Bandwidth allocation mechanisms in the next mobile generation: A practical Approach

IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 6, Ver. IV (Nov – Dec. 2015), PP 55-60
www.iosrjournals.org
DOI: 10.9790/0661-17645560 www.iosrjournals.org 55 | Page
Bandwidth allocation mechanisms in the next mobile generation: A
practical Approach
Sara Salman SelimanAlsafi1
, Ashraf Gasim Elsid Abdalla2
, AminBabiker
A/Nabi Mustafa3
1,3-
Faculty of Engineering- Neelain University Khartoum –Sudan
2-
College of Engineering-Sudan University of Science and Technology
Abstract: This paper presents an algorithm for bandwidth management in integrated LTE network and WLAN.
The proposed algorithm also suitable for multimedia network (image, telephone and videophone).
A software tool is implemented to simulate the proposed algorithm it is basedon windows for random
distribution numbers such as Poisson distribution functionfor traffic generation and uniform distribution for
mobile location using MATLAB. The parameters taken in this proposed simulation model are: number of user,
type of traffic, user class and user bandwidth. The results of the simulation indicate that the new algorithm
increases the bandwidth availability in the lower data rate network and this reduces the congestion in the high
data network.
I. Introduction:
"Mobile wireless industry has started its technology creation, revolution and evolution since early
1970s.In the past few decades, mobile wireless technologieshave experience 4 or 5 generations of
technologyrevolution and evolution, namely from 1G to 4G.The cellular concept was introduced in the 1G tech-
neology which made the large scale mobile wirelesscommunication possible. Digital communication has
replaced the analogy technology in the 2G which improved the wireless communicationquality. Data
communication, in addition to thevoice communication, has been the main focus in the3G technologies and a
converged network for bothvoice and data communication is emerging. Withcontinued RD, there are many
killer applicationopportunities for the 4G as well as technological challenges."[1]
The 5G potential will require the design of a single wireless user terminal able to autonomously operate
in different heterogeneous access networks.A fully reconfigurable terminal changes its communication functions
depending on network and/or user demands. Moreover, this terminal will have to exploit various surrounding
information such as communication with navigation and localization systems and communications with weather
forecast and emergency systems in order to provide richer user services. However, the richness of the services
will necessitate higher bit rates, which will be the main driving factor towards broadband multimedia
development. [2]
Table (i):Comparison ofallGenerationsofmobileTechnology [3].
5G4G3G2G1GTechnology
Features
Soon(probaly202
0)
Now2004-20101990-20041970-1980Start/Deployment
high1Gbps2Mbp64 Kbps2KbpsData Bandwidth
WWWW(comin
g soon)
WiMAX LTE
Wi-Fi
CDMA 2000(
1XRTT,EVDO)
UMTS,EDGE
Digital Cellular
Technology
Analog cellular
technology
Technology
Dynamic
Information
access, Wearable
devices with AI
Capabilities
Dynamic
Information
access,
Wearable
devices
Integrated high quality
audio, video and data
Digital voice
SMS, Higher
capacity
packetized date
Mobile telephony
(voice)
Service
CDMACDMACDMATDMA-CDMAFDMAMultiplexing

Bandwidth allocation mechanisms in the next mobile generation: A practical Approach
All PacketAll PacketPacketCircuit, packetCircuitSwitching
InternetInternetPacket N/WPSTNPSTNCore network
II. Bandwidth requirement formultimedia:
The network bandwidth is divided among users sharing a cell. The amount of bandwidth per user is a
measure of the network capacity, because it depends on the distribution of the user population [4]. The total
bandwidth for 5th
Generation proposed as 1.056Gbit/s distance of up to 2kilometres with the use of an
8*8MIMO [5]. Table (ii) shows the service requirements in term of bandwidth
Table (ii): service requirements [6]
Data RateService
16kbit/sImage
8kbit/sTelephone
16kbit/sVideophone
III. Simulation Scenario:
The flow chart for the proposed algorithm:
IV. Mathematical model:
For the application of the proposed model we used MATLAB to configure like environment real
environment for users of mobile cellular systems. Using random generator function, we select a random location
for users of mobile terminals in the model. And to generate calls to the users arrival times randomly used.
We used Poisson distribution function because of the advantages it is simple, stable and independent in
all moments of time. Poisson distribution gives the number of arrivals in a constant length (t) distributed in the
mean value (λt) [7], the following relationship
P x,t =(( λt)x
/x!)e−λt(1)

After making that environment through consideration of the physical model we can use the data to find less can
receive user when the maximum distance it can travel without having to transfer it to the base station.
Simulation:
Figure 4.1 shows that simulation windows and it represented the random distribution of nodes inside the
building as defined previously, the X axis represent window length and Y axis represented width equal 50 meter
both of them.
Fig:4.1: simulation model window
The second result shown and this random generated depend on the user class (real time and no real time).the X
in figure 4.2 represented the users or nodes needed data rate axis is the number of node which equal 60 user and
Y axis represented data rate that each user needed .
Fig: 4.2: node application data rate
The third result as shown in figure 4.3 it represented the type of traffic or user class (real time and non-
realtime) random generated 1 for real time user and 0 for non-real time user. The X axis is user class 1 or 0, and
Y axis represented number or user in each class. Also figure 4.4 show the percentage of each type of users in
pipe diagram.
0 10 20 30 40 50 60
250
300
350
400
450
500
550
node applcation data rate
Nodes index
datarateinkbps

Fig: 4.3: Traffic classification for users
Fig: 4.4:type of user in pipe diagram
Figure 4.5 represented the maximum data user nodes. The X axis is the nodes index which equal 60
users and Y axis represented bandwidth in kbps.
Fig: 4.5:maximum data user nodes
The result as shown in figure 4.6 it represented the assign resource WLAN user bandwidth. The X axis
is nodes index and Y axis represented bandwidth in kbps and figure 4.7shows the WLAN available bandwidth
after new algorithm.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
5
10
15
20
25
30
35
40
type of user
type of traffic
numberofuser
53%
type of user
47%
real time user
non real time user
0 10 20 30 40 50 60
0
0.5
1
1.5
2
2.5
3
3.5
x 10
5
Node index
BandwidthMbps
Maximum data user/nodes
real time user
non real time user

Fig: 4.6:assign resource WLAN user bandwidth
Fig:4.7 :WLAN available bandwidth after new algorithm
Figure 4.8 represented the assign resource LTE user bandwidth and figure 4.9shows available
bandwidth after new algorithm. The X axis is the nodes index which equal 60 users and Y axis represented
bandwidth in kbps.
Fig: 4.8: assign resource LTE user bandwidth
0 10 20 30 40 50 60
0
1
2
3
4
5
6
7
8
x 10
4
Assign resources WLAN user bandwidth
Nodes index
BandwidthinKbps
0 10 20 30 40 50 60
4
4.5
5
5.5
6
6.5
7
7.5
x 10
4
WLAN Available Bandwidth after new Algrosithm
Nodes index
BandwidthinKbps
0 10 20 30 40 50 60
-2000
-1500
-1000
-500
0
500
1000
Assign resources LTE user bandwidth
Nodes index
BandwidthinKbps

Fig:4.9: LTEavailable bandwidth after new algorithm
IV. Conclusion:
The effective bandwidth management algorithm enhances the bandwidth optimization and utilization.
In this study the proposed algorithm for bandwidth management,in integrated LTE and WLAN networks,
improved the bandwidth availability in the WLAN and it reduces the congestion in the LTE band. This will
grantee the required quality of services however it will introduce a high signaling load due to the frequent
handover between the two networks.
References:
[1]. http://www.isindexing.com/isi/papers/1396420201.pdf)
[2]. Dr. Anwar M. Mousa"Prospective of Fifth Generation MobileCommunication" University of Palestine,Gaza- Palestine.
[3]. “5G Mobile Technologies”
[4]. http://www.doc.ic.ac.uk/~nd/surprise_95/journal/vol1/mjf/article1.html
[5]. Metis project presentation (general overview 25/3/2013) Disclaimer .some of the icons used in the METIS project presentation are
owned by Eriksson. They will be later removed and replaced by METIS specific icons.
[6]. Data communication and computer network PHI learning retrieved 10 July 2011.
[7]. V. B. Iverson, “Tele traffic engineering and network planning,” Technical University of Denmark, Technical University of
Denmark Building 343, May 2010. [Online]. Available:http://www.fotonik.dtu.dk .
0 10 20 30 40 50 60
-1500
-1000
-500
0
500
1000
1500
LTE Available Bandwidth after new Algrosithm
Nodes index
BandwidthinKbps

Bandwidth allocation mechanisms in the next mobile generation: A practical Approach

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Bandwidth allocation mechanisms in the next mobile generation: A practical Approach