base stations [29].
The cellular concept, which is a system-level idea in which a single high-power transmitter is
replaced with multiple low power transmitters, and small segment of the service area is being
covered by each transmitter. It is a major breakthrough in order to solve the problems of limited
user capacity and spectral congestion so; cellular system provides high capacity with a limited
frequency spectrum without making any major technological changes.
Since LTE and LTE-A are abroad band cellular wireless technologies, it is worth summarizing the
key parameters and the specification. In view of the fact that LTE uses different radio access
technologies for downlink and uplink, which naturally makes a difference in the performance they
can offer [30].
3.2 LTE and LTE-A Overview
LTE network is a new radio access technology (RAT) proposed by 3GPP to provide a smooth
migration towards the 4G network and it is a standard wireless communication of high-speed data
for mobile and data terminals. It has inherited a lot from previous 3GPP standards GSM/EDGE
and UMTS/HSPA and in that sense they are considered an evolution of those technologies. It is
designed to increase the capacity, coverage, and speed using a different radio interface together
with core network improvements. All LTE devices have to support Multiple Input Multiple Output
(MIMO) transmissions. The interfaces between network nodes in LTE are Internet Protocol (IP)
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based [31]. LTE specification was designed to provide downlink peak rates of 100Mbps, an uplink
peak rates of 50Mbps, and increase the capacity, coverage, and speed of wireless networks. LTEA supports even higher capacity, coverage, and data rates (i.e. up to 1Gbps in downlink and up to
5ooMbps in uplink). LTE and LTE-A are designed to support spectrum flexibility in the following
three ways:
a) LTE and LTE-A can be deployed with different duplexity: frequency division duplexing
(FDD), time division duplexing (TDD), and half duplex FDD. FDD mode allows downlink
and uplink transmissions simultaneously working in different frequency bands while TDD
allows downlink and uplink transmissions working in the same frequency band with
different time slots. FDD are commonly deployed in a paired spectrum, while TDD is
commonly deployed in an un-paired spectrum.
b) LTE and LTE-A support flexible standardized bandwidth in 1.25MHz, 2.5MHz, 5MHz,
10MHz, 15MHz and 20MHz as shown in figure 2.1. Depending on the available
bandwidth, the transmission bandwidth can be chosen by operators. A smaller bandwidth
is suitable for LTE deployment using legacy mobile cellular bands whereas a larger
bandwidth aims to provide higher data rates.
Figure 3.1: Scalable bandwidth in LTE [32]
c) LTE and LTE-A support operation on different frequency bands and are compatible with
any systems deployed within 900MHz, 2.1GHz and 2.6GHz spectrums.
3.3 LTE Technologies and evolutions
LTE uses different radio access technologies for downlink and uplink, also it includes other
technologies and evolutions to help contribute to the ability of the LTE standard and to meet its
requirements. Which are OFDM, MIMO, turbo coding, and dynamic link-adaptation techniques.
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3.3.1 OFDM
The main reasons LTE selects Orthogonal Frequency Division Multiplexing (OFDM) and its
single-carrier counterpart SC-FDM as the basic transmission schemes include the following:
robustness to the multipath fading channel, high spectral efficiency, low-complexity
implementation, and the ability to provide flexible transmission bandwidths and support advanced
features such as frequency-selective scheduling, MIMO transmission, and interference
coordination. It has a multiple access scheme of Orthogonal Frequency Division Multiple Access
(OFDMA) which is used in the downlink. OFDMA provides high spectral efficiency which is very
immune to interference and reduces computation complexity in the terminal within larger
bandwidths. The OFDM signal can be generated by using the Fast Fourier Transform (FFT). The
available spectrum is divided into multiple, mutually orthogonal subcarriers. The OFDM technique
applied for a signal with 5 MHz bandwidth shown in Figure 3.2 [30].
Figure 3.2: Frequency- Time representation of an OFDMA signal [30]
In the frequency domain, the 5MHz bandwidth is divided into a high number of closely spaced
orthogonal subcarriers. The subcarriers in LTE have a constant spacing of 15 kHz. In EUTRA, the
downlink modulation schemes can be QPSK, 16QAM and 64QAM. In E-UTRA, the guard interval
is a cyclic prefix (CP) which is inserted prior to each OFDM symbol. A group of subcarriers is
called a sub-channel.
3.3.2 SC-FDM
One of the drawbacks of OFDM multicarrier transmission is the large variations in the
instantaneous transmit power. This implies a reduced efficiency in power amplifiers and results in
higher mobile-terminal power consumption. In uplink transmission, the design of complex power
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amplifiers is especially challenging. As a result, a variant of the OFDM transmission known as
Single carrier-frequency-division multiple access (SC-FDMA) is selected in the LTE standard for
uplink transmission. SC-FDM is implemented by combining a regular OFDM system with a pre
coding based on Discrete Fourier Transform (DFT) [33]. By applying a DFT based pre coding,
SC-FDM substantially reduces fluctuations of the transmit power. The resulting uplink
transmission scheme can still feature most of the benefits associated with OFDM, such as lowcomplexity frequency-domain equalization and frequency-domain scheduling, with less stringent
requirements on the power amplifier design.
3.3.3 Turbo Channel Coding
Turbo coding is an evolution of the convolutional coding technology used in all previous standards
with impressive near-channel capacity performance [34]. Turbo coding was having been deployed
in 3G UMTS and HSPA systems. However, in these standards it was used as an optional way of
boosting the performance of the system. In the LTE standard, on the other hand, turbo coding is
the only channel coding mechanism used to process the user data. The near optimal performance
of turbo coders is well documented, as is the computational complexity associated with their
implementation. The LTE turbo coders come with many improvements, aimed at making them
more efficient in their implementation.
3.3.4 MIMO
MIMO is one of the key technologies deployed in the LTE standards. With deep roots in mobile
communications research, MIMO techniques bring to bear the advantages of using multiple
antennas in order to meet the ambitious requirements of the LTE standard in terms of peak data
rates and throughput. MIMO methods can improve mobile communication in two different ways:
by boosting the overall data rates and by increasing the reliability of the communication link. The
LTE standard provides multiple transmit configurations of up to four transmit antennas in its
downlink specification. The LTE-Advanced allows the use of up to eight transmit antennas for
downlink transmission. There are two key features of MIMO [34].
The Spatial Multiplexing: allow transmitting different streams of data simultaneously on the
same resource blocks by exploiting the spatial dimension of the radio channel so that the data
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1
101
0
1
Figure 3.3: MIMO spatial multiplexing [34]
Spatial Diversity: used to exploit diversity and increase the robustness of data transmission. Each
transmitter antenna transmits essentially the same stream of data, so the receiver gets replicas of
the same signal. As shown in Figure 3.4 taking 4 x 4 antenna configuration as an instance, each
receiver antenna may receive the data streams from all transmit antennas.
101
101
101
101
Figure 3.4: MIMO Spatial Diversity [34]
3.3.5 Link Adaptation
Link adaptation is defined as a collection of techniques for changing and adapting the transmission
parameters of a mobile communication system to better respond to the dynamic nature of the
communication channel. Depending on the channel quality, we can use different modulation and
coding techniques (adaptive modulation and coding), change the number of transmit or receive
antennas (adaptive MIMO), and even change the transmission bandwidth (adaptive bandwidth)
[35].
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Adaptive Modulation and Coding
In cellular systems, the quality of the received signal by UE depends on the channel quality from
serving cell, level of interference from other cells, and noise level. To optimize system capacity
and coverage for a given transmission power, the transmitter should try to match the information
data rate for each user to the variations in the received signal. This is commonly referred to as link
adaptation and is typically based on Adaptive Modulation and Coding (AMC). The AMC consists
of the modulation Scheme and code rate.
Modulation Scheme: Low-order modulation (i.e. few data bits per modulated symbol, e.g. QPSK)
is more robust and can tolerate higher levels of interference but provides a lower transmission bit
rate. High-order modulation (i.e. more bits per modulated symbol, e.g. 64QAM) offers a higher bit
rate but is more prone to errors due to its higher sensitivity to interference, noise and channel
estimation errors. Thus it is useful only when the Signal to Interference and Noise Ratio (SINR) is
sufficiently high.
Coding Rate: For a given modulation, the code rate can be chosen depending on the radio link
conditions: a lower code rate can be used in poor channel conditions and a higher code rate in the
case of high SINR [31]. LTE supports the following modulation techniques in the downlink and
uplink:
 64 Quadrature Amplitude Modulation (64 QAM) which uses 64 different quadrature and
amplitude combinations to carry 6 bits per symbol
 16 Quadrature Amplitude Modulation (16 QAM) which uses 16 different quadrature and
amplitude combinations to carry 4 bits per symbol
 Quadrature Phase Shift Keying (QPSK) which uses 4 different quadrature’s to send 2 bits
per symbol [32].
In LTE each subcarrier is modulated with a conventional modulation scheme depending on the
channel condition. LTE uses QPSK, 16QAM, or 64QAM. The FFT sizes of 128, 256, 512, 1024
and 2048, corresponding to LTE channel bandwidth of 1.25, 2.5, 5, 10 and 20MHz are used. Guard
intervals are inserted between each of the symbols to prevent inter-symbol interference at the
receiver caused by multipath delay spread in the radio channel.
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Table 1: LTE basic specification [33]
LTE BASIC SPECIFICATIONS
PARAMETER
DETAILS
Peak downlink speed64QAM(Mbps)
100 (SISO), 172 (2x2 MIMO), 326 (4x4
MIMO)
Peak uplink speeds(Mbps)
50 (QPSK), 57 (16QAM), 86 (64QAM)
Data type
All packet switched data (voice and data). No
circuit switched.
Channel bandwidths(MHz)
1.4, 5, 10, 15, 20
Duplex schemes
FDD and TDD
Mobility
0-500 km/h
Latency
Idle to
active less
Small packets ~10 ms
Access schemes
OFDMA(Downlink)
SC-FDMA (Uplink)
Modulation types supported
QPSK,
16QAM,
downlink)
than
100ms
64QAM (Uplink and
3.4 LTE Network Architecture
The simplified network architecture with open interfaces of LTE is introduced to be all-IP based.
The architecture is designed to be more simplified and flat as compared to the previous 3GPP
releases. Since LTE is the evolution of UMTS, its equivalent components are named Evolved
Universal Terrestrial Radio Access (E-UTRA). This is the air interface includes the user equipment
(UE) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN) and it is used to
describe RAN [36]. System Architecture Evolution (SAE) has been introduced in the new
architecture instead of a radio controller. The combination of the EPC, E-UTRA, and EUTRAN is
called Evolved Packet System (EPS). As shown in Figure 3.7 the LTE network architecture and
the network components are:
3.4.1 User Equipment (UE)
UE refers to the LTE mobile station. The UE can be a handheld device like a smart phone or it can
be a device which is embedded in a laptop. The UE is divided into two parts: The Universal
Subscriber Identity Module (USIM) and the rest of the UE, which is called Terminal Equipment
14 | P a g e
The UE in general is the end-user platform that by the use of signaling with the network, sets up,
maintains, and removes the necessary communication links. The UE is also assisting in the
handover procedure and sends reports about terminal location to the network.
3.4.2 Evolved Packet Core (EPC)
EPC is the network core of the System Architecture Evolution (SAE). The core network is
responsible for the overall control of the UE and establishment of the bearers. The Evolved Packet
Core is the main element of the LTE SAE network. It contains different elements and connects to
the eNodeB’s.

Mobility Management Entity (MME): is the main control element in the EPC used to
process signaling between the CN and the UE. The protocols running between the UE
and the CN are called as the Non-Access Stratum (NAS) protocols.

The S-GW (Serving Gateway): is responsible for IP packet transferring. It acts as a
router, and forwards data between the base station and the packet data network (PDN)
gateway.

PDN Gateway (PGW): The LTE SAE PDN (Packet Data Network) gateway provides
connectivity for the UE to external packet data networks, fulfilling the function of entry
and exit point for UE data. The UE may have connectivity with more than one PGW for
accessing multiple PDNs.

Policy and Charging Rules Function (PCRF): This is the generic name for the entity
within the LTE SAE EPC which detects the service flow, enforces charging policy.

Home Subscription Server (HSS): The HSS is a database server which is located in the
operator's premises. All the user subscription information is stored in the HSS. The HSS
also contains the records of the user location and has the original copy of the user
subscription profile. The HSS is interacting with the MME, and it needs to be connected
to all the MMEs in the network that controls the UE.

Evolved Serving Mobile Location Centre (E-SMLC): The E-SMLC manages the
overall coordination and scheduling of resources required to find the location of a UE that
is attached to E-UTRAN.

Gateway Mobile Location Centre (GMLC): The GMLC contains functionalities
required to support Location Services (LCS). After performing authorization, it sends
positioning requests to the MME and receives the final location estimates.
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3.4.3 Evolved Universal Terrestrial Radio Access Network (E-UTRAN)
E-UTRAN consists of the enhanced NodeB (eNodeB) which handles the radio communications
between the mobile and the evolved packet core. Each eNodeB is a base station that controls the
mobiles in one or more cells. eNodeB’s are connected to each other via X2 interface. The eNodeB’s
are also connected to the EPC via S1 interface, more specifically to the MME by means of the S1MME interface and to the S-GW by means of the S1-U interface [37].
Figure 3.5: E-UTRAN Architecture [37]
3.4.3.1 eNodeB
The eNodeB is a radio base station of a LTE network that controls all radio-related functions in
the fixed part of the system. These radio base stations are distributed throughout the coverage
region and each of them is placed near a radio antenna. One of the biggest differences between
LTE network and legacy mobile communication system 3G is a base station. Practically, an
eNodeB provides bridging between the UE and EPC. All the radio protocols that are used in the
access link are terminated in the eNodeB. The eNodeB does ciphering/deciphering in the user
plane as well as IP header compression/decompression. The eNodeB also has some responsibilities
in the control plane such as radio resource management and performing control over the usage of
radio resources.
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3.4.3.2 X2 Interface
The X2 interface has a key role in the intra-LTE handover operation. The source eNodeB will use
the X2 interface to send the Handover Request message to the target eNodeB. If the X2 interface
does not exist between the two eNodeB’s in question, then procedures need to be initiated to set
one up before handover can be achieved. The Handover Request message initiates the target
eNodeB to reserve resources and it will send the Handover Request Acknowledgement message
assuming resources are found [9].
3.4.3.3 S1 Interface
The radio network signaling over S1 consists of the S1 Application Part (S1AP). The S1AP
protocol handles all procedures between the EPC and E-UTRAN. It is also capable of carrying
messages transparently between the EPC and the UE. Over the S1 interface the S1AP protocol
primarily supports general E-UTRAN procedures from the EPC, transfers transparent non-access
signaling and performs the mobility function [10].
3.4.3.4 E-UTRAN Protocol Stack
The layers of E-UTRAN protocol stack and their responsibilities are:

Physical Layer (PHY): The physical layer provides its services to MAC as transport
channels and maps these channels to physical channels for transmission over the air
interface.

Medium Access Control (MAC): The MAC layer offers its services to RLC as logical
channels and maps these channels to PHY transport channels.

Radio Link Control (RLC): The RLC layer delivers PDCP’s protocol data units (PDU)
to MAC layer with using appropriate MAC logical channels.

Packet Data Convergence Protocol (PDCP): The PDCP sub layer is responsible for
delivering user PDUs to the RRC.

Radio Resource Control (RRC): The RRC layer is a part of LTE c-plane air interface. Its
responsibilities include connection management, mobility functions, system information
broadcast, paging, security, radio bearer management and QoS management functions.
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UE
eNodeB
NAS
NAS
RRC
RRC
PDCP
PDCP
RLC
RLC
MAC
MAC
PHY
PHY
User plane
MME
control plane
User plane
control plane
Figure 3.6: E-UTRAN protocol Stack
3.4.4 Evolved Packet System (EPS) Architecture
EPC + eUTRAN build the Evolved Packet System (EPS). LTE/SAE is specified from Release 8.
The name of the actual Radio Access Network (RAN) is eUTRAN and for Core Network (CN) is
Enhanced Packet Core (EPC). The eUTRAN supports use of different MIMO (Multiple Input
Multiple Output) multiple antenna configurations. This increases the data rates and spectrum
efficiency. One of the objectives E UTRAN is to simplify and reduce the number of interfaces.
Figure 3.7: LTE Evolved Packet System (EPS) Architecture [33]
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3.5 LTE Requirements
LTE requirements cover two fundamental components of the evolved UMTS system architecture:
E-UTRAN and EPC. The goals of the overall system include the following:

Peak data rate: System should support downlink peak data rate of 100Mb/s and
uplink peak data rate of 50Mb/s within a 20 MHz spectrum.

User throughput: An average user throughput per MHz must be 3-4 times
Release 6 HSDPA in downlink and 2-3 times Release 6 HSUPA in uplink.

Spectrum efficiency: In a loaded network, target for spectrum efficiency must be
3-4 times Release 6 HSDPA in downlink and 2-3 times Release 6 HSUPA in
uplink.

Mobility: System should support mobility up to 350 km/h, even up to 500 km/h
depending on the frequency band.

Coverage: Since the data rate, throughput and mobility clauses may not be met
strictly after 30 km maximum cell range is specified.

C-plane capacity: System should be able to support 400 users per node.

U-plane latency: System should provide less than 5ms transfer latency over the
network.

Spectrum: System shall support different spectrum allocation sizes up to 20 MHz
3.6 LTE Physical Layer
The design of LTE physical layer is heavily influenced by requirements of high peak transmission
rate (100 Mbps DL or 50 Mbps UL), spectral efficiency, and multiple channel bandwidths (1.2520 MHz), so that an Orthogonal Frequency Division Multiplex (OFDM) was selected as the basis
for the physical layer to fulfill the requirements. Physical layer tasks include power control and
neighborhood measurements. The OFDMA is selected for the LTE radio access technology, where
the dominant mode of operation is the Frequency Division Duplexing (FDD). With OFDMA, data
is transmitted in multiple orthogonal narrow band streams. This orthogonality ensures that the Inter
Symbol Interference (ISI) is at its minimum. In LTE OFDMA, the transmission bandwidth is
divided into Physical Resource Blocks (PRB) of 180 kHz bandwidth and 0.5msec duration, where
each PRB carries 12 subcarriers. The bandwidth spacing between these subcarriers is 15 KHz [38].
As a result, the number of PRBs varies depending on the system transmission bandwidth, where
each PRB can be assigned to one user at any given time.
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3.7 Handover
Handover is one of the basic elements in cellular network mobility management and is one of the
key procedures for ensuring that the users move freely through the network while still being
connected and being offered quality services. Basically it is the process of establishing a target
radio link from source base station to target base station. When the handover process is initiated,
the target base station is alerted about the awaiting handover by the serving base station. The target
base station allocates a radio resource set and provides information to the serving base station. The
serving base station sends this information to the user equipment. After receiving the information
user equipment breaks the current session with serving base station and establishes the new radio
link using the radio resource set [39].
In LTE one of the main goals is to provide fast and seamless handover from one cell to another
while simultaneously keeping network management simple and handover is the key procedures for
ensuring this.
Hence, optimizing the handover procedure to get the required performance is considered an
important issue in LTE networks. Depending on the required QoS, a handover characteristic
(seamless handover or a lossless handover) is performed as appropriate for each radio bearer [40].
Seamless handover: - The objective of seamless handover is to provide a given QoS when the UE
moves from the coverage of one cell to the coverage of another cell. These types of data are
typically reasonably tolerant of losses but less tolerant of delay.
Lossless handover: - Lossless handover means that no data should be lost during handover.
Lossless handover can be very suitable for delay-tolerant services.
3.7.1 Types of handover
The handover is triggered by the eNodeB, based on the received measurement reports from the
UE. Handover is classified in different types based on the origination and destination of the
handover. Handover is classified as:
Intra-LTE handover: in this case source and target cells are part of the same LTE network.
Inter-LTE handover: handover happens towards other LTE nodes.
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Inter-RAT handover: handover between different radio technologies. Examples can be like from
LTE to WCDMA.
3.7.2 Handover procedure
There are two types of handover procedure in LTE for UEs in active mode:

The S1-handover procedure

The X2-handover procedure
Table 3.2: handover procedures [41]
X2-handover procedure
S1-handover procedure
Is used when direct connectivity between Is performed between two eNBs without the
source and target eNBs exists
X2 interface.
Is quicker
More complex
Used for balancing network load
Enables LTE to perform handover with other
RATs
Minimized interference
Compatible with other non-3GPP specific
access technologies
The table 3.2 shows that appropriate uses of the handover procedures. There are three phases
involved in the S1 and X2 handover procedures namely preparation phase, execution phase and
completion phase [41].
Handover preparation: During the handover preparation, data flows between UE and the core
network. This phase includes messaging such as measurement control, which defines the UE
measurement parameters and then the measurement report sent accordingly as the triggering
criteria is satisfied. Handover decision is then made at the serving eNodeB, which requests a
handover to the target cell and performs admission control. Handover request is then
acknowledged by the target eNodeB.
Handover execution: Handover execution phase is started when the source eNodeB sends a
handover command to UE. During this phase, data is forwarded from the source to the target
eNodeB, which buffers the packets. UE then needs to synchronize to the target cell and perform a
random access to the target cell to obtain UL allocation and timing advance as well as other
necessary parameters. Finally, the UE sends a handover confirm message to the target eNodeB
after which the target eNodeB can start sending the forwarded data to the UE.
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Handover completion: In the final phase, the target eNodeB informs the MME that the user plane
path has changed and is then notified to update the user plane path. At this point, the data starts
flowing on the new path to the target eNodeB. Finally, all radio and control plane resources are
released in the source eNodeB [42].
3.7.3 Handover techniques
Handover can be categorized as hard handover and soft handover also known as Break-Before
Connect (BBC) and Connect (Entry)-Before-Break (CBB), respectively [43].
Soft Handover: Soft handover is a category of handover procedures where the radio links are
added and abandoned in such manner that the UE always keeps at least one radio link to the
UTRAN. Soft and softer handover were introduced in WCDMA architecture. There is a centralized
controller called Radio Network Controller (RNC) to perform handover control for each UE in the
architecture of WCDMA. It is possible for a UE to simultaneously connect to two or more cells
(or cell sectors) during a call [44]. If the cells the UE connected are from the same physical site, it
is referred as softer handover. In handover aspect, soft handover is suitable for maintaining an
active session, preventing voice call dropping, and resetting a packet session. However, the soft
handover requires much more complicated signaling, procedures and system architecture such as
in the WCDMA network.
Hard Handover: In the legacy wireless systems, hard handover is the commonly used handover
method. The hard handover requires a UE to break an existing connection with the current cell
(source cell) and then make a new connection with a target cell [42]. Hard handover has been
adopted in LTE system by 3GPP due to the flat IP-based architecture and the lack of a centralized
controller. The use of hard handovers reduces the complexity of the handover mechanism and
minimizes the handover delay. However, the hard handover approach causes call drop that may
result in lost data during a session. Therefore, a mechanism to avoid data loss is needed for hard
handovers.
3.7.4 Handover measurements
Handover operation in the LTE network is part of the radio resource management and is based on
the user measurements [45].
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Reference Signal Received Power (RSRP): The reference received signal power indicates the
characteristic signal strength of the cell. This measurement is used to rank different LTE candidate
cells according to their signal strength. It can also be used as a handover input for cell selection.
Signal to Interference plus Noise Ratio (SINR): SINR is used to optimize the transmitted power
to maintain the quality of the target service with handover decision. Accurate estimation of SINR
leads to improve efficiency of the system and attain higher service quality. SINR is defined as the
ratio of signal power to the sum of noise and interference powers at the receiver.
Received Signal Strength Indicator (RSSI): RSSI is the total received wideband power observed
by the UE from all sources, including co-channel serving and non-serving cell, adjacent channel
interference, thermal noise and so on.
Reference Signal Received Quality (RSRQ): is the relation between signal and interference plus
noise and is defined as the ratio of RSRP to RSSI times the number of resource block (RB) of the
E-UTRA carrier RSSI measurement bandwidth.
Carrier-to-Interference Ratio (CIR): CIR expressed in decibels (dB) is a measurement of
signaling effectiveness and it is defined as the ratio of the power in the carrier to the power of the
interference signal.
Signal Noise Ratio (SNR): The SNR is a measurement that compares the level of a desired signal
to the level of background noise (unwanted signal). It is defined as the ratio of signal power and
the noise power. A ratio higher than 1:1 indicates more signal than noise.
3.7.5 Handover control parameters
Hysteresis: A handover is initiated when the following condition is met: the RSRP of the
neighboring cell is greater than the RSRP of the SeNB plus the hysteresis value for at least for a
certain amount of time. The valid hysteresis value varies between 0 and 10 dB with steps of 0.5
dB, resulting in 21 valid hysteresis values [45].
Time-to-Trigger: is the time in which the RSRP condition has to hold in order for a handover to
be initiated is specified by the Time-To-Trigger (TTT) parameter. The TTT values for LTE
networks are specified by 3GPP: 0, 0.04, 0.064, 0.08, 0.1, 0.128, 0.16, 0.256, 0.32, 0.48, 0.512,
0.64, 1.024, 1.280, 2.560 and 5.120 in [s]. These 16 values are the only valid TTT values [45].
23 | P a g e
Handover offset: is HO control parameter which is used for excluding users from the service area
of target cell when it is operating heavy traffic load.
3.7.6 Necessity of Handover optimization
Minimize the number of handover failures: The call termination due to handover should be
avoided, and the conversation should be preserved when the mobiles move from one serving cell
to another by doing handover. This is a crucial goal for handover design and optimization.
Minimize the number of unnecessary handovers: It is always desirable to minimize the number
of handovers because excessive handovers increase the switching load and decrease the
communication quality, and traffic capacity of a system. Mitigating Ping-Pong effects (in which
the user repeatedly switches between adjacent cells) and identifying the correct target cell can help
avoiding unnecessary handovers.
Minimize the absolute number of initiated handovers: The handover procedure is risky because
the call may be dropped due to the handover. The number of handover initiations will be
significantly increased if there are many Ping-Pong handovers or incorrect target cell selection.
Hence, it is very important for the operator to minimize the number of handovers to provide a good
service to their customers [46].
Minimize handover delay: Handover should be fast so that the user does not experience service
Degradation or interruption. This goal is more important for hard handover where there is an
interruption in the user plane.
Maximize the total time the user being connected to the best cell: Handover is performed to
have the UE connected to the best cell. Achieving this goal will be easier if the handover is
designed in a way that prolongs the amount of time that the UE is connected to the best cell. Hence,
maximizing the total time that user is connected to the best cell is an important design goal.
Minimize the impact of handover on system and service performance: Minimizing the impact
of handover on system and service performance can be obtained by optimizing the handover
procedure. With an efficient handover algorithm, there should be good system performance for the
user. In addition, to minimize the impact of handover procedure on service performance, with a
specific consideration of delay critical services such as real time services, is also important for
handover design [46].
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3.8 Handover Initiation
Handover initiation is a phase in the handover process in which the appropriate condition to request
a handover to a target cell is triggered. The common handover initiation techniques include;
initiation based on relative signal strength, initiation based on relative signal strength with
threshold, initiation based on relative signal strength with hysteresis, initiation based on relative
signal strength with hysteresis and threshold. Figure 3.8 shows a UE moving from one BS (BS A)
at position LA to another (BSB) at position LB. The average signal strength of BSA decreases as the
UE moves away from it. Similarly, the average signal strength of BSB increases as the UE
approaches it. The BS averages the signal after a time period to remove the rapid fluctuations due
to multipath effects.
Figure 3.8: Handover between two cells [46]
a) Relative signal strength: The UE is handed over from base station A to base station B, when
the signal strength at B first exceeds that at A. If the signal strength at B subsequently falls
below that of A, the mobile unit is handed back to A.
In Figure 3.8, handover occurs at point L1. At this point the signal strength to base station
A is still adequate but is declining, because signal strength fluctuates due to multipath
25 | P a g e
effects. Even with power averaging this approach can lead to a Ping-Pong effect, a scenario
when the UE is repeatedly handed back and forth between two base stations.
b) Relative signal strength with threshold: Handover only occurs when the signal at the
current base station is sufficiently weak (less than a threshold) and the other signal is the
stronger of the two base stations. The intention is that so long as the signal at the current
base station is adequate, handover is unnecessary. If a high threshold is used, such as Th1,
this scheme performs the same as the relative signal strength scheme. With a threshold of
Th2, handover occurs at L2. If the threshold is set quite low compared to the crossover
signal strength (signal strength at L1), such as Th3, the UE may move far into the new cell
(L4) before handover. This reduces the quality of the communication link and may result
in a dropped call. A threshold should not be used alone because its effectiveness depends
on prior knowledge of the crossover signal strength between the current and candidate base
stations.
c) Relative signal strength with hysteresis: Handover occurs only if the new base station is
sufficiently stronger by a margin (H) than the current one. In this case, handover occurs at
L3. This scheme prevents the ping-pong effect, because once handover occurs, the effect
of the margin (H) is reversed.
d) Relative signal strength with hysteresis and threshold: Handover occurs only when the
current signal level drops below a threshold, and when the target base station is stronger
than the current one by a hysteresis margin (H). In Figure 2.8, handover occurs at L3 if the
threshold is either Th1 or Th2 and at L4 if the threshold is at Th3.
26 | P a g e
Source eNB
UE
Target eNB
Measurement control
Uplink allocation
Measurement Report
Down link allocation
Ho
Decision
Handover requested
Handover requested Ack
Handover command
Synchronization and Rach access
Uplink allocation
Handover confirm
Flash Buffer and
Release resource
L3 Signaling
L1/L2 signaling
Figure 3.9: Message chart of the LTE handover procedure
27 | P a g e
Admission
control
CHAPTER- FOUR
SYSTEM DESIGN AND ANALYSIS
4.1 Introduction
In this section the mathematical relationship of input parameters (speed of the user), control
parameters (hysteresis and time to trigger) and output parameters (ping pong, handover failure,
and call drop) and finally the system Model are presented.
In LTE system, HO procedure executed between the serving eNB and target eNB is determined by
a number of parameters, e.g. Time to trigger (TTT) and handover margin etc. However, due to the
different radio condition, the different control parameters are chosen for different scenarios in
order to optimize the HO performance. If the radio conditions change during operation of an LTE
network, such as the user movement, an adaptation of the applied handover control parameters
become necessary.
4.2 System Design
4.2.1 Mathematical relationship under Dynamic UE speed
The key steps of a typical handover process are, first a UE performs RSRP measurements in order
to initiate a handover, then the UE waits until the RSRP from a target is larger than the RSRP from
a serving cell plus a HOM (step-1). Even when this condition is satisfied, it waits for duration of
TTT, before sending a measurement report to its serving cell (step-2). The use of TTT is critical to
ensure that ping-pongs are minimized due to fluctuations in the link qualities from different cells.
If the condition in step-1 is still satisfied after TTT, the UE sends the measurement reports to its
serving cell in its uplink (step-3), which finalizes the handover by sending a handover command
to the UE in the DL after going through several other handover steps (step-4).
RSRPt >RSRPs+HOM
HOTrigger >TTT
(1)
(2)
where and are the RSRP received from the target cell and the serving cell, respectively and is the
handover trigger timer which starts counting when condition
(1) gets satisfied.
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Optimizing HOM and TTT may shift the HO region to an improved radio network operation.
However, choosing the optimal HO parameter is not an easy task. Indeed, it may lead to a worse
operation region. An increase in TTT results in an increase in HO delay, while an increase in HOM
leads to degradation in the quality of the radio connection before the condition of Eq. (1 & 2) are
satisfied, which may lead to HOF. Therefore, it is expected that the optimized value of HO control
parameters can reduce HOPP and HOF.
Different factors can affect the performance of handover output parameters (handover ping-pong,
handover failure, and handover call drop) for instance speed of the user is one of the factors that
affect the performance of handover. Thus at different speed the control parameter has to be
adaptive.
4.2.1.1 Relation between UE Speed and HOM
The mathematical relationship of the Handover margin and the speed of the user can be expressed
by:
HOM =K
Where,
(3)
The variable r represents the coverage radius of the base station, the variable vt represents the speed
of the user, the variable s represents the overlap radius of the two base stations, and the variable t
represents handover time.
4.2.1.2 Relation between UE Speed and Handover failure
Handover Failure Probability as a function of user speed is given as following
Phof
(4)
Where,
ℎ
is probability of handover failure, v is the speed of the user, t is handover time, and r is coverage
area of the cell.
4.2.1.3. Relation between UE Speed and Handover ping-pong
Phopp
Where,
29 | P a g e
(5)
ℎ
is probability of handover ping-pong, v is the speed of the user r is the cell radius and t is the
handover time.
4.2.1.4. Relation between UE Speed and call drop rate
The call drop under the scenario of UE speed is caused as a result of the radio link failure which
could be due to too early handover or too late handover. the handover is being performed at a right
time and right place (having adaptive TTT and HOM) for the users moving at different speed.
A mathematical relationship of call drop rate and user speed can be expressed by
Pc=
(6)
Where,
(7)
R is cell radius, is the mean call duration, v is the speed of the user and is probability of call drop.
4.2.2 Logical relationship case of user equipment speed
Now let’s investigate what will be HOF and HOPP for Different values of Hysteresis and TTT. If
a UE is moving at high speed and the Hysteresis and TTT are both low then it will result in low
HOF and HOPP, but if a UE is moving at low speed and the Hysteresis and TTT are both low then
it will result in very high HOF and HOPP.
Also if a UE is moving at high speed having both the Hysteresis and TTT at high then it will result
in high HOF this is because of too late HO and low HOPP, but If a UE is moving at low speed and
the Hysteresis and TTT are both high then it will result in low HOF and low HOPP.
Thus for the UE moving at different speed having different Hysteresis and TTT lets summarize the
result of HOF and HOPP in the following table.
Input
Control parameters
Outputs
HO Ping-Pong
30 | P a g e
UE speed
HOF
TTT
Hysteresis
Figure 4.1: logical relation b/n HO KPI’s and HO parameters
Table 4.1 Logical relationship of UE speed, HOM, TTT, HOPP, and HOF
No.
When UE
IF HOM
And IF TTT
Then HOF
Then HOPP
speed
1
2
3
4
5
6
7
8
Increase
Increase
Increase
Increase
Decrease
Decrease
Decrease
Decrease
Low
Low
High
High
Low
Low
High
High
Low
High
High
Low
Low
High
Low
High
Decrease
Increase
Increase
Increase
Increase
Increase
Decrease
Decrease
Decrease
Decrease
Decrease
Decrease
Increase
Decrease
Increase
Decrease
From the above table as the speed, TTT and Hysteresis varies the HOF and HOPP varies. But our
goal is to get the optimized handover (i.e. low HOPP and low HOF as much as possible) so we
have to choose the optimized value for each UE speed. For instance, at low speed the Hysteresis
and TTT have to be high or they have to be high and medium respectively. When we look to the
changes that need to be done to optimize these problems, we can see that the solutions contradict
with each other. To decrease too early handover and ping-pong handover events, the handover
parameters must be increased while in order to decrease handover too late events, the parameters
must be decreased. Thus to avoid such contradictions the handover control parameters such as
Hysteresis and TTT has to be taken adaptively for the Dynamic UE speed.
4.3. System model
In this section the way the system is modeled are going to be discussed as following.
Start
31 | P a g e
With O
No
Please enter the
appropriate speed
Without optimizer
With optimizer
Fixed
control
parameter
HO
Perform MLB
Simulation result
Figure 4.3 Flow chart of System model
First, the speed has to be checked then the simulation without optimizer checks whether HO control
parameters are satisfied. If the user speed is low the HOM has to be high to avoid too early
handover failure, and has to be decreased to minimize the handover failure due to too late when
the speed of the user is increased. Since taking an adaptive HOM for the users moving at different
speed optimizes the handover performance, but at a fixed value of TTT can also degrades the
system performance because low TTT value will results in high handover ping-pong and high TTT
32 | P a g e
will cause handover delay. Thus for the users moving at different speed the handover control
parameters (HOM, and TTT) has to be adaptive.
CHAPTER-FIVE
SIMULATION RESULT AND DISCUSSION
5.1 Introduction
In this chapter it is going to discuss about the simulation results of handover failure, handover pingpong, and Handover call drop Vs UE speed with and without optimizer. Also handover failure,
handover ping-pong, and call drop VS UE Speed with and without optimizer are simulated and
discussed. Finally, the optimized handover control parameters used to optimize the Handover
performance are summarized.
33 | P a g e
5.2 Simulation result and discussion
5.2.1 Relation between HOM and Speed of user
Figure 5.1: HOM value Vs Speed of user
The above figure shows that when the speed of the user increases the HOM decreases. This is
because when the user moves at high speed it covers a long distance with a small period of time.
So it will be handoff in very short period of time. This is why HOM is very small for high speed
mobility. Thus for different values of speed the HOM is going to be different and it is chosen
depending on the speed. Generally, the purpose of reducing HOM is to avoid too-late handover
(HOF), to reduce ping-pong effect and to minimize call drop.
Finally HOM value will be zero for the user moving at a speed equals to which is driven from
equation 3
Where,
s = is the overlapping zone between the serving and target cell (in km) and
t= is the handover time (in ms).
Thus the user that moves at a speed of greater than or equal to has zero HOM value.
34 | P a g e
5.2.2 Relation between Handover Failure and Speed of user
Figure 5.2: Handover failure Vs Speed of user
From this figure it is clear that when speed of the user increases the handover failure increases, and
this is when the HOM is set high, and remains the same for the users moving at different speed.
The reason for the increasing of handover fail is due to too-late handover, and this fail has to be
minimized by taking different HOM for the users moving at different speed. i.e. when the user
speed increases the value of HOM has to be decreased.
35 | P a g e
Figure 5.3: Optimization of handover failure at Different Speed of user
The control parameters such as HOM and TTT will not remain the same. Since the simulation is
done using PSO optimizer it takes adaptive Handover control parameters to minimize the HOF.
Thus the handover control parameters for the users moving at low speed are high, and low for the
users moving at high speed, otherwise it results in high HOF due to too early and too late handover
respectively.
Figure 5.4: Optimization of handover failure Vs Speed of user
36 | P a g e
The figure shows that by taking adaptive handover control parameters. Minimization of HOF can
be achieved by varying only one of HOM or TTT as it has tried to see in the literature review and
figure 5.4, but varying only one of these is not efficient, because it affects the other Handover key
performance indicators, and the optimization is lower than the optimization achieved by varying
both handover control parameters.
i.e. by varying only HOM and fixing TTT the HOF could be minimized but may cause high HOPP.
Therefore, an efficient minimization of HOF is achieved by varying both control parameters than
varying only one of the handover control parameters.
5.2.3 Relation between Handover Ping-Pong and Speed of user
Figure 5.5: Handover ping-pong Vs Speed of user
For the user moving at low speed setting the value of TTT low will result in high handover ping
pong also when the speed increases the handover ping pong decreases and that is because the high
speed users pass fast to the target cell. When setting the value of TTT high, the handover pingpong for the low speed users will be minimized, but when the value of TTT remains the same it
causes a HOF for the high speed users. Thus to minimize the handover ping-pong for the users
moving at different speed and to avoid the trade-off between HOF and HOPP the handover control
parameter such as HOM and TTT has to be taken adaptively.
37 | P a g e
Figure 5.6: Optimization of handover Ping-pong at Different Speed of user
The above figure shows that minimization of handover ping-pong by taking the handover control
parameters adaptively.
Figure 5.7: Optimization of handover ping-pong Vs Speed of user
This figure shows Handover ping-pong can be optimized by varying only one of the control
parameters, but this optimization is lower than the optimization achieved by varying both handover
38 | P a g e
control parameters. Thus the handover control parameters such as HOM and TTT has to be taken
adaptively at the same time for the users moving at different speed.
5.2.4 Relation between Handover Call drop and Speed of user
Figure 5.8: handover Call Drop Vs Speed of user
Handover call drop Vs speed of user and shows the probability of that handover call drop is
increased with increasing speed of the user. This is because for the users moving at high speed
there is an increasing in handover failure and as it is mentioned above this is because HOM is high
for all UE speed which results in a high probability of call drop, and to overcome this it has to use
the HO control parameters adaptively. The reason for the call drop that is explained in this scenario
is due to HOF but in other scenarios HOF may not always be the reason for call drop and vice
versa.
39 | P a g e
Figure 5.9: Optimization of handover Call Drop at Different Speed of user
Figure 5.10: Optimization of handover Call Drop Vs Speed of user
The Probability of call drop Vs speed of user by taking adaptive handover control parameters.
Reduction of call drop can be achieved by varying only one of HOM or TTT but varying only one
of these is not efficient because the optimization is lower than the optimization achieved by varying
both handover control parameters.
40 | P a g e
CHAPTER SIX
CONCLUSION AND RECOMMENDATIONS FOR FUTURE WORK
6.1. Conclusion
The LTE standard proposed by the 3GPP to meet the 4G mobile communication standards and it
provides improved performance related to data rate, coverage, capacity, but does not have fast and
seamless handover compared to legacy cellular systems, due to this we motivated to do our thesis
on handover performance optimization in LTE network.
In this thesis, we have designed and simulated handover optimization in LTE network by following
the methodology within step by step procedures. Mathematical equation and mathematical model
are used to simulate and investigate the parameters that will increase the performance of LTE. The
simulation have been performed using Mat lab software to evaluate the users moving at different
speed has obtained an efficient reduction in all of the HO output parameters, at the end it has been
shown that it has achieved a better and efficient optimization.
The main part in our thesis is by using Mat lab called Particle Swarm Optimizer (PSO) tool
performing handover performance optimization in LTE network. Reduction of handover failure,
call drop and ping-pong can be achieved by varying only one of HOM or TTT but varying only
one of them is not efficient because the optimization is lower than the optimization achieved by
varying both handover control parameters. The Mat lab output show that the key performance
indicators of handover such as Handover ping-pong, Handover call drop, and Handover failure
under the scenarios of Dynamic UE speed with adaptive Handover control parameters achieved
better performance.
6.2. Future scope
Every Users expect to get uninterrupted, efficient and stable services in cellular network service.
In wireless communication which prevents from maintaining the connection at a defined level of
QoS especially while a user is moving around. Fast and seamless handover mechanisms are needed
to achieve this target. The problem being addressed in our study is regardless of the traffic load on
the target cell. Then we recommend that the possible extension of this thesis on traffic load of
target cell that operate under heavy traffic load and also Pico-Micro, femto cells with the maximum
of system throughput under Dynamic UE characteristics need to be considered.
41 | P a g e
Reference
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[20] Saeed, Mohamed, Mona El-Ghoneimy, and Hanan Kamal. “An enhanced fuzzy logic
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[36]. Konstantinos Dimou, Min Wang, Yu Yang, Muhammmad Kazmi, Anna Larmo, Jonas
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45 | P a g e
Appendices
Probability of HOF
%MATLAB
CODE
FOR
HANDOVER
FAILURE
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%5%%
t=0.04:0.1:5.120;
v=0:2.8:140;
t1=2; t2=t+t1;
vt=v.*t2;
r=1000;%
f=1.1*(2/pi).*asin(vt/(r));
plot(v,f) xlabel('speed of the
user ') ylabel('Probability of
HOF')
title('optimization of Handover Failure with speed')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%
%MATLAB CODE FOR OPTIMIZATION OF HANDOVER FAILURE USING PSO
OPTIMAZER UAT DIFFERENT SPEED OF USER
%**************************************************************
lb1=[2.5 31 2.6]; ub1=[7 35 10]; lb2=[1 1 0.4]; ub2=[2.5 8 3.6]; lb=[1 0.1 0.4];
ub=[10 30 5.2]; t1=4.5; r1=500; m=3; n=100; wmax=0.9; wmin=0.4; c1=2;
c2=2; maxite=100; maxrun=10; k=175; r=2000; t=0.8; s=100; for
run=1:maxite run; for i=1:n
for j=1:m
x0(i,j)=round(lb(j)+rand()*(ub(j)-lb(j)));
x10(i,j)=round(lb1(j)+rand()*(ub1(j)-lb1(j)));
x20(i,j)=round(lb2(j)+rand()*(ub2(j)-lb2(j)));
end end x=x0; x1=x10; x2=x20;
v=0.1*x0; v1=0.1*x10; v2=0.1*x20; for
i=1:n
f0(i,1)=pchdropmt(x0(i,:));
end
for i=1:n
f10(i,1)=pchdropmt1(x10(i,:));
end for i=1:n
f20(i,1)=pchdropmt2(x20(i,:));
end
[fmin0,index0]=min(f0);
[fmin10,index10]=min(f10);
[fmin20,index20]=min(f20);
46 | P a g e
pbest=x0;
pbest1=x10;
pbest2=x20;
gbest=x0(index0,:);
gbest1=x10(index10,:);
gbest2=x20(index20,:);
ite=1;
tolerance=1;
while ite<=maxite && tolerance>10^-12
w=wmax-(wmax-wmin)*ite/maxite;
for i=1:n
for j=1:m
x(i,j))+c2*rand()*(gbest(1,j)-x(i,j));
x1(i,j))+c2*rand()*(gbest1(1,j)-x1(i,j));
x2(i,j))+c2*rand()*(gbest2(1,j)-x2(i,j));
end
for i=1:n
for j=1:m
x(i,j)=x(i,j)+v(i,j);
x1(i,j)=x1(i,j)+v1(i,j);
x2(i,j)=x2(i,j)+v2(i,j);
end
end
for
i=1:n
for
j=1:m
if x(i,j)<lb(j)
x(i,j)=lb(j);
elseif
(x(i,j)>ub(j))
x(i,j)=ub(j);
end
if
x1(i,j)<lb1(j)
x1(i,j)=lb1(j);
elseif
(x1(i,j)>ub1(j))
x1(i,j)=ub1(j);
end
if
x2(i,j)<lb2(j)
x2(i,j)=lb2(j);
elseif
(x2(i,j)>ub2(j))
x2(i,j)=ub2(j);
end
end
end
for
i=1:n
47 | P a g e
v(i,j)=w*v(i,j)+c1*rand()*(pbest(i,j)v1(i,j)=w*v1(i,j)+c1*rand()*(pbest1(i,j)v2(i,j)=w*v2(i,j)+c1*rand()*(pbest2(i,j)end
f(i,j)=pchdropmt
(x(i,:));
end
for i=1:n
f1(i,j)=pchdropmt1(x1(i,:));
end
for i=1:n
f2(i,j)=pchdropmt1(x2(i,:));
end
for
i=1:n
if
f(i,1)<f0(i,1)
pbest(i,:)=x(i,:);
fo(i,1)=f(i,1);
end
if
f1(i,1)<f10(i,1)
pbest1(i,:)=x1(i,:);
f1o(i,1)=f1(i,1);
end
if
f2(i,1)<f20(i,1)
pbest2(i,:)=x2(i,:);
f2o(i,1)=f2(i,1);
end
end
[fmin,index]=min(fo);
[fmin1,index1]=min(f1o);
[fmin2,index2]=min(f2o);
ffmin(ite,run)=fmin;
ffmin1(ite,run)=fmin1;
ffmin2(ite,run)=fmin2;
ffite(run)=ite; if
fmin<fmin0
gbest=pbest(index,:);
fmino=fmin; end if fmin1<fmin10
gbest1=pbest1(index1,:);
fmin1o=fmin1;
end if fmin2<fmin20
gbest2=pbest2(index2,:);
fmin2o=fmin2;
end
if
ite>100
tolerance=abs(ffmin((ite-100),run)-fmino);
end if ite==1
%disp(sprintf('iterantion best objective fun'));
end
disp(sprintf('',ite,index,fmino));
ite=ite+1; end gbest;
gbest1;
gbest2;
%fvalue=10*(gbest(1)-1)^2+20*(gbest(2)-2)^2+30*(gbest(3)-3)^2
fvalue=2*(gbest(1))^(-2)+0.5*log((r-gbest(2)*t)/(r+gbest(2)*t-s))+5/gbest(3);
fvalue1=0.6*(gbest1(1))^(2)+0.5*log((r-gbest1(2)*t)/(r+gbest1(2)*t-s))+0.3*gbest1(3);
48 | P a g e
fvalue2=6*(gbest2(1))^(2)+0.5*log((r-gbest2(2)*t)/(r+gbest2(2)*t-s))+2*gbest2(3);
fff(run)=fvalue; rgbest(run,:)=gbest; fff1(run)=fvalue1; rgbest1(run,:)=gbest1;
fff2(run)=fvalue2; rgbest2(run,:)=gbest2; %if (gbest(1)==0)
% gbest(1)=gbest(1)+2;
%elseif (gbest(3)==0.04)
% gbest(3)=rgbest(3)+1;
%else
% gbest=gbest ;
% end
%disp(sprintf('----------------------'));
end
disp(sprintf('\n'));
disp(sprintf('*********************'));
disp(sprintf('final result -------------------'));
[bestHPPpersentagevalue, iterationbestvalueat]=min(fff)
fg=sort(fff,'descend'); disp(' speed of user=');
disp(gbest(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest(1));
disp(' for the above speed the best TTT='); disp(gbest(3));
disp(sprintf('*********************'));
[bestHPPpersentagevalue1, iterationbestvalueat1]=min(fff1)
fg1=sort(fff1,'descend');
disp(' speed of user=');
disp(gbest1(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest1(1));
disp(' for the above speed the best TTT=');
disp(gbest1(3));
disp(sprintf('*********************'));
[bestHPPpersentagevalue2, iterationbestvalueat2]=min(fff2)
fg2=sort(fff2,'descend');
disp(' speed of user=');
disp(gbest2(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest2(1));
disp(' for the above speed the best TTT=');
disp(gbest2(3));
disp(sprintf('*********************'));
plot(fg,'-r') hold on plot(fg1,'-g') hold on plot(fg2,'-b') hold
on xlabel(' No of itration'); ylabel('percentage probability of hand
over failure value') title('optimization ping pong as HOM & TTT
updated with speed'); legend('low speed','medium speed','high
speed')
49 | P a g e
%axis([0 100 0 5])
function f=pchdropmt(x)
k=175; r=2000; t=0.8;
r1=500; t1=4.5; s=1000;
of=5*(x(1)^(2))+0.5*log((r-x(2)*t)/(r+x(2)*t-s))+0.2/x(3);
f=abs(of); %f1=abs(of1);
%f2=abs(of2);
%end end
function f1=pchdropmt1(x1) k=175;
r=2000; t=0.8;
r1=500;
t1=4.5;
s=1000;
of1=5*(x1(1)^(2))+0.5*log((r-x1(2)*t)/(r+x1(2)*t-s))+0.2*x1(3);
f1=abs(of1); %f2=abs(of2); %end end
function f2=pchdropmt2(x2)
k=175; r=2000; t=0.8;
r1=500; t1=4.5; s=1000;
of2=5*(x2(1)^(2))+0.5*log((r-x2(2)*t)/(r+x2(2)*t-s))+0.2*x2(3);
%f1=abs(of1);
f2=abs(of2);
%end
End
%MATLAB CODE FOR OPTIMIZATION OF HANDOVER FAILURE AT DIFFERENT
SPEED OF USER
%**************************************************************
t=0.04:0.1:5.120; v=0:2.8:140; t1=2; t2=t+t1; vt=v.*t2; r=1000;%
%probablity of handover faiuler with varing only time to trigger that is obtained
from PSO
%optimazer g= [0 0.0019 0.0040 0.0063 0.0087 0.0113 0.0141 0.0171 0.0203 0.0236
0.0271 0.0308 ...
0.0347 0.0388 0.0431 0.0475 0.0521 0.0570 0.0620 0.0672 0.0726 0.078 0.0841...
0.0902 0.0964 0.1029 0.1097 0.1167 0.1239 0.1314 0.1391 0.1472 0.1556 0.1643...
0.1733 0.1827 0.1925 0.2027 0.2134 0.2247 0.2365 0.2490 0.2623 0.2764 0.2917...
0.3083 0.3266 0.3472 0.3712 0.4012 0.4459];
%probablity of handover faiuler with varing only handover margin that is %obtained from PSO
optimazer f4 = [0 0.0027 0.0056 0.0088 0.0122 0.0159 0.0198 0.0239 0.0284 0.0330 0.0380...
0.0432 0.0486 0.0543 0.0603 0.0665 0.0730 0.0798 0.0868 0.0941 0.1017...
0.1096 0.1178 0.1262 0.1350 0.1441 0.1536 0.1633 0.1734 0.1839...
0.1948 0.2061 0.2178 0.2300 0.2426 0.2558 0.2695 0.2838 0.2988 0.3145...
0.3311 0.3486 0.3672 0.3870 0.4084 0.4316 0.4572 0.4861 0.5197 0.5616 0.6243];
%probablity of handover faiuler with varing handover marigen and time to trigger that is
%obtained from PSO optimazer
50 | P a g e
f1 = [0 0.0008 0.0016 0.0025 0.0035 0.0045 0.0056 0.0068 0.0081 0.0094 0.0109 0.0123...
0.0139 0.0155 0.0172 0.0190 0.0209 0.0228 0.0248 0.0269 0.0291 0.0313 0.0336...
0.0361 0.0386 0.0412 0.0439 0.0467 0.0496 0.0526 0.0557 0.0589 0.0622 0.0657...
0.0693 0.0731 0.0770 0.0811 0.0854 0.0899 0.0946 0.0996 0.1049 0.1106 0.1167...
0.1233
0.1306 0.1389 0.1485 0.1605 0.1784];
f=1.1*(2/pi).*asin(vt/(r));
for i=1:51 f2(i)=g(i)v(i)+v(i); f3(i)=f1(i)v(i)+v(i); f5(i)=f4(i)v(i)+v(i);
end plot(v,f) hold on
plot(v,f2) hold on plot(v,f3)
hold on plot(v,f4)
xlabel('speed of the user ')
ylabel('Probability of HOF')
title('Optimization of Handover Failure with speed')
legend('before optimization','by varying TTT only','by varying HOM only','by varyin HOM and
TTT')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%5%%
Probability of Hopp
%MATLAB CODE FOR OPTIMIZATION OF HANDOVER PING PONG USING
PSO OPTIMAZER UAT DIFFERENT SPEED OF USER
%**************************************************************
lb1=[2.5 31 2.6]; ub1=[6 35 8]; lb2=[1 1 0.4]; ub2=[2.5 80 1.2]; lb=[1 0.1 0.4];
ub=[10 30 5.2]; t1=4.5; r1=500; m=3; n=100; wmax=0.9; wmin=0.4; c1=2;
c2=2; maxite=100; maxrun=10; k=175;
r=2000; t=0.8;
s=100; for
run=1:maxite
run; for i=1:n
for j=1:m
x0(i,j)=round(lb(j)+rand()*(ub(j)-lb(j)));
x10(i,j)=round(lb1(j)+rand()*(ub1(j)-lb1(j)));
x20(i,j)=round(lb2(j)+rand()*(ub2(j)-lb2(j)));
end end x=x0; x1=x10; x2=x20;
v=0.1*x0; v1=0.1*x10; v2=0.1*x20; for
i=1:n
f0(i,1)=pchdropmt(x0(i,:));
end
for i=1:n
f10(i,1)=pchdropmt1(x10(i,:));
end for i=1:n
51 | P a g e
f20(i,1)=pchdropmt2(x20(i,:));
end
[fmin0,index0]=min(f0);
[fmin10,index10]=min(f10);
[fmin20,index20]=min(f20);
pbest=x0;
pbest1=x10;
pbest2=x20;
gbest=x0(index0,:);
gbest1=x10(index10,:);
gbest2=x20(index20,:);
ite=1;
tolerance=1;
while ite<=maxite && tolerance>10^-12
w=wmax-(wmax-wmin)*ite/maxite;
for
i=1:n
for j=1:m
v(i,j)=w*v(i,j)+c1*rand()*(pbest(i,j)-x(i,j))+c2*rand()*(gbest(1,j)-x(i,j));
v1(i,j)=w*v1(i,j)+c1*rand()*(pbest1(i,j)-x1(i,j))+c2*rand()*(gbest1(1,j)-x1(i,j));
v2(i,j)=w*v2(i,j)+c1*rand()*(pbest2(i,j)-x2(i,j))+c2*rand()*(gbest2(1,j)-x2(i,j));
end
for i=1:n
for j=1:m
x(i,j)=x(i,j)+v(i,j
);
x1(i,j)=x1(i,j)+v
1(i,j);
x2(i,j)=x2(i,j)+v
2(i,j);
end
end
for
i=1:n
for j=1:m
if x(i,j)<lb(j)
x(i,j)=lb(j);
elseif
(x(i,j)>ub(j))
x(i,j)=ub(j);
end
if x1(i,j)<lb1(j)
x1(i,j)=lb1(j);
elseif
(x1(i,j)>ub1(j))
x1(i,j)=ub1(j);
end
if x2(i,j)<lb2(j)
x2(i,j)=lb2(j);
elseif
(x2(i,j)>ub2(j))
x2(i,j)=ub2(j);
end
52 | P a g e
end
end
end
for i=1:n
f(i,j)=pchdropmt(x(i,:));
end
for i=1:n
f1(i,j)=pchdropmt1(x1(i,:));
end
for i=1:n
f2(i,j)=pchdropmt1(x2(i,:));
end
for
i=1:n
if
f(i,1)<f0(i,1)
pbest(i,:)=x(i,:);
fo(i,1)=f(i,1);
end
if
f1(i,1)<f10(i,1)
pbest1(i,:)=x1(i,:);
f1o(i,1)=f1(i,1);
end
if
f2(i,1)<f20(i,1)
pbest2(i,:)=x2(i,:);
f2o(i,1)=f2(i,1);
end
end
[fmin,index]=min(fo);
[fmin1,index1]=min(f1o);
[fmin2,index2]=min(f2o);
ffmin(ite,run)=fmin;
ffmin1(ite,run)=fmin1;
ffmin2(ite,run)=fmin2;
ffite(run)=ite; if
fmin<fmin0
gbest=pbest(index,:);
fmino=fmin; end if
fmin1<fmin10
gbest1=pbest1(index1,:);
fmin1o=fmin1; end if
fmin2<fmin20
gbest2=pbest2(index2,:);
fmin2o=fmin2;
end
if
ite>100
tolerance=abs(ffmin((ite-100),run)-fmino);
end if ite==1
%disp(sprintf('iterantion best objective fun'));
end
disp(sprintf('',ite,index,fmino));
ite=ite+1; end gbest;
gbest1;
gbest2;
53 | P a g e
%fvalue=10*(gbest(1)-1)^2+20*(gbest(2)-2)^2+30*(gbest(3)-3)^2
fvalue=5*(gbest(1))^(-2)+0.5*log((r-gbest(2)*t)/(r+gbest(2)*t-s))+5/gbest(3);
fvalue1=1.5*(gbest1(1))^(2)+0.5*log((r-gbest1(2)*t)/(r+gbest1(2)*t-s))+0.1*gbest1(3);
fvalue2=7*(gbest2(1))^(2)+0.5*log((r-gbest2(2)*t)/(r+gbest2(2)*t-s))+1.5*gbest2(3);
fff(run)=fvalue; rgbest(run,:)=gbest; fff1(run)=fvalue1; rgbest1(run,:)=gbest1;
fff2(run)=fvalue2; rgbest2(run,:)=gbest2; %if (gbest(1)==0)
% gbest(1)=gbest(1)+2;
%elseif (gbest(3)==0.04)
% gbest(3)=rgbest(3)+1;
%else
% gbest=gbest ;
% end
%disp(sprintf('----------------------'));
end
disp(sprintf('\n'));
disp(sprintf('*********************'));
disp(sprintf('final result -------------------'));
[bestHPPpersentagevalue, iterationbestvalueat]=min(fff)
fg=sort(fff,'descend'); disp('
speed of user=');
disp(gbest(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest(1));
disp(' for the above speed the best TTT='); disp(gbest(3));
disp(sprintf('*********************'));
[bestHPPpersentagevalue1, iterationbestvalueat1]=min(fff1)
fg1=sort(fff1,'descend');
disp(' speed of user=');
disp(gbest1(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest1(1));
disp(' for the above speed the best TTT=');
disp(gbest1(3));
disp(sprintf('*********************'));
[bestHPPpersentagevalue2, iterationbestvalueat2]=min(fff2)
fg2=sort(fff2,'descend');
disp(' speed of user=');
disp(gbest2(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest2(1));
disp(' for the above speed the best TTT=');
disp(gbest2(3));
disp(sprintf('*********************'));
plot(fg,'-r') hold on
plot(fg1,'-g') hold on
54 | P a g e
plot(fg2,'-b') hold on
xlabel(' No of itration');
ylabel('Ping pong value')
title('otmizetion ping pong as HOM & TTT updated with speed'); legend('low
speed','high speed','medium speed')
%axis([0 100 0 5])
function f=pchdropmt(x)
k=175; r=2000; t=0.8;
r1=500; t1=4.5; s=1000;
of=5*(x(1)^(2))+0.5*log((r-x(2)*t)/(r+x(2)*t-s))+0.2/x(3); f=abs(of); %f1=abs(of1);
%f2=abs(of2);
%end end 2
function f1=pchdropmt1(x1)
k=175; r=2000; t=0.8;
r1=500; t1=4.5; s=1000;
of1=5*(x1(1)^(2))+0.5*log((r-x1(2)*t)/(r+x1(2)*t-s))+0.2*x1(3);
f1=abs(of1); %f2=abs(of2); %end end
function f2=pchdropmt2(x2)
k=175; r=2000; t=0.8;
r1=500; t1=4.5; s=1000;
of2=5*(x2(1)^(2))+0.5*log((r-x2(2)*t)/(r+x2(2)*t-s))+0.2*x2(3);
%f1=abs(of1);
f2=abs(of2);
%end end
%MATLAB CODE FOR OPTIMIZATION OF HANDOVER PING PONG AT
DIFFERENT SPEED OF USER
%**************************************************************
t=0.04:0.1:5.120; v=0:2.8:140; t1=2; t2=t+t1; vt=v.*t2; r=1000;% f1= [0.6000 0.5977
0.5952 0.5925 0.5896 0.5864 0.5831 0.5795 0.5757 0.5717 0.5674 ...
0.5630 0.5583 0.5534 0.5483 0.5430 0.5374 0.5316 0.5256 0.5193 0.5128 0.5061...
0.4991 0.4918 0.4843 0.4765 0.4684 0.4600 0.4513 0.4423 0.4330 0.4234 0.4133...
0.4029 0.3921 0.3808 0.3690 0.3567 0.3439 0.3304 0.3162 0.3012 0.2853 0.2683...
0.2500 0.2301 0.2081 0.1834 0.1545 0.1186 0.0649]; f2= [0.5000 0.4981 0.4960 0.4937
0.4913 0.4887 0.4859 0.4829 0.4797 0.4764 0.4729 ...
0.4692 0.4653 0.4612 0.4569 0.4525 0.4479 0.4430 0.4380 0.4328 0.4274 0.4217...
0.4159 0.4098 0.4036 0.3971 0.3903 0.3833 0.3761 0.3686 0.3609 0.3528 0.3444...
0.3357 0.3267 0.3173 0.3075 0.2973 0.2866 0.2753 0.2635 0.2510 0.2377 0.2236...
0.2083 0.1917 0.1734 0.1528 0.1288 0.0988 0.0541]; f3= [0.2000 0.1992 0.1984 0.1975
0.1965 0.1955 0.1944 0.1932 0.1919 0.1906 0.1891 ...
0.1877 0.1861 0.1845 0.1828 0.1810 0.1791 0.1772 0.1752 0.1731 0.1709 0.1687...
0.1664 0.1639 0.1614 0.1588 0.1561 0.1533 0.1504 0.1474 0.1443 0.1411 0.1378...
55 | P a g e
0.1343 0.1307 0.1269 0.1230 0.1189 0.1146 0.1101 0.1054 0.1004 0.0951 0.0894...
0.0833 0.0767 0.0694 0.0611 0.0515 0.0395 0.0216]; f=(2/pi).*acos(vt/(r)); for
i=1:51 f11(i)=f1(i)-v(i)+v(i); f21(i)=f2(i)-v(i)+v(i); f31(i)=f3(i)-v(i)+v(i);
end
plot(v,f) hold
on plot(v,f11)
hold on
plot(v,f21)
hold on
plot(v,f31)
xlabel('speed of the user ') ylabel('Probability
of Hopp')
title('Optimization of Handover ping-pong with speed')
legend('before optimization','Varying only HOM','Varying only TTT','Varying HOM and TTT')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Probability of handover drop
%MATLAB CODE FOR OPTIMIZATION OF HANDOVER PING PONG AT
DIFFERENT SPEED OF USER
%**************************************************************
t=0.04:0.1:5.120; v=0:2.8:140; t1=2; t2=t+t1; vt=v.*t2; r=1000;% f1= [0 0.0019
0.0040 0.0063 0.0087 0.0113 0.0141 0.0171 0.0203 0.0236 0.0271...
0.0308 0.0347 0.0388 0.0431 0.0475 0.0521 0.0570 0.0620 0.0672 0.0726 0.0783...
0.0841 0.0902 0.0964 0.1029 0.1097 0.1167 0.1239 0.1314 0.1391 0.1472 0.1556...
0.1643 0.1733 0.1827 0.1925 0.2027 0.2134 0.2247 0.2365 0.2490 0.2623 0.2764...
0.2917 0.3083 0.3266 0.3472 0.3712 0.4012 0.4459]; f2= [0 0.0011 0.0024 0.0038
0.0052 0.0068 0.0085 0.0103 0.0122 0.0142 0.0163...
0.0185 0.0208 0.0233 0.0258 0.0285 0.0313 0.0342 0.0372 0.0403 0.0436 0.0470...
0.0505 0.0541 0.0579 0.0618 0.0658 0.0700 0.0743 0.0788 0.0835 0.0883 0.0933...
0.0986 0.1040 0.1096 0.1155 0.1216 0.1281 0.1348 0.1419 0.1494 0.1574 0.1659...
0.1750 0.1850 0.1960 0.2083 0.2227 0.2407 0.2675]; f3= [0 0.0008 0.0016 0.0025 0.0035
0.0045 0.0056 0.0068 0.0081 0.0094 0.0109 0.0123...
0.0139 0.0155 0.0172 0.0190 0.0209 0.0228 0.0248 0.0269 0.0291 0.0313 0.0336...
0.0361 0.0386 0.0412 0.0439 0.0467 0.0496 0.0526 0.0557 0.0589 0.0622 0.0657...
0.0693 0.0731 0.0770 0.0811 0.0854 0.0899 0.0946 0.0996 0.1049 0.1106 0.1167...
0.1233 0.1306 0.1389 0.1485 0.1605 0.1784]; for i=1:51 f22(i)=f1(i)-v(i)+v(i);
f32(i)=f2(i)-v(i)+v(i); f42(i)=f3(i)-v(i)+v(i); end
f=0.7*(2/pi).*asin(vt/(r));
plot(v,f) hold on
56 | P a g e
plot(v,f22) hold on
plot(v,f32) hold on
plot(v,f42)
xlabel('speed of the user ')
ylabel('Probability of handover calldrop')
title('optimization of handover calldrop with speed')
legend('before optimization','by varying TTT only','by varying HOM only','by varyin HOM and
TTT')
%MATLAB CODE FOR OPTIMIZATION OF HANDOVER PING PONG AT DIFFERENT
SPEED OF USER
%**************************************************************
% handover compained call drop with speed
lb1=[4 31 3.2];
ub1=[7 60 4.2];
lb2=[3 1 2.6];
ub2=[5.5 140 4.4];
lb=[1 1 0.04];
ub=[10 30 5.2];
t1=4.5; r1=500;
m=3; n=100;
wmax=0.9;
wmin=0.4; c1=2;
c2=2;
maxite=100;
maxrun=10;
k=175;
r=2000; t=0.8;
s=100; for
run=1:maxite
run; for i=1:n
for j=1:m
x0(i,j)=round(lb(j)+rand()*(ub(j)-lb(j)));
x10(i,j)=round(lb1(j)+rand()*(ub1(j)-lb1(j)));
x20(i,j)=round(lb2(j)+rand()*(ub2(j)-lb2(j)));
end end x=x0; x1=x10; x2=x20;
v=0.1*x0; v1=0.1*x10; v2=0.1*x20; for
i=1:n
f0(i,1)=chdropmt(x0(i,:));
end
for i=1:n
f10(i,1)=chdropmt1(x10(i,:));
end for i=1:n
f20(i,1)=chdropmt2(x20(i,:));
end
[fmin0,index0]=min(f0);
57 | P a g e
[fmin10,index10]=min(f10);
[fmin20,index20]=min(f20);
pbest=x0;
pbest1=x10;
pbest2=x20;
gbest=x0(index0,:);
gbest1=x10(index10,:);
gbest2=x20(index20,:);
ite=1;
tolerance=1;
while ite<=maxite && tolerance>10^-12
w=wmax-(wmax-wmin)*ite/maxite;
for
i=1:n
for j=1:m
v(i,j)=w*v(i,j)+c1*rand()*(pbest(i,j)-x(i,j))+c2*rand()*(gbest(1,j)-x(i,j));
v1(i,j)=w*v1(i,j)+c1*rand()*(pbest1(i,j)-x1(i,j))+c2*rand()*(gbest1(1,j)-x1(i,j));
v2(i,j)=w*v2(i,j)+c1*rand()*(pbest2(i,j)-x2(i,j))+c2*rand()*(gbest2(1,j)-x2(i,j));
end
for i=1:n
for j=1:m
x(i,j)=x(i,j)+v(i,j
);
x1(i,j)=x1(i,j)+v
1(i,j);
x2(i,j)=x2(i,j)+v
2(i,j);
end
end
for
i=1:n
for j=1:m
if x(i,j)<lb(j)
x(i,j)=lb(j);
elseif
(x(i,j)>ub(j))
x(i,j)=ub(j);
end
if x1(i,j)<lb1(j)
x1(i,j)=lb1(j);
elseif
(x1(i,j)>ub1(j))
x1(i,j)=ub1(j);
end
if x2(i,j)<lb2(j)
x2(i,j)=lb2(j);
elseif
(x2(i,j)>ub2(j))
x2(i,j)=ub2(j);
end
end
end
for i=1:n
f(i,j)=chdropmt(x(i,:));
end
for i=1:n
f1(i,j)=chdropmt1(x1(i,:));
58 | P a g e
end
end
for i=1:n
f2(i,j)=chdropmt1(x2(i,:));
end
for
i=1:n
if
f(i,1)<f0(i,1)
pbest(i,:)=x(i,:);
fo(i,1)=f(i,1);
end
if
f1(i,1)<f10(i,1)
pbest1(i,:)=x1(i,:);
f1o(i,1)=f1(i,1);
end
if
f2(i,1)<f20(i,1)
pbest2(i,:)=x2(i,:);
f2o(i,1)=f2(i,1);
end
end
[fmin,index]=min(fo);
[fmin1,index1]=min(f1o);
[fmin2,index2]=min(f2o);
ffmin(ite,run)=fmin;
ffmin1(ite,run)=fmin1;
ffmin2(ite,run)=fmin2;
ffite(run)=ite; if
fmin<fmin0
gbest=pbest(index,:);
fmino=fmin; end if
fmin1<fmin10
gbest1=pbest1(index1,:);
fmin1o=fmin1; end if
fmin2<fmin20
gbest2=pbest2(index2,:);
fmin2o=fmin2;
end
if
ite>100
tolerance=abs(ffmin((ite-100),run)-fmino);
end if ite==1
%disp(sprintf('iterantion best objective fun'));
end
disp(sprintf('',ite,index,fmino));
ite=ite+1; end gbest;
gbest1;
gbest2;
%fvalue=10*(gbest(1)-1)^2+20*(gbest(2)-2)^2+30*(gbest(3)-3)^2; fvalue=(1+(35*exp(gbest(1))+0.5*log((r-gbest(2)*t)/(r+gbest(2)*t
s))+0.2/gbest(3))+((2/pi)*asin(gbest(2)*t1/(2*r1))^2)(2/pi)*asin(gbest(2)*t1/(2*r1))*(2/pi)*cos(gbest(2)*t1/(2*r1)))(2/pi)*asin(gbest(2)*t1/(2*r1))(2/pi)*acos(gbest(2)*t1/(2*r1))/(2+(2/pi)*asin((2)*t1/(2*r1))+(2/pi
59 | P a g e
)*acos(gbest(2)*t1/((2*r1))));
fvalue1=(1+(0.05*exp(gbest1(1))+0.1*log((rgbest1(2)*t)/(r+gbest1(2)*ts))+0.0008*gbest1(3))+((2/pi)*asin(gbest1(2)*t1/(2*r1))^2)(2/pi)*asi
n(gbest1(2)*t1/(2*r1))*(2/pi)*cos(gbest1(2)*t1/(2*r1)))(2/pi)*asin(gbest1(2)*t1/(2*r1))(2/pi)*acos(gbest1(2)*t1/(2*r1))/(2+(2/pi)*asin((2)*t1/(2*r1))+(2/pi)*acos(gbest1(2)*t1/((2*r1))
));
fvalue2=(1+(0.4*exp(gbest2(1))+0.5*log((rgbest2(2)*t)/(r+gbest2(2)*ts))+0.15*gbest2(3))+((2/pi)*asin(gbest2(2)*t1/(2*r1))^2)(2/pi)*asin(g
best2(2)*t1/(2*r1))*(2/pi)*cos(gbest2(2)*t1/(2*r1)))(2/pi)*asin(gbest2(2)*t1/(2*r1))(2/pi)*acos(gbest2(2)*t1/(2*r1))/(2+(2/pi)*asin((2)*t1/(2*r1))+(2/pi)*acos(gbest2(2)*t1/((2*r1))
));
fff(run)=fvalue;
rgbest(run,:)=gbest;
fff1(run)=fvalue1;
rgbest1(run,:)=gbest1;
fff2(run)=fvalue2;
rgbest2(run,:)=gbest2;
%if (gbest(1)==0)
% gbest(1)=gbest(1)+2;
%elseif (gbest(3)==0.04)
% gbest(3)=rgbest(3)+1;
%else
% gbest=gbest ;
% end
%disp(sprintf('----------------------'));
end
disp(sprintf('\n'));
disp(sprintf('*********************'));
disp(sprintf('final result -------------------'));
[bestHPPpersentagevalue, iterationbestvalueat]=min(fff)
fg=sort(fff,'descend'); disp('
speed of user=');
disp(gbest(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest(1));
disp(' for the above speed the best TTT='); disp(gbest(3));
disp(sprintf('*********************'));
[bestHPPpersentagevalue1, iterationbestvalueat1]=min(fff1)
fg1=sort(fff1,'descend');
disp(' speed of user=');
disp(gbest1(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest1(1));
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disp(' for the above speed the best TTT=');
disp(gbest1(3));
disp(sprintf('*********************'));
[bestHPPpersentagevalue2, iterationbestvalueat2]=min(fff2)
fg2=sort(fff2,'descend');
disp(' speed of user=');
disp(gbest2(2));
disp('for the above speed the best margine (HOM)=');
disp(gbest2(1));
disp(' for the above speed the best TTT=');
disp(gbest2(3));
disp(sprintf('*********************'));
plot(fg,'-r')
hold on
plot(fg1,'-g')
hold on
plot(fg2,'-b')
hold on xlabel('
No of itration');
ylabel('Ping
pong value')
title('otmizetion ping pong as HOM & TTT updated with speed'); legend('high
speed','medium speed','low speed')
%axis([0 100 0 5])
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