This document discusses determining the optimal FFT size for WiMAX systems under different fading conditions. It presents the results of simulations performed using QualNet to analyze quality of service metrics like packet delivery ratio, delay, jitter and throughput for various FFT sizes (2048, 1024, 512, 128) and data rates (200-1000kbps) under Rayleigh and Rician fading. The key findings are that under Rayleigh fading, FFT size 128 provides the maximum tradeoff index, while under Rician fading, FFT size 512 is optimal. The tradeoff index, calculated as a weighted combination of the QoS metrics, is used to determine the best configuration.

1. International Journal of Electronics and JOURNAL Engineering & Technology (IJECET), ISSN 0976
INTERNATIONAL Communication OF ELECTRONICS AND
– 6464(Print), ISSN 0976 – 6472(Online) Volume 3, Issue 1, January- June (2012), © IAEME
COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)
ISSN 0976 – 6464(Print)
ISSN 0976 – 6472(Online)
Volume 3, Issue 1, January- June (2012), pp. 139-146
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DETERMINATION OF OPTIMUM FFT FOR WI-MAX UNDER
DIFFERENT FADING
Abhishek choubey
HOD,ECE deptt.
R.K.D.F. Bhopal
abhishekchaubey84@gmail.com
Mayuri Kulshreshtha
M.E (D.C.)
R.K.D.F. Bhopal
mayuri.kulsh@gmail.com
Karunesh
M.Tech (Electronics Engg.)
Allahabad University
karunesh.ec@gmail.com
ABSTRACT
Here we are using Worldwide Interoperability for Microwave Access (WiMAX)
technology with focus on Quality of Service (QoS). The basics of the technologies for the
physical layer and the Media Access Control (MAC) layer are introduced. Here in this
paper an area-efficient FFT processor is proposed for IEEE 802.16 Wi-MAX systems.
The proposed scalable FFT processor can support the variable length of 2048, 1024, 512
and 128. And we are taking various data rates as 200 Kbps, 400Kbps, 600 Kbps,
800Kbps and 1000 Kbps to find the Quality of service and the trade off index to find
which FFT size is suitable for wi-max system at different channel properties
Here the simulator which we are using in our work is qualnet simulator version 5.1. As
the main aim of wi-max is to provide the best quality of service so here we’ll find the
QoS at different scenarios based on the values of FFT and by applying the different data
rates and also we are using heterogeneous network to simulate QoS and we are also using
CBR which is traffic generator application layer protocol used to generate traffic at
constant bit rate.
Keywords: Wi-Max, IEEE 802.16, Qualnet simulator, FFT.
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2. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976
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I. INTRODUCTION
WiMAX is a telecommunication protocol that provides fixed and mobile internet access,
in which this protocol combines a number of wireless technologies that have emerged
from IEEE to face the rapid demand of higher data rate and longer transmission range in
wireless access and to enable a high speed connection to the Internet in terms of
multimedia service, trade, commerce, education, research and other applications. In other
hand, WiMAX technology based on IEEE 802.16 standard which is a Broadband
Wireless Access (BWA) that offers mobile broadband connectivity. Here first of all we
are defining wi-max architecture and then the simulation model for which we want to
simulate our result. Here we are simulating our result using two fading techniques such as
Rayleigh fading and the Racian fading.
We are taking four FFT values as 2048, 1024, 512 and 128 and the data rates are 200
Kbps, 400 kbps, 600 Kbps, 800Kbps so that we can find on which value of FFT and data
rate we’ll get the best TOI. TOI is trade off index which is used to simulating the best
results among them. We are also using CBR which generates the constant traffic and it is
the application layer protocol. Result will be described in our next section.
II. WI-MAX SIMULATION MODEL
The purpose of this simulation study is to investigate and evaluate different types of
scenarios in order to determine the one that is most efficient in WiMAX network. The
simulations are performed using QualNet simulation. This simulation provides an
intuitive model set up capability that includes packet delivery ratio, average jitter,
average end to end delay and throughput.
Here we are taking two base stations and 20 are the subscriber station. Cloud icon is used
as wireless subnet and we’ll change the property of physical layer and MAC layer in
wireless subnet and base stations as we want to simulate our result using Wi-max.
We are simulating QoS without fading, with Rayleigh fading and with Racian fading.
The FFT values vary from 2048 to 128 and data rates varies from 200 Kbps to 1000
Kbps.
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Frequency band (GHz) 2.4
Channel bandwidth (MHz) 20
FFT size 2048-128
Number of MS 11-22
Number of BS 2
BS transmit power 20 p_t dB m/ height (m)
MS transmit power 15 p_t dB m/ height (m)
Services types (QoS) Packet delivery ratio, delay, jitter, throughput
Data rates (Kbps) 200-1000
Simulation time 30s
III. PERFORMANCE EVALUATION
Here we are taking different channel properties for simulating the best result. Firstly we
are simulating result with Rayleigh fading.
Quality of service with Rayleigh fading
Here we’ll find the QoS in terms of packet delivery ratio, average end to end delay,
average jitter and throughput. First of all we are taking channel property as Rayleigh
fading, the graphs for all the services will be shown as-
Graph 4.1 Packet Delivery ratio
Graph 4.1 is the graph of packet delivery ratio, which is the ratio of the received packets
and the transmitted packets. At X-axis we are taking different data rates as 200 Kbps, 400
Kbps, 600 Kbps, 800 Kbps and the 1000 Kbps. We are also taking the values of FFT as
2048, 1024, 512 and 128 at Y-axis. Here we can see at all the three values of FFT all
lines are about same but at 2048 FFT the values of packet delivery ratio is changed.
different data rates all the points are changed, so from the above graph we can see there is
no affect of FFT for packet delivery ratio but at different data rates the value of packet
delivery ratio is changed. As we are increasing data rates the packet delivery ratio is
decreasing it means at higher data rates less amount of packets are receiving at the
destination.
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Graph 4.2 Average jitter
Graph 4.2 is the graph of average jitter. As we know Jitter is the variation in arrival times
of successive packet from a source to a destination. Here we can see when we are
changing the values of FFT there is little effect on jitter, but with increasing the data rates
jitter is decreasing continuously. So we can say jitter is inversely proportional to data
rate, it means at increasing data rates jitter is decreasing.
Graph 4.3 average delay
Graph 4.3 is the graph of average delay. Here we can see at FFT value of 2048 and 1024
with all data rate values except 1000 Kbps the delay is about to same or we can say about
to constant, it means there is little delay with FFT 2048 and 1024. When we talk about
the FFT value 512, the delay is increasing with increasing data rate. But at 128 FFT delay
is increased at some values of data rates and after then it is continuous for other data
rates.
Graph 4.4 Throughput
Graph 4.4 is the graph of throughput. Throughput is defined as how much data is
accepted at the receiver. Here we can see throughput is increasing with increasing Data
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rate, it means throughput is ditrectly proportional to data rates. But when we talk about
FFT there is little effect of FFT at throughput.
Quality of service with Racian fading
Now we’ll define the QoS by changing the channel property as Racian fading.
Graph 4.5 Packet delivery ratio
Graph 4.5 is the graph of packet delivery ratio for Racian fading. Here we can see the
packet delivery ratio for 2048 and 1024 is much heigher than that of FFT value 512 and
128. But when we talk about data rates the ratio is about to constant for the FFT 512 and
128, but for othe FFT value the ratio is firdt decreasing and then it is constant.
Graph 4.6 average jitter
Graph 4.6 is the graph of average jitter. As we know Jitter is the variation in arrival times
of successive packet from a source to a destination. Here we can see when we are
changing the values of FFT there is little effect on jitter, but with increasing the data rates
jitter is decreasing continuously. So we can say jitter is inversely proportional to data
rate, it means at increasing data rates jitter is decreasing. We can also that jitter for
Racian fading is same as the jitter for Rayleigh fading.
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Graph 4.7 Average delay
Graph 4.7 is the graph of delay with Racian fading. Here we can see dalay for FFT value
2048 and1024 is much heigher then delay with FFT value 512 and 128. So we can say
FFT and delay are directly proportional to each other. At all the data rates the delay is
about to same depending upon the FFT values.
Graph 4.8 Throughput
Graph 4.8 is the graph of throughput. Here we can see throughput is increasing with
increasing Data rate, it means throughput is ditrectly proportional to data rates. But when
we talk about FFT there is little effect of FFT at throughput. We can also throughput with
Rayleigh fading is same as throughput with Racian fading.
IV. CONCLUSION
Here we’ll find the conclusion using finding the value of Trade off Index, which is used
to find that on which channel properties we’ll get the best quality of service. There are
three channel properties in which we are finding the QoS. These properties are done with
Rayleigh fading and with Racian fading. The value of TOI (trade off index) will be found
by the formula.
It is measured as the formula-
TOI= (a*throughput) + (b*packet delivery ratio)/(c*delay) + (d*jitter)
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Where a, b, c, d are the weights which depends upon the person, who is trying to evaluate
the efficiency. In this paper work throughput, delay, jitter and average packet delivery
ratio are there to calculate trade off index.
For calculating, trade off index firstly we’ll show the values of above tables, then we’ll
implement another graph by comparing these values. Here we have shown some
constants as a, b, c and d, the values for all these constants will be put as some unit place,
So every value has to be brought as unit place, whatever is in points will be multiplied by
positive power of 10, and if not in the points then multiplied by negative power of 10.
Trade of index with Rayleigh fading
Graph 5.1
Here for conclusion we are having the graph of TOI. As we know by using TOI we have
to find on which value of FFT we’ll get the maximum TOI. From the above graph we can
see the FFT value for 128 we’ll get the maximum trade off index.
Trade off index with Racian fading
Graph 5.2
Now we’ll find the maximum TOI for Racian fading. Here we can see that for the FFT
value of 512 we’ll get the maximum TOI.
So we can conclude that the best FFT value for Rayleigh fading is 128 and for
Racian fading the optimum FFT value is 512.
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V. REFERENCES
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[8] Computer World. URL: http : / /www. computerworld .com/s/article/9215414/IEEE
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