# Design and Implementation of OFDM System and Reduction of Inter-Carrier Interference at Different Variance

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2 systems exhibit a sensitivity to phase noise higher than single carrier modulations due to its long symbol period. Because carriers are kept very close to each other, OFDM is very sensitive to distortion that may remove the orthogonality between carriers. recipient will then see their signal better, the other signals will be clearly separated. Phase noise can cause several types of signal degradation that are usually very difficult to quantify analytically. When the modulation experiences phase noise, it encounters two problems: 1) a common phase rotation over all the carrier frequencies which rotate the entire signal space for a given OFDM symbol 2) inter-carrier interference due to the loss of orthogonality between subcarriers. Especially, the ICI seriously degrades system predominance because it may break down the orthogonality between subcarriers. 2. Orthogonal Frequency Division Multiplexing Orthogonal Frequency Division Multiplexing [5] is a technology related to Frequency Division Multiplexing. With it, many different signal scan be sent over the same medium, at the same time. Each signal uses a different basis function. By using the basis function given, the sender and Figure 2: An example o OFDM with 4 different signal shown in different colour 3. Orthogonality If two signals are said to be orthogonal then their dot product is zero. As the subcarriers are orthogonal then the spectrum of each subcarrier has a null at the center frequency of the other subcarriers in the system. It is as shown in the figure. OFDM Generation And Reception: An OFDM carrier signal is the sum of a number of orthogonal sub-carriers, with baseband data on each subcarrier being independently modulated commonly using some type ofquadrature amplitude modulation (QAM) or phase-shift keying (PSK). This composite baseband signal is typically used to modulate a main RF carrier. is a serial stream of binary digits. By inverse multiplexing, these are first demultiplexed into parallel streams, and each one mapped to a (possibly complex) symbol stream using some modulation constellation (QAM, PSK, etc.). Note that the Figure 3: Transmitter constellations may be different, so some streams may carry a higher bit-rate than others. An inverse FFT is computed on each set of symbols, giving a set of complex time-domain samples. These samples are then quadrature-mixed to passband in the standard way. The real and imaginary components are first converted to the analogue domain using digital-to-analogue converters (DACs); the analogue signals are then used to modulatecosine and sine waves at the carrier frequency,, respectively. These signals are then summed to give the transmission signal,. Paper ID:

3 The receiver picks up the signal, which is then quadrature-mixed down to baseband using cosine and sine waves at the carrier frequency. This also creates signals centered on, so low-pass filters are used to reject these. The baseband signals are then sampled and digitised using analog-to-digital converters (ADCs), and a forward FFT is used to convert back to the frequency domain. Figure 4: Receiver This returns parallel streams, each of which is converted to a binary stream using an appropriate symbol detector. These streams are then re-combined into a serial stream,, which is an estimate of the original binary stream at the transmitter. Figure 6: BER performance with ICI cancellation at phase noise variance=1 ICI Self Cancellation Methods It is seen that the difference between the ICI co-efficient of the two consecutive sub-carriers is very small. This makes the basis of ICI self cancellation. Here one data symbol is not modulated in to one sub-carrier, rather at least in to two consecutive sub-carriers. If the data symbol =a is modulated in to the 1st sub-carrier then =-a is modulated in to the 2nd sub-carrier. Hence the ICI generated between the two subcarriers almost mutually cancels each other. This method is suitable for multipath fading channels as here no channel estimation is required. Figure 7: BER performanc with ICI cancellation at phase noise variance=2 4. Conclusion In this paper we have calculated the BER and SNR at different phase noise variance from zero to 10 and we have seen that when the phase noise variance is increased BER and SNR performance is decreased as well as we calculated the BER at SNR=15 db and 20 db. The improved graph as bellow. Figure 8: BER performance with ICI cancellation at phase noise variance=3 Figure 5: BER performance with ICI cancellation at zero phase noise variance Figure 9: BER performance with ICI cancellation at phase noise variance=4 Paper ID:

4 Figure 10: BER performance with ICI cancellation at phase noise variance=5 Figure 13: BER performance with ICI cancellation at phase noise variance=8 Figure 11:BER performance with ICI cancellation at phase noise variance=6 Figure 14: BER performance with ICI cancellation at phase noise variance=9 Figure 12: BER performance with ICI cancellation at phase noise variance=7 Figure15: BER performance with ICI cancellation at phase noise variance=10 Figure 16: BER improvement graph at SNR =15db and 20 db Paper ID:

5 Reference International Journal of Science and Research (IJSR) [1] B. Senthil, R. Aravind,K.M.M. Prabhu An Enhanced Inter-carrier Interference Reduction Scheme for OFDM System with Phase Noise Received: 7 April 2012 / Revised: 3 August 2012 / Published online: 24 August 2012 [2] L. Yang, G. Ren, and Z. Qiu, A novel Doppler frequency offset estimation method for DVB-T system in HST environment, IEEE Trans. Broadcast., vol. 58, no. 1, pp , Mar [3] Alka Karla and Rajesh Kanna-A Survey of Intercarrier Interference Cancellation Schemes in OFDM System, The IUP Journal of Telecommunications, Vol. III, No. 1, 2011 [4] H.-C. Wu, X. Huang, Y. Wu, and X. Wang, Theoretical studies and efficient algorithm of semiblind ICI equalization for OFDM, IEEE Trans. Wireless Commun., vol. 7, no. 10, pp , Oct [5] X. Huang and H.-C.Wu, Robust and efficient intercarrier interference mitigation for OFDM systems in time-varying fading channels, IEEE Trans. Veh. Technol., vol. 56, no. 5, pp , Sep [6] N. C. Beaulieu and P. Tan, On the effects of receiver windowing on OFDM performance in the presence of carrier frequency offset, IEEE Trans. Wireless Commun., vol. 6, no. 1, pp , Jan [7] H.-C.Wu, Analysis and characterization of intercarrier and interblock interferences for wirelessmobileofdm systems, IEEE Trans. Broadcast.,vol. 52, no. 2, pp , Jun [8] S. R. Herlekar, C. Zhang,H.-C.Wu, A. Srivastava, and Y.Wu, OFDM performance analysis in the phase noise arising from the hot-carrier effect, IEEE Trans. Consum. Electron., vol. 52, no. 3, pp ,Aug [9] X. Wang, Y. Wu, J.-Y. Chouinard, and H.-C. Wu, On the design andperformance analysis of multisymbol encapsulated OFDM systems, IEEE Trans. Veh. Technol., vol. 55, no. 3, pp , May 2006 [10] M. Russell and G. L. Stüber, Interchannel interference analysis of OFDM in a mobile environment, in Proc. IEEE Veh. Technol. Conf.,Jul. 1995, vol. 2, pp Author Profile Er. Gaurav Verma has completed his B.Tech in Electronic and Communication Engineering from Marudhar Engineering College (MEC) Bikaner Rajasthan, INDIA in the year He is currently pursuing M.Tech in Electronic and Communication Engineering, JCDMCOE SIRSA. Paper ID:

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