International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 4- March 2016
Neighborhood Cell Scanning in Network with
Small Cells for Handover Purpose
#1
Senthil Kumar.J, #2Archana.M,
AP, Department of Computer Science and Engineering#1,
PG Student, Department of Computer Science and Engineering#2
School of Engineering, Vels University, Chennai, India.
Abstract:
II.RELATED WORK
Deployment of small cells can improve the
throughput and users quality of service. Moving
users must be able to discover cells in their
neighbourhood. For this purpose, the users
perform neighbourhood scanning. Proposing these
algorithm will reduce the energy consumption and
increase the Efficiency for future mobiles in
network.
Keywords
Neighbourhood Scanning ,
Handover , Nodes , Mobile Network .
Most recently for scanning it will take scenarios
of MENBs. if the user equipment is connected to
SCeNBs, the problem discovering of all potential
candidates for handover. this problem is
addressed].Both papers deal with a solution for
minimization called hidden node problem.
If two cells are in neighbors but they are fail to
receive signal of each because of an interrupted
path . if the hidden cells are not discovered, they
cannot be included in User Equipment.
I. INTRODUCTION
Deployment of small cells increases overall
throughput of network and it enables to offload
macro cells. A high number of SCeNBs in network
implies several problems. one of the major problem
related to mobility management.
if a user is moving must perform handover from a
current serving cell to target cell. To decide about
proper time of handover, Reference signal received
power between user and serving of neighboring
cells is measured. This process known as
neighborhood scanning.
Scanning of neighboring cells in LTE-A and
WCDMA networks automatic neighbor relation
and detected set reporting are defined respectively.
By using this mechanisms, User need not to know
its neighboring cells before scanning takes place.
A. Distance Based Scanning
The proposed algorithm exploits knowledge of
existing visited cell and obstructed paths principle
between two cells to reduce number of scanning
events. To follow this proposal we first define
notation and system model. Then, the principle of
obstructed paths combined with knowledge of
previous visited cell is described.
B. Obstructed Path
The number of scanned cells can be reduced by
using obstructed path and previous visited cell.
obstructed path means that if the cell with small
coverage radius is deployed with radius of large
cell. Each user can pass from one side of the MeNb
to another without handover.
It automatically scan only surrounding cells,
which share same frequency band. The major
drawback of these mechanisms with respect to
future mobile networks considering multiple radio
access technology consists in scanning only cells in
same band as the serving cell.
If the user scans an excessive number of
neighboring cells, time for finding the most
appropriate candidate for handovers increased. it
results in wasting battery power of User.
Deployment of small cells is key assumed enabler
of 5g heterogeneous mobile networks.
Fig.1 .Network Deployment
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 4- March 2016
Benefits of the principle of obstructed path and
previous visited cell can be demonstrated by the
figure.
Here the MUE has to scan 10 neighboring cells
belonging to B2 during the movement of the MUE
within area of MeNB2.if the proposed approach is
considered the MUE scans only 4 neighboring
cells. for the expression of the DNC relations
among all the cells within the MeNb coverage, we
adopt the graph theory. for each network the graph
is defined. the set of vertices of the grap represent
all cells from which the handover to the MeNb is
possible.
Fig.3 Proposal of Self-Configuration
After each handover to the MeNb ,the timer is
launched and previously visited cell is stored.
During the MUE connection to the MeNb in self
configuration phase.
Fig. 2 Distance neighbour cell relation
The proposed algorithm is designed for creation
of NCL of MUE. the SCeNBs are of limited range
and the obstructed paths are not so frequent under
coverage. Thus the NCL composed according to
our proposal is usually identical with the set Bm.
After performing a sufficient number of
handovers, the distance between distant neighbours
and the self-configuration phase is completed.
Remaining infinite values of some elements
indicate that the cell is not the distant neighbour of
cell. it means that path between these two cells is
obstructed.
A. Simulation model
The drawback of the principle of obstructed paths
is that during whole movement of User Equipment
,The MUE have to scan all cells included. we
further propose to exploit an estimation of the
distances between the cells. This allows by
reducing number of cells which cannot be accesed.
III. SELF CONFIGURATION FOR
DISTANCE BASED SCANNING
The first step after the new MeNb is deployed is
self configuration phase. At the beginning of this
phase, the dm is empty and DNCs of the MeNb are
not known.
Fig.4 Environment for Simulation
Simulation area with twelve block of buildings
with different number of floors is shown. among
those blocks, apartments, offices, restaurants, and
working places are distributed. in simulation area,
four fixed MeNBs providing LTE-A, coverage are
placed according are dropped at random place and
random floors in each block.
The position of the fem to cell is randomly
generated in every simulation drop. in total, ten
drops with a length of 500 000 steps are run. for
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International Journal of Engineering Trends and Technology (IJETT) – Volume 33 Number 4- March 2016
algorithm, the speed can influence the performance
Significant.
IV. PERORMANCE METRICES
in this ,the performance of our algorithm is
compared with competitive algorithm.
A. Competitive algorithm
Three algorithm are compared with our proposal:
Mobility state estimation based scanning(MSEBS)[14];Background
inter
frequency
measurement(BIM)[13];obstructed path(op)[10].
The MSE-BS performs scanning based on the
mobility state of the UE. The algorithm selects the
cell for scanning based the mobility state. UE in the
normal state
perform scanning of the
SCeNBs.User Equipment performs scanning of
neighboring cells with an interval of 1 second.
The Second algorithm ,BIM prolongs the
scanning period in order to save energy. Last, the
performance is also compared with op algorithm.
the proposed distance based scanning denoted as
DBs scans only cells included in user equipment.
B. Simulation Results
The average number of scanned cells per second
when UE is connected to the MeNBs. As can be
seen the MSE-BS algorithm scans all cells to which
the handover from MeNBs is possible. The BIM
reaches lower average number of scanned cells
than MSE-BS. The number of scanned cells
decreased with the MSE-BS .
Contrary BIM and MSE-BS the number of
scanned cells is not rising continuously with the
density of SCeNBs for the op. For low density of
SCeNBs, the number of scanned cells rises with the
number of cells. The reason is that the paths among
cells is getting lower.
The higher value of GI leads to earlier addition of
neighbouring cells to the set of scanned cells.
Earlier scanning of neighbouring cells negatively
influences the energy consumption as presented.
The average energy consumption is presented. it
depicts that highest energy consumption per second
is more than 70 m. if it can be used then the energy
consumption is reduced for 85%.
The prolongation of the time of connection to
MeNBs leads, at the same time to a shortening of
the time of connection to the SCeNBs. The Main
purpose of the SCeNBs in network is to improve
QOS for users in its proximately. Therefore,
lowering utilization of the SCeNBs leads to loss in
their potential to improve network performance.
The highest energy consumption is reached as
expected by the MSE-BS algorithm. it will be
significantly reduced for all densities of SCeNBs.
The reduction is lowered for all densities.
V. CONCLUSION
As a result, our proposed algorithm reaches very
low number of scanned cells and low energy
consumption while high utilization of SCeNBs is
ensured. our Distance based scanning algorithm
outperforms the MSE-BS and OP for more than
90%.Thus,it can be used not only in existing
mobile networks but it very appropriate also for
future 5g heterogeneous networks. in future we
intend to focus on self optimization phase of the
proposed algorithm in order to facilitate automatic
adaption of the set of cells for scanning .
ACKNOWLEDGEMENT
The Scanning algorithm will wishes to
acknowledge that help to reduce the efficiency for
future mobile which was introduced by authors
give an optimized result for correct nodes.
REFERENCES
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Fig.5 Average energy consumption for
neighbourhood scanning
ISSN: 2231-5381
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