 Open Access
 Total Downloads : 7
 Authors : C.Vinodh, N.Karthik
 Paper ID : IJERTCONV2IS12001
 Volume & Issue : NCACCT – 2014 (Volume 2 – Issue 12)
 Published (First Online): 30072018
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Performance Comparision of OFDM Synchronization Techniques
C.Vinodh and N.Karthik
P.G Scholar, ME Communication Systems, Sri Sai Ram Engineering College, Chennai Assistant Professor, ECE Department, Sri Sai Ram Engineering College, Chennai
Abstract In the recent years there occurs a rapid growth in wireless communication which increased the need of high speed data transmission.The future wireless systems are expected to support a wide range of services which includes video, data and voice. Orthogonal Frequency Division Multiplexing (OFDM) is a promising candidate for achieving high data rates in mobile environment because of its multicarrier modulation technique and ability to convert a frequency selective fading channel into several nearly flat fading channels. In this project, Performance Comparison of OFDM synchronization technique is considered. Timing offset, Carrier frequency offset and Phase offset are considered. Symbol synchronization is done with the help of Training Sequence which is deviated from conventional cyclic prefix based synchronization. Cyclic Prefix of the OFDM symbol has been used in Carrier frequency offset estimate based on Maximum Likelihood Estimate (MLE).Phase offset estimation was also carried out with the help of training sequences. These estimated offsets were used to make corrections in the received signals to achieve better signal power to noise power ratio at the input of the detector.

INTRODUCTION
The evolution of wireless technologies had grown up remarkably since 1897 .Orthogonal frequency division multiplexing (OFDM) is the most popular Communication system which evolved as the future.
The differences occurring between OFDM and FDM are shown below in fig 1 the fig 2 below shows OFDM transceiver which converts digital data and maps its to subcarrier amplitude and phase. It transforms spectral representation of data to space domain
Figure 1.1 Frequency spectrums of FDM signal and OFDM signal
The Inverse Fast Fourier Transform (IFFT) can be used to perform the above operations but it is much more computationally inefficiency. The OFDM signal is transmitted by mixing up required frequency. In the receiver side the reverse of mixing the RF signal to base band for processing is used and then FFT is used to analyze the signal in the frequency domain.
Now consider Orthogonal Frequency Division Multiplexing (OFDM) system which is illustrated in figure 1.4.The input data bits are initially mapped using the modulation QPSK in which the bits are grouped as symbols and then Inverse Fast Fourier transform is taken. After that the training sequences and cyclic prefix are inserted which are again passed through the AWGN and Fading channel. Using synchronization, the OFDM symbols are mapped to the original position. After removing of cyclic prefix, training sequences and FFT is taken. After that symbols are decoded into bits.
III. PROPOSED WORK
Figure 1.4 Block diagram of OFDM System with Synchronization
Certain issues associated with the receiver subsystem are High sensitive time synchronization
Frequency offset synchronization and frequencyselective fading channels.

RELATED WORKS:
The various previous works related to this work is stated below:

In [1], the authors discussed about synchronization using training sequences. Estimation of timing offset, frequency offset are done in this report.

In [2], symbol detection using one training sequence for two symbols. The algorithm use CramÂ´erRaolower bound for frequency offset .

In [3], describes about Maximum Likelihood Estimation (MLE) of symbol and carrier frequency offset with the help of Cyclic prefix .
In [4], describes optimal ML estimator of time and frequency offset using window. The correlation residing in cyclic prefix samples and useful data samples
The aim of this work is to study the receiver synchronization algorithm of OFDM systems which is shown in figure 1.4 by simulating a transceiver. With the help of design specification chosen, the algorithm in [1] was carried out with the help of MATLAB simulation considering the effects of multipath channel impairments, Carrier Frequency Offset (CFO) and synchronization of OFDM symbol.
The techniques involved in synchronization of OFDM receiver over time, carrier frequency and phase offsets are described. The simulation specifications and observed results are also disused in this paper.
The block diagram of OFDM system shown in figure has been carried out with the following design specifications with anomalies described in the earlier chapters like Time offset, Carrier Frequency offset and phase offset.

DESIGN SPECIFICATIONS
In this work, the simulation parameters have taken as stated in [1]. This used 256 point fast Fourier transform (FFT) with 240 active subcarriers, 15 guard subcarriers, 14 cyclic prefix, sample frequency of 1.6MHz, subcarriers spacing of 6.25kHz, number of OFDM symbols per time slot is 4, training sequences of 128.

SIMULATION OF OFDM SYSTEM IN AWGN CHANNEL
In the first step simulation was carried out to estimate the effect of AWGN channel on bit error rate (BER) performance over signal power to noise power ratio (SNR). The simulated result is plotted in figure 4.1, and it is observed that OFDM system requires minimum of 11dB SNR to yield BER
of 104.
Fig 3.1 SNR vs. BER curve for AWGN channel

SIMULATION OF OFDM SYSTEM IN RAYLEIGH CHANNEL
The simulation of OFDM system is carried out with the help of following design specification in Rayleigh multipath channel.
pling Time
0.1ns
lays in ns
781 156
2344
ins in dB
3 6
pread
2344ns
r shift
0
type
cy selective & ding
Table 3.2 Design specification

SYMBOL SYNCHRONIZATION OF OFDM SYSTEM
Awellknown drawback of OFDM is that it requires accurate symbol synchronization because the OFDM signal is demodulated based on symbol structure and the arriving time of the received signal isunknown. Wrong symbol synchronization would cause the intersymbol interference (ISI), and then bring up an increase of bit error rate (BER), so it is essential to achieve accurate and fast symbol synchronization for OFDM system.
The following graph shows that when offset = 125 and estimated timing is 1084, the OFDM system gets synchronized to the estimated timing.
Figure 3.2 Probability occurrence of estimated timing

OBSERVATIONS

From the simulation it has been inferred that after an SNR value greater than 0 dB OFDM system is properly synchronized.

For different value of offsets, simulation is confirms that the system gets exactly synchronized for positive SNR.


CARRIER FREQUENCY OFFSET ESTIMATION:
As we saw in the earlier chapters CFO is due to the mismatch of the RF oscillator in the transmitter and receiver side of the OFDM system.
In the figure 4.3 as SNR value increases, MSE of estimated CFO decreases under Rayleigh channel.
Figure 4.3 SNR Vs MSE for =0.0019
The following table gives estimated offset for SNR=20 dB.
Transmissions IEEE transactions on broadcasting, vol. 56, no. 4
Frequency offset
Estimated ffset(AWGN channel)
Estimated P
offset (Rayleigh channel)
0.0019
0.0019
0.0014
0.0029
0.0029
0.0027
0.0039
0.0039
0.0040
0.0049
0.0049
0.0047
0.0059
0.0049
0.0055
0.0069
0.0069
0.0067
0.0079
0.0079
0.0083
0.0089
0.0089
0.0084
age No: 345362
It is observed that the offset is possible to estimate exactly while the channel is AWGN. If the noise increases or channel becomes highly faded, the error in the estimate becomes larger beyond the values shown in the table 4.3.

CONCLUSION
Thus in this project OFDM system is simulated based on the selected specifications and receiver algorithm was verified with the help of MATLAB by considering the receiver design anomalies like timing offset, Carrier Frequency Offset, phase offset. Timing synchronization is done with the help of training sequences inserted between the OFDM symbols. Carrier frequency offset is cancelled by means Maximum Likelihood Estimate (MLE) and Phase offset is estimated and corrected with the help of training sequence
REFERENCES
[1]. Zhang RongtaoXie Xianzhong Wang Xi(2006) Synchronization Algorithm for OFDM based on Training Cyclic Prefix International Conference on Communication Technology ICCT, pp.1 – 4 [2]. Schmidl T M, Cox D C. (1997) Robust frequency and timing synchronization for OFDM. – IEEE Transactions on Communications, Volume 45 No.12 pp.1613 – 1621 [3]. Van de Beek J J, Sandell M, Boriesson P (1997) ML estimation of time and frequency offset in OFDM Systems – IEEE Transaction on SignalProcessing, volume 45 No.7 pp.1800 1805[4]. Lee. J, Lou, H and Toumpakaris, D. (Oct. 2004)Maximum likelihood estimation of time and frequency offset for OFDM systems – Electronics Letters.
Volume 40, Issue 22, 28 Page(s):1428 1429
[5]. MicheleMorelli, Member IEEE, C.C. Jay Kuo, Fellow IEEE, and [6]. Hung NguyenLe and Tho LeNgoc (2010) PilotAided Joint CFO and DoublySelective Channel Estimation for OFDM