1. The document discusses performance enhancement of WiMAX mobile handover using OFDM with M-QAM modulation and best relay selection. 2. It analyzes the bit error rate performance of M-QAM OFDM systems for different modulation schemes, numbers of relays, and subchannels. 3. The results show that M-QAM OFDM with best relay selection provides higher performance and lower error communication compared to other techniques.

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International Journal of Electronics and Communication Engineering & Technology
(IJECET)
Volume 6, Issue 9, Sep 2015, pp. 11-18, Article ID: IJECET_06_09_002
Available online at
http://www.iaeme.com/IJECETissues.asp?JTypeIJECET&VType=6&IType=9
ISSN Print: 0976-6464 and ISSN Online: 0976-6472
© IAEME Publication
PERFORMANCE ENHANCEMENT OF WI-
MAX MOBILE HANDOVER OFDM USING
M-QAM SYSTEM WITH BEST-RELAY
SELECTION
Pratima Singh
M. Tech. Scholar
Department of Electronics & Communication Engineering
Institute of Engineering & Technology, Alwar-301030 (Raj.), India
Dr. Anil Kumar Sharma
Professor & Principal
Department of Electronics & Communication Engineering
Institute of Engineering & Technology, Alwar-301030 (Raj.), India
ABSTRACT
According to present skill in future generation networks will be
categorized by variable and high data rates, quality of services, unbroken
mobility both within a network and between networks of different technologies
and service providers. An important aspect of components in a global next
generation network is standardization to allow vendor independence and
interoperability. A technology developed to fulfill these characteristics,
standardized by IEEE, is 802.16, also referred to as WI-MAX. The mobile
World-Wide Interoperability for Microwave Access (Mobile WI-MAX) air
interface accepts orthogonal frequency division multiple access (OFDMA). In
our study, we investigate the error rate performance of improvement variety
for M-array QAM OFDM-based system with best-relay selection up to 64-
array QAM because 32 arrays are already developed. The results present bit
error probability of M-array QAM OFDM-based system with best-relay
selection for different values of the numbers of relays the numbers of sub-
channels and modulation scheme. M-array-QAM OFDM-based system with
best-relay selection provides higher performance and error less
communication.
Keywords: BPSK, QAM, OFDM, QPSK, WI-MAX

2. Pratima Singh and Dr. Anil Kumar Sharma
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Cite this Article: Pratima Singh and Dr. A. K. Sharma. Performance
Enhancement of Wi-Max Mobile Handover OFDM Using M-QAM System
with Best-Relay Selection, International Journal of Electronics and
Communication Engineering & Technology, 6(9), 2015, pp. 11-18.
http://www.iaeme.com/IJECET/issues.asp?JTypeIJECET&VType=6&IType=9
1. INTRODUCTION
WI-MAX tools or technology supports IEEE 802.16 and it is a telecommunication
protocol giving full access to mobile net worldwide. WI-MAX technology does
numerous functions at a time such as contribution high speed internet, provided that
phone services like transformation of information, video streaming voice application
etc. In the OFDM transmission systems, each and every frame is moderated below the
selective bandwidth and high speed fading channel. The system shows can also be
varied very across the subcarriers, based on the input data stream. Supposing the
comparable fixed transmission systems are compulsory for each OFDM subcarrier,
the probabilities of receiving errors is repressed by OFDM subcarrier with higher
order modulation, resulting in deficient performances. Orthogonal Frequency Division
Multiplexing (OFDM) is functional in this project according to the IEEE 802.16
standard, which permits Transmission of data rates from 6Mbps up to 54Mbps.
Distinct modulation schemes as Binary Phase Shift Keying (BPSK), Quadrate Phase
Shift Keying (QPSK) and M-array Quadrature Amplitude modulation (M-QAM) are
used according to differing Data Rates for Signal visualization at each block of
Transceiver. Simulation is carried to measure Bit Error Rate (BER), Symbol error rate
& to measure number of data bits, coded bits in OFDM symbol by using different
modulation & Code rate. Pre implementation simulation for WI-MAX system is
developed to decrease system cost & to recover active utilization with inadequate
properties.
The Orthogonal Frequency Division Multiplexing (OFDM) is a multiplexing
method that boundaries a channel with a higher comparative data rate into numerous
orthogonal sub-channels with a lower data rate. For high data rate transmissions, the
symbol duration Ts is short. Then ISI due to multipath broadcast misrepresents the
received signal, if the symbol durations are smaller as the maximum delay of the
channel. To moderate this effect a narrowband channel is needed, but for high data
rates a broadband channel is needed. Figure.1 shows a WI-MAX model with base
station.
Figure 1 Wi-max with Base Station

3. Performance Enhancement of Wi-Max Mobile Handover OFDM Using M-QAM System with
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To overawe this difficult the total bandwidth can be divided into numerous
Parallel narrowband subcarriers. Thus a block of N serial data symbols with Duration
Ts is transformed into a block of N parallel data symbols, each with Duration T =
N×Ts. The goal is that the new symbol duration of each subcarrier is superior to the
maximum delay of the channel, T > T max. With many low data rate subcarriers at the
same time, a higher data rate is attained. In order to make the OFDM symbol a serial
to parallel block is used to convert N serial data symbols into N parallel data symbols.
Then each parallel data symbol is moderated with different orthogonal frequency
subcarriers, and added to an OFDM symbol. Since wireless communications systems
are vulnerable to multi-path channel reflections, a cyclic prefix is additional to
decrease ISI. A cyclic prefix is a recurrence of the first unit of a symbol that is added
to the end of the symbol. In adding, it is significant because it allows multi-path
representations of the original signal to fade so that they do not interfere with the
subsequent symbol.
Figure 2 Cyclic Prefix Insertion Wireless Communications Systems
2. PROBLEM STATEMENT
The Mobile WI-MAX, in the earlier insufficient years has become one of the most
important technologies because it has the ability to provide users with a high speed
wireless connection in a Metropolitan Area Network. Mobility brings with it the need
of handovers which occur when a user moves from one cell to the other. Handover is
considered as a highly important issue in mobile WI-MAX. Mobile WI-MAX holds a
clear advantage over these technologies as it offers much higher data rates and a wider
transmission range, but the handover related issues must be resolved to allow WI-
MAX to compete in the market and fulfill its potential.
3. SYSTEM MODEL
The general system block diagram is given in Figure.3. where each of the three main
blocks are Transmitter, Channel, and Receiver.

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Figure 3 System Block Diagram.
Transmitter: The equiprobable binary data bits b from the information source are
passed through the channel encoder. The encoded bits are then interleaved before
being converted to symbols (the modulation block) and transmitted through the
channel. Better results can be obtained by optimizing the inter-laver with respect to
the channel time variations, however. By performing channel coding and interleaving,
we can benefit from some degree of channel time diversity, which depends on the
channel coherence interval and the frame length chosen for data transmission.
Channel: Let us denote by hx and hy the large-scale and small-scale irradiance
fluctuations, respectively. hx and hy are assumed to be statistically independent and
described by a gamma distribution. Based on these assumptions, the intensity
fluctuation h = hxhy has a ΓΓ distribution with the probability density function (PDF)
as follows [9].
Here, α and β are the effective numbers of large-scale and small-scale eddies of
the scattering environment, respectively, and Kα(x) is the modified Bessel function of
the second kind and order α. Assuming plane wave propagation that is valid for
relatively long-range applications, as well as turbulent eddies of zero inner scale,
these parameters can be directly related to the atmospheric conditions.
where σ 2
x and σ 2
y denote the variances of hx and hy, respectively, and χ 2
=
1.23C 2
n k 7/6
L 11/6
is the Rytov variance. Here, k = 2π/λ is the wave number
with λ the wavelength, and L is the link distance. Also, C 2
n stands for the index of
refraction structure parameter.
Receiver: At the receiver, after signal detection (the demodulator block) and de-
interleaving, channel decoding is performed. The demodulation is performed based on

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the received signal light intensity. The electrical signal after the optical/electrical
conversion is:
where I is the received signal light intensity, Ia is the remaining ambient light
intensity after frequency and spatial filtering, and η is the optical/electrical conversion
efficiency. Also, n is the sum of thermal, dark, and shot noise. We assume that the
ambient light can be almost perfectly cancelled. So, after the cancellation of the
ambient light, the received signal before demodulation is:
We suppose that the receiver is thermal noise limited, and consider n as a zero-
mean Gaussian Additive Noise of variance σ 2
n, independent of the signal I.
Let Ts denote the symbol duration and N 0 the noise unilateral power spectral density.
Taking into account the low-pass filtering of bandwidth 1/2Ts after photo-detection,
the noise variance equals σ 2
n = N 0/2Ts. We further consider the received signal
intensity I as the product of I 0, the emitted light intensity, and h, the channel
atmospheric turbulence with the PDF given in (1): I=hIo. The demodulator provides at
its output logarithmic likelihood ratios (LLR) on the transmitted bits instead of hard
values 0 or 1 (see Section 3 for more details). In other words, we perform soft signal
detection. As we will explain in Section 4, in most cases, we perform soft-input soft-
output (SISO) channel decoding, because as it is well known, soft decoding provides
a better performance, compared to hard-decoding [10]. In such a case, the LLRs at the
output of the demodulator are fed to the channel decoder, which in turn, provides
LLRs on the information data bits at its output.
4. PROPOSED IMPLEMENTATION
The Modulation techniques used are, Binary Phase Shift Keying (BPSK) and
Quadrature Phase Shift Keying (QPSK). BPSK gives Less Probability of error and
need a complicated synchronizing circuit at the receiver for generation of local
carrier. Ambiguity in the output signal because use square law device in receiver side.
In QPSK for the same bit error rate, the BW required by QPSK is reduced to half as
compared to BPSK. Because of reduced BW, the information transmission rate of
QPSK is higher. Variation in QPSK amplitude is not much. Hence carrier power
almost remains constant. The projected impression is to first splitting the conservative
signal that is going for FFT, into two fragments. Once this each part is Fourier
changed and then the outputs are collective together. Consider a system with ‘n’
number of signals waiting for Fourier change at the receiver. These ‘n’ signals are
split into two equal parts of length ‘n/2’. Each signal is passed complete Fourier alter.
It will result in two orders each of length ‘n’. These signs will be then added to create
the final distorted signal. After the demodulation of the more signal the predictable
bits are compared with the conveyed bits. Let us assume that the frequency offset is
a fraction of subcarrier design i.e.
Also, for simplifying the equations, lets us assume that the transmitted symbols on
all subcarriers, =1 . The received signal is,

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The output of the correlation for sub-carrier ‘m’ is, For , the integral reduces
to the OFDM receiver with no impairments case. Though for non-zero values of , we
can see that the amplitude of the correlation with subcarrier ‘m’ includes, Distortion
due to frequency offset between actual frequency and the preferred frequency .
5. PARAMETERS USED
The input parameters used in simulation are shown in Table-1.
Table-1 Input Parameter for Status value in Proposed Simulation Model
Sl. No. Parameter Extended Values
1 FFT size. N-FFT 32
2
Number of used subcarriers. N-
DSC
256
3 FFT Sampling frequency 24MHz
4 Subcarrier spacing 312.5kHz
5 Used subcarrier index {-26 to -1, +1 to +26}
6 Cyclic prefix duration, 0.6us
7 Data symbol duration, 2.2us
8 Total Symbol duration, 4us
9
Number of used subcarriers. N-
DSC
52
10 FFT Sampling frequency 40MHz
11
Modulation Schemes Modulation Schemes BPSK, QPSK,
16-QAM, 64-QAM
6. RESULT
Handover performance of mobile WI-MAX is evaluated by measuring Bit Error Rate
(BER) versus time elapsed when packets transmitted from source to destination
station through different modulation techniques like BPSK, QPSK & 16 M-QAM.
During performance evaluation different parameters like cyclic prefix, no. of OFDM
symbols, bandwidth and no. of channels are considered which are entered by user.
Following are the steps followed for simulation-
 Simulations are as (BPSK, QPSK, 16 M-QAM).
 Type of "cyclic prefix" (1/4 1/8 1/16 1/32).
 The simulation WITH and WITHOUT encoding of the bits and study.
 We carry out the simulation through different SUI channels (=1).
 We do a simulation with different values of the nominal BW of the system.
 To exit the program.

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Figure 4-6 shows the simulation results for BPSK, QPSK and M-QAM.
Figure 4 BER Received Symbol for Cycle Prefix (G=0.25) for BPSK
Figure 5 BER Received Symbol for Cycle Prefix (G=0.25) for QPSK
Figure 6 BER Received Symbol for Cycle Prefix (G=0.25) for M- QAM

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7. CONCLUSION
It is experiential that for a particular value of Bit Error Rate, SNR value for BPSK
/QPSK is lower than 16QAM and 64QAM. In the first form of WI-MAX values, the
movement was not maintained at all. Through the time developed a necessity of user
mobility, the performance of the OFDM system is compared by varying the size of
the QAM modulation. In previous work BER for 16-QAM was 0.001 at 0.25 cycle
prefix and 28 MHz and in our research, it optimized with 0.0001 with same input
parameter so that BER performance of OFDM improves with increasing size of QAM
modulation. In future, adaptive cyclic prefix length & FFT size may be used which
improves the performance much better.
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