# A Comparative performance analysis of CFO Estimation in OFDM Systems for Urban, Rural and Rayleigh area using CP and Moose Technique

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4 victim of CFO is 2πε. Therefore, the amount of CFO can be found by the multiplication of OFDM symbol (CFO affected) with the CP and after that taking their phase angle measurements, as show below *, -, -+ (6) In order to reduce the noise effect, its average can be taken over the samples in a CP interval as {, -, -} (7) The above equation can estimate CFO in the range of [- 0.5, +0.5]. Therefore, CP results CFO estimation in the range ε 0.5. Hence, this technique is useful for the estimation of Fractional CFO. The drawback of this technique is that it does not estimate the integer offset. using equation [Richard Van Nee et al, 2000], the phase difference between CP and the corresponding rear part of an OFDM symbol. Second, using equation (8) OFDM parameters used in the simulation are given in the table below. Table1. Simulation Parameters Parameter Estimation technique Channel model Value Cyclic prefix and Moose Urban and Rural Number of Subcarrier 512 Normalized CFO().15 FFT size 256 Sampling time(ts) Doppler frequency(fd) Modulation technique SNR range 1/20Mhz 200Hz QAM 0-30 db 3.2 Symbol based Estimation Method The basis of this technique, proposed by P.H. Moose is that same data frame is repeated and the phase value of each carrier between consecutive symbols is compared. If two identical training symbols are transmitted consecutively, the corresponding signals with CFO of ε are related with each other as follows., -, -, -, - (8) In this estimation mean square error can be calculated as. Where is the ratio of the signal to noise for the received signals, and N is the number of subcarriers (SCs). According to the paper, the limit of accurate estimation (for acquisition range) for this algorithm Acquisition Range (.15) therefore the acquisition range for subcarrier spacing is between -0.5 and 0.5, which is smaller than the value that is in the IEEE802.11a. When acquisition range goes towards the 0.5, may due to the noise and the discontinuity of the arctangent, jump to -0.5 when this occurs the estimate is no longer unbiased and in practice, it becomes useless. This estimation for the small values of CFO is conditionally unbiased. However, the big weakness for suggested algorithm in Moose s paper is its dependency to the starting point; therefore the algorithm needs to know the start point of the OFDM symbol. 4. Simulation parameter and result discussion MATLAB simulator tool are used to estimate the Carrier frequency effect on OFDM system by cyclic prefix and Moose method. To compare CFO estimation techniques, two equations are simulated. First, by The effect of carrier frequency offset on OFDM system can be analyzed and estimate by using cyclic prefix and Moose estimation method for Urban, Rural and Rayleigh model on the basis of mean square error and SNR through MATLAB simulation software. Effect of Frequency offset proposed scheme can be easily checked by complementary cumulative distribution function (CCDF) plot. In this paper, we are using 512 numbers of sub-carrier, normalized CFO.15, SNR range 0-30db and modulation technique QPSK to analyzed the effect of frequency offset for Urban, Rural and Rayleigh area. In Fig.4.1, we have seen that CCDF plot between MSE versus SNR for urban area. From figure we can simply estimate that Mean square error at 21 db SNR is approx for Moose method whereas by cyclic prefix method MSE is approx Fig 4.1 CCDF plot between CFO mean square error and SNR for urban area In Fig.4.2, we have seen that CCDF plot between MSE versus SNR for rural area. From figure we can simply analyzed that CFO estimation performance of Moose method is more efficient and reliable than cyclic prefix technique International Journal of Current Engineering and Technology, Vol.5, No.4 (Aug 2015)

5 Conclusion Fig 4.2 CCDF plot between CFO mean square error and SNR for rural area In Fig.4.3, we have seen that CCDF plot between MSE versus SNR for rayleigh area. From figure we can simply estimate that Mean square error at low SNR, moose method is better but at 25 db SNR, estimation performance of Moose and cyclic prefix is mostly same. Fig 4.3 CCDF plot between CFO mean square error and SNR for Rayleigh area After investigating the result we can simply state that overall estimation performance of Moose method for Urban, Rural and Rayleigh is better and effective than cyclic prefix method. In this paper, we investigated the effects of CFO in OFDM system. From mathematical analysis and simulation results we see that CFO introduces Inter- Carrier Interference (ICI) which destroys the orthogonality of subcarriers. Two CFO estimation schemes, i.e., the CP based scheme and frequency domain based Moose scheme have also been applied to the OFDM systems. After observing the Simulation results we can conclude that overall CFO estimation performance of Frequency Domain scheme (Moose method) for urban,rural and Rayleigh model has better than time domain CP based method in terms of normalized MSE over SNR. References A.C.Bingam (May 1990) Multicarrier modulation for data transmission: An idea whose time has come. IEEE Commun. Mag., 28(5):5-14 Nee, R.V. and R.Prasad (January 2000), OFDM for Wireless Multimedia Communications, Artech House Publishers, Norwood, MA. IEEE (2004) IEEE Standard for Local and metropolitan area networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems W. J. Zhang, Y. F. Guan, W. Q. Liang, D. Z. He, F. Ju, and J. Sun (Mar. 2007), An introduction of the Chinese DTTB standard and Analysis of the PN595working modes, IEEE Trans. Broadcasting, vol. 53, no. 1, pp B. Sathish Kumar, K.R. Shankar Kumar, and R.Radhakrishnan (2009), An Efficient Inter Carrier Interference Cancellation Schemes for OFDM Systems, IJCSIS, Vol. 6, No. 3. Yong Soo Cho, J. Kim, W. Young Yang, and Chung G (2010) Kang, MIMO-OFDM Wireless Communications with MATLAB (John Wiley & Sons (Asia), Singapore) Richard Van Nee, Ramjee Prasad (2000), OFDM for Wireless Multimedia Communications, (Artech House, Boston, London) 2946 International Journal of Current Engineering and Technology, Vol.5, No.4 (Aug 2015)

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