Post on 23-Jan-2023
1
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
A
Synopsis
ON
MOBILE CELL SELECTION IN 4G LONG TERM
EVOLUTION-ADVANCED (LTE-A) NETWORKSSubmitted in Partial Fulfillment of the Requirement
for the Award of the
Degree of
MASTER OF TECHNOLOGY
In
Electronics & Communication Engineering Submitted by
MURTADHA ALI NSAIF SHUKUR
Roll No: 11127232Under the Supervisions of
Dr. H.P.Sinha
Dr. Kuldip Pahwa
ECE Department
2014
2
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Department of Electronics & Communication Engineering
M.M Engineering College, Maharishi Markandeshwar
University Mullana (Ambala), Haryana, India
133207
CONTENTS1. Introduction-------------------------------------------------
----------------------------------( 4 )
2. LTE
evolution. .-------------------------------------------------
-----------------------------( 8 )
3. Introduction to LTE-Advanced
------------------------------------------------------------(
9 )
4. New features of LTE-Advanced: from Release 8 to Release 10
---------------------( 12 )
5. Difference between LTE and LTE-
Advanced-------------------------------------------( 13 )
6. Key challenges in implementing LTE and LTE-
Advanced---------------------------( 14 )
7. Cell
Selection----------------------------------------------------
----------------------------( 17 )
8. Key literature
survey.------------------------------------------------------
------------------( 18 )
3
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
9. Motivation.--------------------------------------------------
----------------------------------( 26 )
10. Formulation of problem
-------------------------------------------------------------
-------( 27 )
11. Objectives------------------------------------------------
-------------------------------------( 27 )
12. Research
methodology--------------------------------------------------
--------------------( 27 )
13. Time
schedule .---------------------------------------------------
---------------------------( 29 )
14. References------------------------------------------------
------------------------------------( 30 )
4
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
LIST OF TABLES
1. Comparison of parameters of UMTS, HSPA, HSPA+ and
LTE.--------------------- ( 9 )
2. Specification of LTE
system. .----------------------------------------------------
--------- ( 9 )
3. Difference between specifications of LTE and LTE-
Advanced-----------------------( 14 )
4. Research
methodology--------------------------------------------------
--------------------( 29 )
5. Time
schedule-----------------------------------------------------
---------------------------( 29 )
5
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
LIST OF FIGURES
Figure (1) LTE Radio Access Network
Architecture-----------------------------------------( 5 )
Figure (2) OFDMA and SC-FDMA in LTE
---------------------------------------------------( 7 )
Figure (3) MIMO in LTE
---------------------------------------------------------------
---------( 8 )
6
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Figure (4) LTE /SAE
architecture---------------------------------------------------
------------( 8 )
Figure (5) MIMO scheme
(8x4)----------------------------------------------------------
-------( 11 )
Figure (6) Relay types in LTE
systems--------------------------------------------------------
( 13 )
Figure (7) Example of persistent scheduling
allocation-------------------------------------( 17 )
Figure (8) Different types of cells in a
network----------------------------------------------( 18 )
Figure (9) An example of a possible scenario in a real
network---------------------------( 28 )
7
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
1.Introduction to LTE systemsLong Term Evolution (LTE) is the result of the standardization
work done by the 3GPP to achieve a new high speed radio access
in the mobile communications frame. 3GPP is a collaboration of
groups of telecom associations working on Global System for
Mobile Communication (GSM) [3]. 3GPP published and introduced
the various standards for IP based system in Release 8, which
was also termed Long Term Evolution and abbreviated as LTE.
Initially, LTE was introduced in the Release 8 in 2008. In
2010, the Release 9 was introduced to provide enhancements to
LTE and in 2011 Release 10 was brought as LTE-Advanced, to
expand the limits and features of Release 8 and to meet the
requirements of the International Mobile Telecommunications-
Advanced (IMT-Advanced) of ITU-R for the fourth generation of
mobile technologies (4G), and the future operator and end
user’s requirements. The key reason of the evident of the LTE-A
is the growing demand for network services, such as VoIP, web
8
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
browsing, video telephony, and video streaming, with
constraints on delays and bandwidth requirements, poses new
challenges in the design of the future generation cellular
networks [4]. Recently in 2011, LTE was further developed
through Release 10 to satisfy ITU’s IMT-Advanced requirements
for 4G cellular systems. LTE radio transmission and reception
specifications are documented in TS 36.101 for the UE (User
Equipment) and TS 36.104 for the eNB (Evolved Node B). As per
these specifications, LTE is theoretically capable of
supporting up to 1Giga Bits per second (1Gbps) for fixed user
and up to 100 Mega Bits per second (100 Mbps) for high speed
user. This is considerably high speed. For this reason, both
research and industrial communities are making a considerable
effort on the study of LTE systems, proposing new and
innovative solutions in order to analyze and improve their
performance.
In principle, LTE access network based on Orthogonal Frequency
Division Multiple Access (OFDMA) in downlink and Single Carrier
Frequency Division Multiple Access (SC-FDMA) for uplink. It is
expected to support a wide range of multimedia and Internet
services even in high mobility scenarios[4]. Therefore, it has
been designed to provide high data rates, low latency, and an
improved spectral efficiency with respect to previous 3G
networks. LTE networks are highly flexible for a worldwide
market and offer a variable bandwidth feature that gives to
network operators the possibility to throttle the bandwidth
occupation between 1.4 and 20MHz. The most important novelty
introduced by LTE specifications is the enhanced QoS support by
9
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
means of new sophisticated RRM (Radio Resource Management)
techniques [3]. The overall goal of LTE technology is to
significantly increasing peak data rates scaled linearly
according to spectrum allocation, improving spectral
efficiency, lowering costs, improving services, making use of
new spectrum opportunities, improved quality of service, and
better integration with other open standards. Also LTE does not
support soft handover, so there is no need for a centralized
data-combining function in the network. However, in order to
achieve these goals, LTE implementers and users have to face a
number of challenges. For example, mobile operators will need
to deal with specific challenges associated with LTE, such as
interoperability with legacy and other 4G systems, ensuring
end-to-end network QoS and high-quality service delivery, and
interaction with IMS for the delivery of multimedia services
and voice.
The LTE radio access network architecture is shown in Figure 1.
LTE encompasses the evolution of the radio access through the
Evolved Universal Terrestrial Radio Access Network (EUTRAN).
LTE is accompanied by an evolution of the non-radio aspects
under the name ‘System Architecture Evolution’ (SAE) which
includes the Evolved Packet Core (EPC) network. Together LTE &
SAE comprise the Evolved Packet System (EPS).
10
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Figure 1: LTE Radio Access Network
Architecture [2].
In Figure 1, EPS uses the concept of EPS bearers to route IP
traffic from a gateway in the PDN to the User Equipment (UE). A
bearer is an IP packet flow with a defined Quality of Service
(QoS) between the gateway and the UE. The E-UTRAN with EPC
together set up and release bearers as required by
applications. The eNodeB is responsible for Radio resource
Management (RRM) – assignment, reassignment and release of
radio resources. It is used in the signaling of Access stratum
signaling protocols, along with scheduling and transmission of
paging messages received from the MME and broadcast information
received from the Mobility Management Entity (MME). Other
functions such as measurement gathering for scheduling,
mobility decisions and routing the user plane date to Serving
Gateway (SGW) are also taken care by the eNodeB, The User
11
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Equipment is mainly responsible for 3 functions: 1)
To mark its entry into the signal network and several other
changes, 2) to report its location while it is in the idle
mode, and 3) requesting uplink grants to transmit data while in
active mode. Apart from these functions several other
measurements such as Reference Symbol Received Power (RSRP),
Reference Symbol Received Quality (RSRQ), Received Signal
Strength Indicator (RSSI), and Signal to Noise Ratio (SNR) are
also carried out by the UE.
Mobile Management Entity (MME) helps authenticate UEs into the
system, tracks active and idle UEs and pages UEs when triggered
by the arrival of the new data. When a UE attaches to an eNB,
the eNB selects an MME. MME in turn selects the Serving Gateway
(SGW) and the Packet Data Network Gateway (P-GW) that will
handle the user’s bearer packets. MME also takes care of the
Non-Access stratum signaling and authentication (in conjunction
with the Home Subscriber Server - HSS). Serving Gateway (SGW)
routes and forwards user data packet, terminates downlink data
for idle UEs and is also the local mobility anchor for inter-
eNodeB handover. The mobility anchor function applies to both
UE in the E-UTRAN and other 2G/3G technologies. The S-GW also
maintains a buffer for each idle UE and holds the packets until
the UE is paged and an RF channel is re-established. For each
UE associates with the Evolved Packet Core (EPC), at a given
point of time there is a single UE. Other functions of the S-GW
include IP backhaul admission and congestion control, point of
policy enforcement and IP backhaul Quality of Service (QoS).
Packet Gateway (P-GW) is responsible for the UE Internet
12
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Protocol (IP) address assignment and provides connectivity to
the external packet data networks. The P-GW provides charging
(billing) support, packet filtering/screening, policy
enforcement and lawful intercept. If a UE is accessing multiple
packet data networks, it may have connectivity to more than 1
P-GW. Home Subscriber Server (HSS) is the master database that
contains the UE profiles and authentication data used by the
MME for authenticating and authorizing UEs. It also stores the
location information of the UE which is used for user mobility
and inter-technology handovers. The HSS communicates with the
MME using Diameter protocol. Policy and Charging Rules Function
(PCRF) creates rules for setting policy and charging rules for
the UE. It provides network control for service data flow
detection, gating, QoS authorization and flow based charging.
It applies security procedures, as required by the operator,
before accepting service information. Decides how a certain
service data flow will be treated in the P-GW and ensures that
the P-GW user plane traffic mapping and treatment matches the
user’s subscription profile. Serving GPRS (General Packet Radio
System) Support Node (SGSN) is responsible for the delivery of
data packets to and from UEs within its geographical service
area. The SGSN provides the interfaces between the MME and S-GW
in the Evolved Packet Core (EPC) [2]. The technologies used to
implement all the components of LTE are:
Orthogonal Frequency Division Modulation (OFDM): OFDM
technology has been incorporated into LTE because it enables
high data bandwidths to be transmitted efficiently while
still providing a high degree of resilience to reflections
13
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
and interference. The access schemes differ between the
uplink and downlink: OFDMA (Orthogonal Frequency Division
Multiple Access) is used in the downlink; whereas, SC-FDMA
(Single Carrier - Frequency Division Multiple Access) is used
in the uplink, as shown in Figure 2. SC-FDMA is used in view
of the fact that its peak-to-average power ratio (PAPR) is
small and the more constant power enables high RF power
amplifier efficiency in the mobile handsets - an important
factor for battery powered equipment.
Figure 2: OFDMA and SC-FDMA in LTE [3].
Multiple Input Multiple Output (MIMO): One of the main
problems that previous telecommunications systems have
encountered is that of multiple signals arising from the many
reflections that they encountered. By using MIMO (Figure 3),
these additional signal paths can be used to advantage and to
increase the throughput. When using MIMO, it is necessary to
use multiple antennas to enable the different paths to be
distinguished. Accordingly schemes using 2 x 2, 4 x 2, or 4 x
4 antenna matrices can be used. While it is relatively easy
to add further antennas to a base station, the same is not
true of mobile handsets; where, the dimensions of the user
14
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
equipment limit the number of antennas can be placed at least
half a wavelength apart.
Figure 3: MIMO in LTE [3].
System Architecture Evolution (SAE): With the very high
data rate and low latency requirements for 3G LTE, it is
necessary to evolve the system architecture to enable the
improved performance to be achieved. The new SAE network
(Figure 4) is based upon the GSM/WCDMA core networks to
enable simplified operations and easy deployment, as shown in
Figure 4. Despite this, the SAE network brings in some major
changes, and allows far more efficient and effect transfer of
data.
Figure 4: LTE /SAE architecture [2].
2. LTE Evolution
15
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Although there are major step changes between LTE and its 3G
predecessors, it is nevertheless looked upon as evolution of
the UMTS/3GPP 3G standards as shown in the Table 1. Although
LTE uses a different form of radio interface using OFDMA/SC-
FDMA instead of CDMA; yet there are many similarities with the
earlier forms of 3G architecture and there is scope for much
re-use. LTE can, therefore, be seen to provide a further
evolution of functionality, increased speeds and general
improved performance.
Table 1: Comparison of parameters of UMTS, HSPA, HSPA+ and LTE
WCDMA(UMTS)
HSPAHSDPA/HSUPA
HSPA+ LTE
Max downlink speed
384Kbps 14Mbps 28Mbps 100Mbps
Max uplink speed
128Kbps 5.7Mbps 11Mbps 50Mbps
Latency round trip time
150ms 100ms 50ms(max)
~10ms
3GPP releases Rel99/4
Rel 5/6 Rel 7 Rel 8/10
Approx years of initial roll out
2003/04 2005/06(HSDPA)2007/08(HSUPA)
2008/09 2009/10
Access technology
CDMA CDMA CDMA OFDMA/SC-FDMA
In addition to this, LTE is an all IP based network, supporting
both IPv4 and IPv6. There is also no basic provision for voice;
although, this can be carried as VoIP. The key measure of LTE
is the ability to provide very high bit rates. In addition, it
provides high spectral efficiency, very low latency and support
16
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
of variable bandwidth. The detailed specification of LTE is
given in Table 2.
Table 2: Specification of LTE [1-3].
Specification Details Peak downlinkspeed 64QAM(Mbps)
100 (SISO), 172 (2x2 MIMO), 326 (4x4 MIMO)
Peak uplink speed(Mbps)
50 (QPSK), 57 (16QAM), 86 (64QAM)
Data type All packet switched data (voice and data).No circuit switched.
Channelbandwidths
1.4, 3, 5, 10, 15 and 20 MHz
Duplex schemes FDD and TDDLatency Idle to active less than 100 ms
Small packets ~10 msSpectralEfficiency
Downlink: 3 to 4 x HSDPA Rel. 6Uplink: 2 to 3 x HSUPA Rel. 6
Supported antennaconfigurations
Downlink: 4x2, 2x2, 1x2, 1x1Uplink: 1x2, 1x1
Access schemes OFDMA (downlink)SC-FDMA (uplink)
Modulation typessupported
QPSK, 16QAM, 64QAM (Uplink and downlink)
Coverage Full performance up to 5 Km, Slight degradation (5 – 30) Km
3. Introduction to LTE-Advanced LTE-Advanced extends the features of LTE in order to exceed or
at least meet the IMT-Advanced requirements. It should be a
real broadband wireless network that behaves as an advanced
fixed network like FTTH (Fiber-To-The-Home) but with better
quality of service. It also must fulfill operator’s demands
like a reduced cost per Mbit transmitted, compatibility with
all 3GPP previous systems and a better service providing in
17
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
terms of homogeneity, constant quality of the connection and
smaller latency. The key goals of LTE-Advanced are:
Support of asymmetrical bandwidths and larger bandwidth
(maximum of 100MHz): In LTE (release 8), the bandwidth could
have different sizes but had to be the same in the downlink
and in the uplink. In LTE-Advanced (Release 10) bandwidths
can be different because due to actual demand in mobile
networks, the traffic from the station to the user is bigger
than the one from the user to the station. And they can be as
asymmetric as they want within the limit of the 100 MHz LTE-
Advanced provides. The sum of both bandwidths (downlink +
uplink) cannot exceed 100 MHz. Carrier aggregation to achieve
wider bandwidth is a key factor as well as the support of
spectrum aggregation, to achieve higher bandwidth
transmissions.
Enhanced multi-antenna transmission techniques: LTE
introduced MIMO in the data transmission. However in LTE-
Advanced, the MIMO scheme has to be extended to gain spectrum
efficiency (which is proportional to the number of antennas
used), cell edge performance and average data rates. LTE-
Advanced considers a configuration 8x8 in the downlink and
4x4 in the uplink. LTE-Advanced tries to get the network
closer to the user to provide a uniform user experience and
to increase the capacity of the network. For that purpose, it
uses advanced topology networks. Advanced topology networks
provide the benefits and the performance increase. Some of
the characteristics of this type of networks are [1]:
18
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
They are self-organizing networks; this will minimize the
number of Drive Tests for example.
Intelligent Node Association
Support for relays
Adaptive Resource Allocation
Multicarrier (spectrum aggregation)
Coordinated Beamforming
LTE-Advanced is intended to support further evolution of LTE
and to establish EUTRAN as an IMT-Advanced technology. LTE-A
also known as LTE release 10 is set to provide higher bitrates
in a cost efficient way and at the same time also focus on
higher capacity, i.e.:
Increased peak data rate DL 3Gbps, UL 1.5Gbps
Increased number of simultaneously active subscribers
Improved performance and higher spectral efficiency
Worldwide functionality and roaming
Compatibility of services
Inter working with other radio access systems
To achieve these goals, several enhancements are being
considered. At the physical layer, LTE is expected to provide
substantial improvement in peak, average and cell-edge spectral
efficiencies, under the assumption of 8x8 antenna configuration
in the downlink and 4x4 in the uplink. Under the same
assumptions, peak spectral efficiency of 30 and 15bps/Hz should
be met for the downlink and uplink respectively. Some of the
physical layer enhancement techniques are Carrier Aggregation,
Co-ordinated Multipoints, Relays, uplink and downlink spatial
multiplexing up to 4 and 8 transmit antennae respectively.
19
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Small cells such as picocells and femtocells bring the network
closer to users and provide a big leap in performance[5]. But
LTE-Advanced optimizes small cell performance through features
such as ‘Range Expansion’ to make the leap even more
significant. Simply adding small cells to a network only
benefits users close to the cell, but LTE-A enhances the users
experience for all the users including those on the cell edge
with higher data rates, even when the small cells are not
positioned in optimal locations. Additionally, the advanced
receivers allow devices to discover small cells early and
further increase performance of range expansion. To achieve the
requirements set by LTE-A, support for wider transmission
bandwidths, other than the 20Mhz bandwidth set aside for LTE
specified in 3GPP release 8/9, is required. The preferred
solution to this is Carrier Aggregation (CA). It is one of the
most distinct features of LTE-A. CA allows the expansion of
effective bandwidth delivered to a user terminal through
concurrent utilization of radio resources across multiple
carriers. Multiple component carriers are then aggregated to
form a larger transmission bandwidth. LTE-A can aggregate up to
5 carriers (up to 100MHz) to increase user data rates and
capacity for busty applications [7]. The Aggregation(s) when
combined with higher order MIMO can provide extremely high data
rates, as shown in Figure 5.
20
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Figure 5: MIMO scheme
(8x4) [2].
4. New features of LTE-Advanced: from Release 8 to
Release 10 As discussed above, LTE is the result of the standardization
work done by the 3GPP to achieve a new high speed radio access
in the mobile communications frame. It was introduced in the
sequence of Release 8 in 2008, the Release 9 in 2010 and
Release 10 in 2011 to meet the requirements of the IMT-Advanced
of ITU-R for the fourth generation of mobile technologies (4G),
and the future operator and end user’s requirements. The key
measure of LTE is the ability to provide very high bit rates.
In addition, it provides high spectral efficiency, very low
latency and support of variable bandwidth. Some of the LTE new
features are:
Orthogonal Frequency Division Multiple Access: OFDMA, a
multi-user version of the modulation scheme called Orthogonal
Frequency-Division Multiplexing, in the downlink. This gives
robustness against multipath interference and connects with
some advanced techniques also used like MIMO (shown in Figure
5) and frequency domain channel dependent scheduling.
21
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Single Carrier Frequency Division Multiple Access with
Dynamic Bandwidth in the uplink: SC-FDMA has lower peak-to-
average power ratio (PAPR) which is a major improvement for
the user equipment (UE), as it improves the transmission
power efficiency.
Multiple Input Multiple Output antenna solutions: MIMO is
used to improve the data bit rates and spectral efficiency.
It consists of using multiple antennas in both the receiver
and transmitter in order to use the multipath effects, which
reduces the interference and leads to high transmission
rates. MIMO works by dividing the data flow into multiple
unique flows, and transmits them in the same radio channel at
the same time[12].
Coordinated multipoint transmission and reception (CoMP): It
is used to improve the received signal of the user terminal.
Both the serving and neighbor cells are used in a way that
the co-channel interference from neighboring cells is
reduced. It implies dynamic coordination between
geographically separated transmission points in the downlink
and reception at separated points in the uplink. This
mechanism is used to improve the coverage of high data rates
and to increase the system bit rate[15].
Relaying: Relaying increases the coverage area and capacity
of the network. User’s mobile devices communicate with the
relay node, which communicates with a donor eNB (enhanced
Node B). Relay nodes can also support higher layer
functionality like decoding user data from the donor eNB and
re-encoding the data before transmitting it to the user
22
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
terminal. There are two types of relay nodes as shown in
Figure 6 below. Type 1 relay nodes control their cells with
their own cell identity, and are used for the purpose of the
transmission of synchronization channels and reference
symbols. This type of relays guarantee compatibility with
previous releases as it appeared in Release 8 to provide
service to Release 8 mobile terminals. However, Type 2 relay
(Figure 6) nodes don’t own an identity, so the mobile user
won’t be able to distinguish if a transmission comes from the
donor eNB or from the relay. eNBs transmit control data and
relays transmit user data.
(a) Type 1 relays (b) Type 2 relaysFigure 6: Relay types in LTE systems [4].
5. Difference between LTE and LTE-Advanced LTE and LTE Advanced are high speed 4G wireless technologies.
These 4G technologies give virtually, LAN reality to mobile
handsets and to feel the real experience of the triple play
services such as voice, video and high speed data. Both LTE and
LTE Advanced offer high speed access to Internet equivalent to
FE connection. The key differences between LTE and LTE-Advanced
are mentioned below and in Table 3.
23
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
LTE: 3GPP has completed the specification for Long Term
Evolution as part of Release 8. The work on LTE began in 2004
and completed in 2009 and first deployment occurred in 2010.
LTE is supposed to offer 326 Mbps with 4×4 MIMO and 172 Mbps
with 2×2 MIMO in 20 MHz spectrum. LTE supports both FDD
(Frequency Division Duplexing) and TDD (Time Division
Multiplexing). The major advantage in LTE is high throughput
with low latency. In reality LTE is offering 120 Mbps and the
speed depends on the user’s closeness to the tower and the
number of users in a particular cell area[5].
LTE Advanced: After the success of LTE, 3GPP is recently
addressing to satisfy the specification of IMT Advanced
(International Mobile Telecommunications-Advanced) set for
LTE Advanced. The major advantage of LTE Advanced is its
backward compatibility meaning that, LTE devices can work in
LTE Advanced and LTE Advanced devices can operate in LTE as
well. LTE Advanced standards are defined in 3GPP release 10.
LTE Advanced expected to offer download peak rate of 1000
Mbps in a low mobility scenario and 100 Mbps in a high
mobility. Low mobility is defined as pedestrian speed (10
Km/hr) and high mobility as 350 Km/hr. LTE Advanced offers
speed of 40 times faster than 3G commercial networks. LTE
Advanced offers All-IP, High Speed, Low Latency and high
quality spectrum efficiency in mobile network which enhances
the experience of mobile triple play services. The key
differences between LTE and LTE Advanced are mentioned in
Table 3 below.
24
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Table 3: Difference between specifications of LTE and LTE-
Advanced.
Specification LTE LTE-APeak Data Rate DownLink
150 Mbps 1 Gbps
Peak Data Rate Up Link
75 Mbps 500Mbps
Transmission Band (DL)
20MHz 100MHz
Transmission Band (UL)
20MHz 40MHz
Scalable Bandwidths 1.3,3,5,10, and 20MHz
Up to 20-100MHz
Capacity 200 active usersper cell in 5MHz
3 times higherthan LTE
6. Key challenges in implementing LTE and LTE-AdvancedThe main design factors that should be taken into account
before defining an allocation policy for LTE are:
A. Key design aspects
1) Complexity and scalability: Ideally, A LTE packet scheduler
works with a time granularity of 1ms; i.e., it has to take
allocation decisions every TTI. Therefore, low complexity and
scalability are fundamental requirements for limiting
processing time and memory usage. Finding the best allocation
decision through complex and non-linear optimization problems
or through an exhaustive research over all the possible
combinations would be too expensive in terms of computational
cost and time [14]. For this reason, FDPS decisions are usually
based on the computation of per-RB metrics for each user. In
this manner, complexity reduction is achieved because each RB
is allocated to the user with the highest metric independently
25
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
of other RBs. Let N and R be the number of active users in the
current TTI and the number of available RBs, respectively; the
scheduler has to calculate M = N.R metrics every TTI. This
assures the scalability requirement thanks to the linear
dependence on the number of resource blocks and users.
2) Spectral efficiency: Effective utilization of radio
resources is one of the main goals to be achieved. To this aim,
several types of performance indicators can be considered: for
instance, a specific policy could aim at maximizing the number
of users served in a given time interval or, more commonly, the
spectral efficiency (expressed in bit/s/Hz) by always serving
users that are experiencing the best channel conditions. One of
the most used efficiency indicators is the user good-put, a
measure of the actual transmission data rate without including
layer two overheads and packet retransmissions due to physical
errors.
3) Fairness: A blind maximization of the overall cell throughput
surely enables effective channel utilization in terms of
spectral efficiency, but also brings to very unfair resource
sharing among users. Fairness is therefore a major requirement
that should be taken into account to guarantee minimum
performance also to the cell-edge users (or in general to users
experiencing bad channel conditions).
4) QoS Provisioning: As well-known, QoS provisioning is very
important in next generation mobile networks. It is a major
feature in all-IP architectures. LTE maps QoS constrained flows
to dedicated radio bearers that, depending on their QCIs,
enable special RRM procedures. QoS constraints may vary
26
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
depending on the application and they are usually mapped into
some parameters: minimum guaranteed bitrate, maximum delivering
delay, and packet loss rate. Thus, it is important to define
QoS-aware schedulers.
B. Practical limitations in real LTE systems
Several aspects of LTE deployment in real environment may
impact on the choice of the best allocation schemes to be
adopted. These are:
1) Uplink limitations: In downlink, due to the use of OFDMA, the
scheduler can fill out the RB allocation mask without ordering
constraints. Instead, SC-FDMA method, used for uplink
transmissions, allows the UEs to transmit only in a single
carrier mode. Therefore, the scheduler for the uplink has
limited degrees of freedom: it has to allocate contiguous RBs
to each user without the possibility of choice among the best
available ones[9].
2) Control Overhead: The PDCCH, which carries DCI messages, is
time-multiplexed with the data-channel occupying a variable
number of OFDM symbols (up to 3). As a consequence, the amount
of resources dedicated to the PDCCH is limited, thus decreasing
the degrees of freedom for the downlink scheduler. PDCCH
overhead can be reduced using specific RRM procedures, either
by lowering a priori the number of users to be served (and
hence the number of DCI messages) or by utilizing low bit rate
DCI formats. The latter solution poses some constraints on the
construction of the RB allocation mask (for example allowing
the assignment of only contiguous RBs to the same UE.
27
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
3) Limitations on the Multi-User Diversity Gain: An important
limitation for LTE resource sharing algorithms is to derive
from the availability, at the eNB, of accurate channel quality
measurements. For the downlink, UEs are in charge of sending
CQIs to the serving eNB. For the uplink, instead, the eNB may
use reference signals transmitted by the UEs to estimate uplink
channel quality. The chosen CQI reporting scheme has great
impact on the multi-user diversity gain, as it defines the time
and frequency resolution of the channel quality information
available at the scheduler. This consideration can be easily
confirmed observing, as representative example that in the case
of wideband CQI reporting scheme (i.e., a single CQI value is
transmitted for the entire spectrum) the sensitivity to channel
conditions would become totally useless and the multi-user
diversity gain would go to zero. Thus, it appears clear how, in
such situations, the adoption of sophisticated techniques would
not bring to any gain. Furthermore, efficiency is limited
because multi-user diversity gain results to be upper bounded;
that is, increasing indefinitely the number of users competing
for allocation does not bring to any gain over a certain
threshold [14]. Moreover, it actually exists an optimal number
of candidate users depending on the system bandwidth.
4) Energy consumption: Energy saving is a required feature for
mobile terminals, and in LTE it is achieved through
Discontinuous Reception (DRX) methods. The basic idea of DRX is
to allow an UE to save energy turning off its radio equipment
when there are no data transmissions [21], as in typical
alternation of on/off periods (DRX cycles). In LTE, moreover,
28
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
DRX can be enabled in presence of active flows as well,
allowing off periods between packet burst transmissions. Such
operations require the knowledge of the activation of DRX
cycles. In principle, if the network could predict when a
certain user needs to transmit/receive data, an UE would only
need to be awake at such specific time instants. On the other
hand, in absence of a precise coupling between scheduling and
DRX procedures, it may occur that resources are allocated to an
UE during its off periods with consequent loss of data and
waste of bandwidth.
C. Persistent and semi-persistent scheduling
In LTE, the dynamic frequency domain strategies have the main
benefit of exploiting multiuser diversity gain, but this comes
at the cost of increased control overhead, due to the need of
forwarding DCI messages to scheduled users every TTI. For this
reason, especially in scenarios with high traffic load, the
limited amount of radio resources dedicated to control
information transmission can become a bottleneck, with
consequent degradation of QoS provisioning capabilities [23].
To face this problem, persistent solutions have been
investigated [24]. In these approaches, the control overhead is
used to preallocate to the same UE certain RBs over a time
sequence, distinguishing between active and inactive periods.
Under this scheme, once the eNB has informed a user on the
persistent allocation, the interested UE will know in advance
the specific TTI/RB couples where it should decode PDSCH
payloads (or, for the uplink direction, it should transmit
PUSCH payloads) with no need of any additional PDCCH overhead.
29
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
In Figure 7, a graphical example of a persistent resource
allocation is given. Here for instance, user 1 has resources
allocated every three TTIs and user 2 every five TTIs, always
on the same sub-carriers. Besides the impossibility to exploit
channel sensitivity, a major drawback of persistent approach is
that it does not appear suitable for supporting HARQ. In
practice, a single packet needs on average more than a single
transmission to be correctly decoded at the receiver, and the
number of retransmissions varies for each user, depending on
many factors such as the channel quality, the user mobility,
and the perceived inter-cell interference[30]. For these
reasons, semi-persistent algorithms are being deeply
investigated as a trade-off among static persistent approaches
and fully dynamic ones, especially if conceived for VoIP
traffic impossibility to exploit channel sensitivity.
Figure 7: Example of persistent scheduling allocation [2].
7. Cell selection: Cell selection by a mobile UE is anotherissue in LTE. In particularly, an interesting challenge in the
physical layer of LTE is how the mobile unit immediately after
powering on, locates a radio cell and locks on to it. More
30
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
specifically, it is very challenging to know how the mobile
unit establishes this connection with the strongest cell
station in vicinity. To do this, the mobile unit has to
overcome the challenges of estimating the channel to
communicate with the cell site and frequency
synchronization[1]. Also, multiple mobile units communicate to
the same receiver and from various distances. Thus, it is up to
the mobile to synchronize itself appropriately to the base
stations. LTE uses two signals, the Primary Synchronization
Signal and the Secondary Synchronization Signal sequentially to
determine which of the available cell sites a mobile would lock
in to. In addition if the inter cell interference is present
and if its level is high, then it will be very difficult for
the mobile UE to make a selection of the cell. The major cause
for inter cell interference is adjacent channel interference
(ACI) [5]. Adjacent-channel interference (ACI) is caused by
imprecise synchronization of multiple users accessing the same
Orthogonal Frequency Division Multiplexing (OFDM) channel.
Small frequency offsets between multiple users breaks the
orthogonality of their spectra due to the small spectral shifts
of the user’s sin(x)/(x) spectra relative to their design
locations at the zeros of the other user’s sin(x)/x. The system
multiple access procedure is designed to minimize these offsets
but there will be a small residual offset that can only be
reduced by interference cancellation techniques. Among all the
challenges mentioned above, the author of this synopsis is very
much interested in the area of cell selection. There are
different types of cells depending upon their area of usage and
31
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
coverage. The key cell types are Microcell, Macrocell,
Femtocell Picocell and Satellite (also known world wide
coverage). An overview of different types of cells is
presented in Figure 8.
Figure 8: Different types of cells in a network [7].
8. Key literature survey1. Aimin et.al. [26] in 2006 investigated a wireless system of
multiple cells, each having a downlink shared channel in
support of high-speed packet data services. Authors mentioned
that in practice, such a system consists of hierarchically
organized entities including a central server, Base Stations
(BSs), and Mobile Stations (MSs). Authors in this study tried
to improve global resource utilization and reduce regional
congestion given asymmetric arrivals and departures of mobile
users, a goal requiring load balancing among multiple cells.
For this purpose, authors proposed a scalable cross-layer
framework to coordinate packet-level scheduling, call-level
cell-site selection and handoff, and system-level cell
32
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
coverage based on load, throughput, and channel measurements.
In this framework, an opportunistic scheduling algorithm—the
weighted Alpha-Rule—exploited the gain of multiuser diversity
in each cell independently, trading aggregate (mean) downlink
throughput for fairness and minimum rate guarantees among
MSs. Authors specific contributions in such a framework are
highlighted by the minimum-rate guaranteed weighted Alpha-
Rule scheduling, the load-aware MS handoff/cell-site
selection, and the Media Access Control (MAC)-layer cell
breathing. Author’s evaluations showed that their framework
can improve global resource utilization and load balancing,
resulting in a smaller blocking rate of MS arrivals without
extra resources while the aggregate throughput remains
roughly the same or improved at the hot-spots.
2. Supratim et al. [27] in 2013 mentioned that the success of
LTE Heterogeneous Networks (Het-Nets) with macro cells and
pico-cells critically depends on efficient spectrum sharing
between high-power macros and low power picos. Authors
mentioned that the two important challenges in this context
are: (i) determining the amount of radio resources that macro
cells should offer to pico-cells, and (ii) determining the
association rules that decide which UEs should associate with
picos. In this research, authors developed an algorithm to
solve these two coupled problems in a joint manner. Author’s
algorithm accounted for network topology, traffic load, and
macro-pico interference map. Authors also presented results
for evaluations using RF plan from a real network and discuss
SON based eICIC implementation.
33
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
3. Sanil F. [28] in 2011 mentioned that LTE is designed with a
goal of evolving the radio access technology under the
assumption that all services would be packet-switched, rather
than following the circuit-switched model of earlier systems.
This research mainly emphasizes on Physical layer and a proof
for the physical layer message sequence. The main purpose of
this research is to study, analyze and implement a proof of
Physical layer process in control plane of LTE system. The
focus is on physical layer between the UE and eNB. Authors
performed the test trials and screenshots for the analysis of
call drops were taken and included. Author’s results showed
the achievable Downlink and Uplink throughput in multi user
and single user environment compared with the channel
capacity of 10MHz channel. The research is mainly based on
3GPP LTE specifications and discussions.
4. Berardinelli Gilberto [29] in 2010 deals with the air
interface design for the uplink of 4th generation systems
based on SC-FDM technology. The interaction of MIMO with
SC-FDM is investigated in terms of link performance as well
as its effects on the transmit waveforms. Author included the
enhancement mechanisms such as fast link adaptation and
Hybrid Automatic Repeat Request (HARQ). Author presented a
transmit diversity space frequency coding (SFC) algorithm;
where the encoding is performed over adjacent subcarriers is
shown to compromise the single carrier nature of the uplink
signals. Space Time Coding (STC) has therefore to be
preferred for a SC-FDM radio interface, despite of a lower
flexibility. An SFC scheme which does not increase the PAPR
34
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
of the transmit waveform is also derived. Authors performance
results obtained with Monte Carlo simulations show its
effectiveness for small transport data blocks. The
investigations carried out in this rersearch confirm SC-FDM
as a valid air interface for the uplink of LTE-A; with a
careful design of the transceiver chain, it can achieve
indeed the same link performance of OFDM, while keeping the
remarkable advantage of a higher power amplifier efficiency.
5. Jaewon et. al. [30] in 2013 presented an operational strategy
to mitigate co-channel interference (CCI) by using
geographically distributed remote radio heads (RRHs). Author
mentioned that the inter-node CCI becomes a dominant
performance degradation factor for heterogeneous network
(HetNet) systems. According to authors, there are emerging
attempts in Third Generation Partnership Project to adopt
advanced techniques to Long Term Evolution Advanced systems
to mitigate CCI problems for HetNet systems, namely, the
coordinated multipoint transmission (CoMP). However, the CoMP
scheme cannot control the CCI generated from outside
coordination boundaries. To resolve this problem, authors
proposed a partial activation strategy by using RRHs deployed
near cell edge which results in moving coverage boundary
effects. Based on Monte Carlo system level simulations,
performance of the conventional strategies and the presented
strategy is evaluated by authors. Their simulation results
showed that their scheme outperforms the enhanced inter-cell
interference coordination and CoMP schemes especially for
users located near cell edge areas.
35
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
6. Jakub et. al. [31] in 2009 mentioned that the objectives in
ongoing research related to mobile positioning are
inexpensive solutions providing high accuracy of position
estimation. Authors mentioned that Cell ID+RTT is identified
as one of the most available and applicable location
technique for UMTS. According to authors, this technique
provides high degree of accuracy, but only for users within
SHO. Therefore, authors in this study aimed to present an
algorithm for increasing SHO window for the time instant
needed for necessary RTT measurements. Author’s simulation
outcomes showed that application of their algorithm increases
the availability of accurate Cell ID+RTT estimates (16–20 m
in free propagation environment) for nearly all served users
in the network, simultaneously improving overall accuracy to
40 m for 90% of measurements.
7. Jung-Min et. al. [32] in 2010 mentioned that in a
hierarchical cellular network employing universal frequency
reuse, the level of both intra- and inter-cell interference
largely depends on the selection of a serving cell for the
users in the overlapping area of multiple cells. Therefore,
authors proposed a cell selection algorithm that is suitable
for hierarchical cellular networks. In their algorithm,
uplink transmit power is used as a key parameter and cells
are selected on the basis of the coordination of multiple
users, rather than the choice of a single user. Authors
simulation results showed that their algorithm improves
performance with respect to the number of supportable users
36
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
and the transmit power that each user needs in order to
achieve a given target SINR.
8. Dong et. al. [33] in 2012 mentioned that handover failure
probability is one of the important factors to determine the
handover performance in cellular radio system such as the 3rd
generation partnership project (3GPP) long term evolution. To
minimize the handover failure probability, the Hybird target
cell selection (TCS) scheme considering both the received
signal strength (RSS) and load information of neighboring
evolved Node Bs (eNBs) based on X2 interface in 3GPP LTE
system has been introduced in this research. Authors
mentioned that the amount of cell load in serving and
neighboring eNBs can be drastically changed over time due to
the handover operation, so the Hybrid TCS scheme should
consider the cell load change between the serving and
neighboring eNBs in the handover procedure for handover
preparation. In this research, authors proposed a modfied
Hybrid TCS scheme based on the least mean square (LMS)
algorithm for estimating the load status of the neighboring
eNBs in order to mitigate the handover failure probability.
Authors mentioned TCS scheme chooses the target eNB with
minimum load based on the LMS algorithm and providing higher
RSS. Their experiment results reveal the effectiveness of
their scheme and its advantages over the conventional schemes
in terms of handover failure probability.
9. Anna et. al. [34] in 2013 mentioned that wireless
communication network consist nowadays of multiple standards,
as well as cells of different sizes and coverage. According
37
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
to authors, providing the best connection in such environment
is a challenging task. Therefore, authors proposed an
approach of solving the cell selection problem in
heterogeneous networks. The method recursively applies
efficient algorithms for bipartite graph matching to provide
the final solution. This method does the cell selection in
multistandard heterogeneous networks. The idea is based on a
recursive use of algorithms dedicated to find matchings in
bipartite graphs. A platform for evaluation purposes has
already been implemented and evaluated.
10. Ömer et. al. [35] in 2010 mentioned that relaying is a
promising enhancement to current radio access networks. Relay
enhanced LTE-Advanced networks are expected to fulfill the
demanding coverage and capacity requirements in a cost-
efficient way. However, due to low transmit power, the
coverage areas of the relay nodes will be small. Therefore,
the performance of relay deployments may be limited by load
imbalances. In this study, authors presented a practical
solution for this problem by introducing a bias to cell
selection and handover decisions along with a reduction in
eNB transmit power. According to authors, this method
resulted in an extension of the relay cells and an
appropriate load balance can then be achieved. Moreover, it
is shown that a proper power control setting is necessary in
the uplink and that power control optimization can further
enhance the system performance. Author’s comprehensive system
level simulations confirm that their solution yields
38
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
significant user throughput gains both in the uplink and the
downlink.
11. Li Huang et. al. [36] in 2013 mentioned that femtocells
have emerged as a promising solution to provide wireless
broadband access coverage in cellular dead zones and indoor
environments. However, co-channel deployments of closed
subscriber group femtocells cause coverage holes in
macrocells due to co-channel interference. To address this
problem, cognitive radio technology has been integrated with
femtocells, in this research. CR-enabled femtocells can
actively sense their environment and exploit the network side
information obtained from sensing to adaptively mitigate
interference. Authors investigated three CR-enabled
interference mitigation techniques, including opportunistic
interference avoidance, interference cancellation, and
interference alignment. In this research, authors presented a
joint opportunistic interference avoidance scheme with Gale-
Shapley spectrum sharing (GSOIA) based on the interweave
paradigm to mitigate both tier interferences in macro/femto
heterogeneous networks. In this scheme, cognitive femtocells
opportunistically communicate over available spectrum with
minimal interference to macrocells; different femtocells are
assigned orthogonal spectrum resources with a one-to-one
matching policy to avoid intratier interference. Author’s
simulations show considerable performance improvement of the
GSOIA scheme and validate the potential benefits of CR-
enabled femtocells for in-home coverage.
39
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
12. Kemal et. al. [37] in 2013 mentioned that heterogeneous
cellular networks provide significant improvements in terms
of increased data rates and cell coverage, and offer reduced
user rate starvation. In this study, authors identified that
the cell selection criterion is an important factor
determining the user rates especially in the uplink
transmissions and apply cell breathing to determine the user
and base station assignments. Authors observed that their
interference-based cell selection algorithm provide better
load balancing among the base stations in the system to
improve the uplink user rates. Authors presented the
implementation steps in a typical LTE network and
demonstrated the performance improvements through
simulations.
13. Steven et. al. [38] in 2012 discussed the problem of
associating users, in an heterogeneous network, to either a
macro node or a pico node within a tightly coordinated cell
cluster. Authors introduced a new theoretical framework to
model this problem for the downlink and derived upper bounds
for achievable sum rate and minimum rate using convex
optimization. Authors proposed a heuristics based approach,
consisting in dynamic cell association, enabling to achieve
performance close to the upper bounds. Authors implemented
these heuristics in an LTE simulator and showed the potential
of such dynamic cell association for a small LTE network.
14. Kyuho et. al. [39] in 2009 mentioned that next-generation
cellular networks will provide higher cell capacity by
adopting advanced physical layer techniques and broader
40
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
bandwidth. Authors also mentioned that even in such networks,
boundary users would suffer from low throughput due to severe
inter-cell interference and unbalanced user distributions
among cells, unless additional schemes to mitigate this
problem are employed. Therefore, authors presented a solution
to this problem by jointly optimizing partial frequency reuse
and load-balancing schemes in a multi-cell network. Authors
formulated this problem as a network-wide utility
maximization problem and proposed optimal offline and
practical online algorithms to solve this. Author’s online
algorithm turns out to be a simple mixture of inter- and
intra-cell handover mechanisms for existing users and user
association control and cell-site selection mechanisms for
newly arriving users. According to authors, a remarkable
feature of their algorithm is that it uses a notion of
expected throughput as the decision making metric, as opposed
to signal strength in conventional systems.
15. Huthaifa Al-Jaradat et. al. [40] in 2013 studies the
technical challenges associated with some of the RRM tasks
(including Packet scheduling, interference management and
handover control), in addition it presents from the open
literature some of the proposed solutions to these technical
challenges. According to authors, Packet scheduling faces
the challenge of supporting diverse QoS requirements of
different traffic types, while maintaining the overall system
throughput and fairness among users at an acceptable level.
Another challenge is the difficulty of scheduling due to the
adoption of CA and CoMP scheme. Authors mentioned that
41
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
interference in LTE-A raises due to the adoption of HetNet.
eICIC is the adopted method to relieve its effect which can
be grouped under three main techniques: time domain
technique, frequency domain technique and power control
technique. HHO is the only handover supported in the LTE and
LTE-A. HHO is fairly simple and less-complex compared to the
SHO, but HHO has several disadvantages such as high outage
probability, disruption time and carrier interference.
16. Wenan et. al. [41] in 2011 mentioned a modified scheduling
scheme of Round Robin (RR) algorithm. In this scheme, each
cell users are divided into two groups: cell-edge UEs and
cell-center UEs. Also, the available frequency bands are
divided into two groups: CoMP frequency and non-CoMP
frequency. The cell-edge UEs are equally scheduled by their
local eNB on PRBs of CoMP frequency zone. The local eNB
requests cooperation from neighboring eNBs on the relative
PRB. However, other eNBs may request cooperation on the same
PRB, which is scheduling conflict. In such case, eNBs
receiving the cooperation requests follow the rule “first
come first served”, that is the eNBs respond to the first
cooperation request and ignore other requests. Cell-center
UEs are equally scheduled in a circular order and are
allocated PRBs of single cell frequency band. And if some of
cell-edge UEs are not scheduled in the cooperation mode, they
will be scheduled as cell-center UEs at the end. Finally, the
remaining resources are allocated to cell-center UEs, as they
cannot be used for CoMP.
42
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
17. Jong et. al. [42] in 2013 proposed an intelligent cell
selection scheme for inter-system handovers in heterogeneous
networks that satisfies user requirements as well as system
requirements. Their scheme uses uncertain parameters such as
user system preference, communication cost, mobile speed,
transmission delay, packet loss, and cell loads in the
decision process utilizing the aggregation functions in fuzzy
set theory. Contrary to many existing schemes which consider
only either system parameters or user requirements, their
scheme considers both. This scheme hierarchically analyzes
the relative value of cell selection parameters based on the
current state of heterogeneous networks, the speed of mobile
terminals, and the change in QoS. Then, it focuses on the
adaptation of relative importance values for each cell
selection parameter. Computer simulation results performed by
authors showed that their scheme provides systems and users
with much better performance compared to existing schemes.
18. Anna et. al. [43] in 2013 proposed a novel optimization
model for resource assignment in heterogeneous wireless
network. The model adopts two objective functions maximizing
the number of served users and the minimum granted utility at
once. A distinctive feature of author’s model is to consider
two consecutive time slots, in order to include handover as
an additional decision dimension. Furthermore, the solution
algorithm that author’s proposed refines a heuristic solution
approach recently proposed in literature, by considering a
real joint optimization of the considered resources. Author’s
simulation study shows that the new model leads to a
43
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
significant reduction in handover frequency, when compared to
a traditional scheme based on maximum SNR.
19. Chung-Ju et. al. [44] in 2013 mentioned a preference
value-based cell selection (PVCS) scheme to satisfy quality
of service (QoS) requirements, maximize accommodated number
of calls, and minimize handoff occurrence frequency in
heterogeneous wireless networks. The PVCS scheme contains
three stages including candidate cells selection, preference
value calculation, and target cell determination. The
candidate cells selection is used to sift the suitable cells
for the call request. All suitable cells form a candidate
cell set. The preference value calculation computes the
preference value of each cell in the candidate cell set,
which is optimized by considering QoS factor, loading factor,
and mobility factor, for the purpose of maintaining QoS
requirements of a call request, maximize accommodated number
of calls, and minimizing handoff occurrence frequency.
Eventually, the candidate cell, which has the maximum
preference value, would be selected for the call request.
Simulation results performed by authors showed that PVCS
scheme achieve higher total throughput than UGT while
satisfying the QoS requirements
20. Lin Gao et. al. [45] in 2011 mentioned that cell selection
and resource allocation (CS-RA) are processes of determining
cell and radio resource which provide service to mobile
station (MS). Optimizing these processes is an important step
towards maximizing the utilization of current and future
networks. In this research, authors investigated the problem
44
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
of CS-RA in heterogeneous wireless networks. Specifically,
author’s proposed a distributed cell selection and resource
allocation mechanism, in which the CS-RA processes are
performed by MSs independently. Author’s formulated the
problem as a two-tier game named as inter-cell game and
intra-cell game, respectively. In the first tier, i.e. the
inter-cell game, MSs selected the best cell according to an
optimal cell selection strategy derived from the expected
payoff. In the second tier, i.e., the intra-cell game, MSs
choose the proper radio resource in the serving cell to
achieve maximum payoff. Furthermore, author’s proposed
distributed algorithms named as CS-Algorithm and RA-Algorithm
to enable the independent MSs converge to Nash equilibria.
Author’s simulation results showed that their algorithms
converge effectively to Nash equilibria and that their CS-RA
mechanism achieves better performance in terms of throughput
and payoff compared to conventional mechanisms.
9. MotivationCell selection by a mobile UE is a key issue in LTE. In
particularly, an interesting challenge in the physical layer
of LTE is how the mobile unit immediately after powering on,
locates a radio cell and locks on to it. More specifically,
it is very challenging to know how the mobile unit
establishes this connection with the strongest cell station
in vicinity. To do this, the mobile unit has to overcome the
challenges of estimating the channel to communicate with the
cell site and frequency synchronization. Also, multiple
45
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
mobile units communicate to the same receiver and from
various distances. Thus, it is up to the mobile to
synchronize itself appropriately to the base stations. LTE
uses two signals, the Primary Synchronization Signal and the
Secondary Synchronization Signal sequentially to determine
which of the available cell sites a mobile would lock in to.
In addition if the inter cell interference is present and if
its level is high, then it will be very difficult for the
mobile UE to make a selection of the cell. The major cause
for inter cell interference is adjacent channel interference
(ACI). Adjacent-channel interference is caused by imprecise
synchronization of multiple users accessing the same
Orthogonal Frequency Division Multiplexing (OFDM) channel.
Small frequency offsets between multiple users breaks the
orthogonality of their spectra due to the small spectral
shifts of the user’s sin(x)/(x) spectra relative to their
design locations at the zeros of the other user’s sin(x)/x.
This practical problem of LTE seems very interesting; which
motivated the author to perform research in this domain.
10. Formulation of problemFrom the literature review, the ability to provide services
in a cost-effective manner is one of the most important
building blocks of competitive modern cellular systems.
Usually, an operator would like to have a maximal utilization
of the installed equipment, that is, to maximize the number
of satisfied customers at any given point in time. The
research through this synopsis will address one of the
46
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
problems in this domain, the cell selection mechanism. This
mechanism determines the base station (or base stations) that
provide the service to a mobile station. More specifically,
the research through this synopsis will focus on joining of
the mobile station to the network (called cell selection),
and/or when a mobile station is on the move in idle mode
(called cell reselection, or cell change). This will also
include the effect of suppression of interference due to
other mobile stations. It is because in uplink multi-user
scenario, the interference is not only introduced by
incorrect symbol timing estimation and frequency offsets, but
also by the relative delays between users. Therefore, the
author is motivated to perform research in this domain.
11. Objectives1. To do the review of mobile cell selection in LTE-A
networks and its associated problems and challenges.
2. To implement LTE physical layer using OFDMA and SCFDMA in
Matlab.
3. To develop a hierarchical cell identity based strategy to
do mobile cell selection in single and multiple user
scenarios and also in cell interference region.
4. To develop a method based on fractional loading to improve
the cell selection performance (i.e. reduction of inter-cell
interference) in overlapping regions of irregular shaped
cells of LTE. To evaluate its performance compared to
traditional frequency reuse method.
12. Research methodology
47
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
Conventionally, cell selection is based on the downlink
received signal strength which means mobile users will
connect to the site from which the received power is
strongest. For example, in 3GPP LTE, cell selection is
performed according to two parameters measured by a User
Equipment (UE): Reference Signal Received Power (RSRP) and
Reference Signal Received Quality (RSRQ). Reference signal
received power (RSRP), is defined as the linear average over
the power contributions of the resource elements that carry
cell-specific reference signals within the considered
measurement frequency bandwidth. RSRQ is calculated based on
RSRP which provides additional information and ensures a
reliable cell selection decision when RSRP is not sufficient.
In homogeneous networks, RSRP based cell selection guarantees
good channel conditions in both downlink and uplink. However,
it is very difficult when a mobile UE powers on and/or when
the UE moves from one cell to another or when it is in the
overlapping region of two or more cells. To better understand
consider Figure 9, which shows one possible scenario in a
real network. Assume that the UE belongs to network operator
1 (green). There are two other carriers also operating an LTE
network but of course at different frequencies. The terminal
receives all base stations but at different power levels.
Based on the above definition the UE will select the strong
cell for each carrier . Using this the UE will start with
network operator 3 and figure out after decoding the SIB Type
1 that the PLMN saved on the USIM does not match to the
transmitted one. From this information it will stop with its
48
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
attempt and proceed to the next strongest signal, which is
operator 2 (red). Now the PLMN does not correspond so the UE
will continue with signal 3 (green) – and the PLMN will
match. This way the mobile UE will do the cell selection. The
research methodology to be used is mentioned below.
Figure 9: An example of a possible scenario in a real
network[16].
There are many types of cells :
1. Microcells : is a cell in a mobile phone network served by a
low power cellular base station (tower), covering a limited
area such as a mall, a hotel, or a transportation hub, The
range of it is few hundreds of meters. It is used in urban
areas[32].
2. Macrocells : is a cell in a mobile phone network that
provides radio coverage served by a high power cellular base
station (tower). The macrocells provide coverage larger
than microcell The antennae for macrocells are mounted on
49
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
ground-based masts, rooftops and other existing structures,
at a height that provides a clear view over the surrounding
buildings and terrain. It is used in the early phase of
cellular telephony[32].
3. Femtocells: is a small, low-power cellular base station ,
typically designed for use in a home or small business.
4. Picocells: is a small cellular base station typically
covering a small area, such as in-building (offices, shopping
malls, train stations, stock exchanges, etc.), or more
recently in-aircraft[32].
Table 4: Research methodology.
Step
1
Implement LTE Physical Layer using SC-FDMA and OFDMA in
MatlabStep
2
Develop and Implement an algorithm for Mobile UE LTE Cell
Joining Using Hierarchical cell Identity Step
3
Identify the challenges of Inter-Cell Interfaces of
Overlapping Cells regions and presence of multiple mobile
UE.Step
4
Develop an algorithm using the fractional loading concept
to improve the cell selection performance (i.e. reduction
of inter-cell interference) in overlapping regions of
irregular shaped cells of LTE.Step
5
Evaluate the performance of above algorithm compared to
traditional frequency reuse method.
13. Time schedule
50
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
The following is the schedule to be followed for the M.Tech
dissertation
Table
5: Time schedule
Synopsis Jan, 2014
Literature Review & Paper I March, 2014
Coding April, 2014
Paper II April, 2014
Dissertation May, 2014
14. References1) D. Amzallag, R. Yehuda, D. Raz and G. Scalosub, “Cell selection
in 4G cellular networks”, IEEE Transactions on mobile
computing, vol. 12, no. 7, pp.1443-1455, July 2013.
2) F. Capozzi, G. Piro, L. Griec, G. Boggia, and P. Camarda
“Downlink packet scheduling in LTE cellular networks: key
design issues and a survey” IEEE Communications Survey &
Tutorials, vol. 15, no. 2, pp.678-697, 2013.
3) R. Nag. Kummithe, “Interference mitigation in 4G LTE-A
heterogeneous networks”, Advances in Electrical Engineering
Systems, IEEE wireless communications and networking, vo. 13,
no. 5, Dec. 2012.
4) 3gpp, 3rd generation partnership project, “Technical
specification group radio access network”, Physical channels
and modulation (release 8), 3gpp ts 36.211.
5) S. Carlaw, A. Giustina, R. Bhat and S. Rao, “Femtocells -
opportunities and challenges for Business and Technology”,
51
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
John Wiley & Sons Ltd. ISBN: 978-0-470-74816-9, pp.170-175,
2009.
6) A. Roessler, S. Rohde and T. Schwarz, “Cell search and cell
selection in UMTS LTE”, IEEE wireless communications and
networking, Sep.2009.
7) 3gpp, “Itu library and archive services”, url
http://www.itu.int/en/history/overview/pages/history.aspx
cited on 19th Jan. 2014.
8) 3gpp, “Evolved universal terrestrial radio access (E-UTRA);
physical layer; measurements (Release 10)”, TS 36.214
v10.1.0, March 2011.
9) N. Arshad, M.A. Jamal, Dur E. Tabish and S. Saleen, “Effect
of wireless channel parameters on performance of turbo
codes”, IEEE communications letters, vol. 1, no. 3, pp.
129-134, 2012.
10) S. Landstrom, H. Murai and A. Simonsson, “Deployment
aspects of LTE pico nodes”, Institute communications
workshops (ICC) 2011, IEEE international conference, vol.3,
no.5, pp.1-5, June 2011.
11) A. Furuskär, K. Johansson, L. Falconetti and F.
Kronestedt, “Heterogeneous networks (Hetnets) an approach to
increasing cellular capacity and coverage”, IEEE
communications Magazine vol.6, no 1, pp.223-227, Feb. 2011.
12) J. Lee, J. K. Han and J. Zhang, “MIMO technologies in 3gpp
LTE and LTE-advanced”, International journal of wireless
communication and networking, vol.10, no 3, pp.144-166, 2009.
52
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
13) 3gpp, 3rd generation partnership project, “Technical
specification group radio access network”, Physical channel
and modulation (release 8), 3gpp ts 36.201.
14) R. Kwan, C. Leung, and J. Zhang, “Multiuser scheduling on
the downlink of an LTE cellular system”, IEEE communications
vol.14, no. 4, pp. 31–34, Jan. 2008.
15) H. Yang, F. Ren, C. Lin, and J. Zhang, “Frequency-domain
packet scheduling for 3gpp LTE uplink,” in proc. of IEEE
Information communications, vol.11, no.1, pp. 1 –9 March,
2010.
16) L. Ruiz De Temino, G. Berardinelli, S. Frattasi and P.
Mogensen, “Channel-Aware scheduling algorithms for SC-FDMA in
LTE uplink”, in proc. of IEEE personal, indoor and mobile
radio communications, France, pp. 1 –6, Sep. 2008,
17) F. Capozzi, D. Laselva, F. Frederiksen, J. Wigard, I.
Kovacs and P. Mogensen, “UTRAN LTE downlink system
performance under realistic control channel constraints”, in
proc. Of IEEE Veh. Tech. Conf., Alaska, USA, pp. 1 –10, Sep.
2009.
18) 3gpp, tech. Specif. Group radio access network -
multiplexing and channel coding, 3gpp ts 36.212.
19) K. Pedersen, G. Monghal, I. Kovacs, T. Kolding, A.
Pokhariyal, F. Frederiksen, and P. Mogensen,
“Frequency domain Scheduling for OFDMA with limited and noisy
channel feedback,” in proc. of IEEE veh. Tech. Conf.,
Baltimore, USA, pp. 1792 –1796, 2007.
53
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
20) 3gpp, Tech. Specific Group radio access network – max.-
ues/subframe for optimum E-UTRA performance (5-
20Mhz), 3GPP TSG-RAN WG1 R1-070792.
21) C. Bontu and E. Illidge, “DRX mechanism for power saving
in LTE,” IEEE Communications Magazine, vol. 47, no. 6, pp. 48
–55, Jun. 2009.
22) L. Zhou, H. Xu, H. Tian, Y. Gao, L. Du, and L. Chen,
“Performance analysis of power saving mechanism with
adjustable DRX cycles in 3gpp LTE”, in proceedings of IEEE
veh. Tech. Conf., Alberta, pp. 1 –5, sep. 2008
23) D. Laselva, F. Capozzi, F. Frederiksen, K. Pedersen, J.
Wigard, and I. Kovacs, “On the impact of realistic control
channel Constraints on Qos provisioning in UTRAN LTE” , in
proc. of IEEE veh. Tech. Conf., vtc-fall, Alaska, USA, pp. 1
–5, Sep. 2009.
24) 3gpp, Tech. Specific Group radio access network -
persistent scheduling in E-UTRA, 3gpp tsg-ran wg1 r1-070098.
25) D. Jiang, H. Wang, E. Malkamaki, And E. Tuomaala,
“Principle and performance of semi-persistent scheduling for
VoIP in LTE system”, in proc. of IEEE wireless
communications, networks and mobile computer, China, pp. 1 –
44, sep. 2007.
26) A. Sang, M. Madihian and R. Gitlin, “Coordinated load
balancing, handoff/cell-site selection, and scheduling in
multi-cell packet data systems”, IEEE communications letters,
vol. 22, no. 6, June 2006.
27) D. Supratim, P. Monogioudis, J. Miernik And P. Seymour
“Algorithms for enhanced inter cell interference coordination
54
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
in LTE Hetnets”, IEEE wireless communications and networks,
vol. 16, no. 3, pp.1-14, Jan 2013.
28) S. Fulani and Q. Liang, “Physical layer test trials and
analysis of call drops and real time throughput versus
channel capacity of the long term evolution (4G) technology”,
International Journal of Electronics Engineering, vol. 9, no.
3, pp.120-130, 2011.
29) G. Berardinelli, “Air interface for next generation mobile
communication networks: physical layer design: a LTE-A
uplink”, Department of Electronic Systems, pp.56-60, (2010).
30) J. Kim, D. Lee and W. Sung, “Interference coordination of
heterogeneous LTE systems using remote radio heads“, ASP
Eurasip journal on advances in signal processing 2013, url
http://asp.eurasipjournals.com/content/2013/1/90, pp.1-8,
2013.
31) J. Borkowski, J. Niemelä, And J. Lempiäinen, “Enhanced
performance of cell idrtt by implementing forced soft
handover algorithm”, IEEE wireless communications and
networks, institute of communications engineering, vol. 7,
no. 3, pp.543-550, 2004.
32) J. Moon and D. Ho Cho, “Efficient cell selection algorithm
in hierarchical cellular networks: multi-user coordination”,
IEEE communications letters, vol. 14, no. 2, pp.157-159, Feb.
2010.
33) D. Hoi Kim and J. Berger, “Target cell selection scheme
using LMS algorithm for load estimation of neighboring EnBs
in 3GPP LTE system”, International journal of innovative
55
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
computing, information and control, vol. 9, no. 2, pp.793-
803, Feb. 2013.
34) A. Zakrzewska, Sarah Ruepp and S. Michael, “Cell selection
using recursive bipartite matching”, IEEE International
Conference on Computer Communications (INFOCOM 2013),
Department of photonics engineering, vol. 13, no. 6, pp.656-
666, 2013.
35) Ö. Bulakci, A. Bou Saleh, S. Redana, B. Raaf and J.
Hämäläinen, “Enhancing LTE-Advanced relay deployments via
relay cell extension”, 15th international OFDM-workshop,
Hamburg, Germany, Sep. 2010.
36) L. Huang and G. Zhu, “Cognitive femtocell networks: an
opportunistic spectrum access for future indoor wireless
coverage”, IEEE wireless communications, vol. 10, no. 8,
pp.44-51, Apr. 2013.
37) K. Davaslioglu and E. Ayanoglu, “Interference-based cell
selection in heterogenous networks”, Department of Electrical
Engineering and Computer Science, IEEE wireless
communications, vol. 11, no. 4, pp.13-25, Feb. 2013.
38) S. Corroy, L. Falconetti and R. Mathar, “Cell association
in small heterogeneous networks: downlink sum rate and min
rate maximization”, Institute for theoretical information
technology, IEEE wireless communications and networking
conference, vol. 12, no. 9, pp.898-902, Dec. 2012.
39) K. Son, S. Chong and G. Veciana, “Dynamic association for
load balancing and Interference avoidance in multi-cell
networks”, IEEE Transactions on wireless communications, vol.
8, no. 7, pp. 3566- 3576, July 2009.
56
SYNOPSIS: MOBILE CELL SELECTION IN 4G LTE-A NETWORKS
40) H. Al-Jaradat and K. Sandrasegaran, “Survey on the
research challenges of radio resource management in LTE-A and
the current proposed solutions for these challenges”,
International journal of computers & technology, vol 7, no.
3, pp.626-637, June 2013.
41) W. Zhou, W. Chen, Z. Tan, S. Chen and Y. Zhang, “A
modified RR scheduling scheme based comp in LTE-A system”, in
communication technology and application, IET international
conference,vol.7, no.6, pp. 176-180, 2011.
42) C. Lee And S. Moo Yoo, “Intelligent cell selection
satisfying user requirements for inter-system handover in
heterogeneous networks”, the International Journal for
Computer and Telecommunications Computer Communications,
vol.9, no.15, pp.2106-2114, July 2012.
43) S. Ruepp, M. Berger, F. D’andreagiovanni and Anna
Zakrzewska, “Biobjective optimization of radio access
technology selection and resource allocation in
heterogeneous wireless networks”, International symposium on
modeling & optimization in mobile, ad-hoc & wireless
networks, Rawnet, pp.652-658, October 2013.
44) C. Chang, C. Yuan Hsieh and Y. Han Chen, “A preference
value-based cell selection scheme in heterogeneous wireless
network”, IEEE communications society, vol.2, no.12, pp.2106-
2114, 2010.
45) L. Gao, X. Wang, G. Sun and Y. Xu, “A game approach for
cell selection and resource allocation in heterogeneous
wireless networks”, Sensor mesh and ad hoc communications and