Performance Evaluation of COFDM in Time Varying Environment

Transcription

1 International Journal of Electronics and Computer Science Engineering 294 Available Online at ISSN: Performance Evaluation of COFDM in Time Varying Environment 1 Karan Singh Gaur, 2 Monika Rawat, 3 Javed Ashraf 1 MTech Student, Alfalah School of Engineering & Technology Faridabad, Haryana, India 2 Asst. Prof.ECE, Rawal Institution Faridabad, Haryana, India 3 Asso. Prof.ECE, Alfalah School of Engineering & Technology Faridabad, Haryana, India - 1 karansinghgaur@gmail.com, 2 monikarawat53@yahoo.com, 3 jashraf.jmi@gmail.com, Abstract: In this Paper, a simulation of COFDM (Coded OFDM) over Multipath Fading channel, using R-S (15/11, Double error correcting) Code is done. Coherent QPSK is used to modulate the data and a training based channel estimator is implemented. In the present work it is observed the performance of RS code and chooses the effective parameters in the AWGN Channel that can improve COFDM system. Evaluation of Symbol Error Rate (SER) performance for R-S code as a function of code rate and block size can be tested.this testing can be applied to single carrier system with AWGN channel model using coherent Quadrature phase shift keying modulation (QPSK) technique. A new scheme may evaluate and compare all results with conventional performances for every step, and consequently to clear out the improvements stem from applying R-S codes. SER performance over AWGN channels is done respectively. Key Words: OFDM, COFDM, AWGN, SNR. 1-INTRODUCTION The name OFDM is derived from the fact that the digital data is sent using many carriers, each of a different frequency (Frequency Division Multiplexing) and these carriers are orthogonal to each other, hence Orthogonal Frequency Division Multiplexing [1]. It is a modulation scheme that allows digital data to be efficiently and reliably transmitted over a radio channel, even in multi-path environments. OFDM transmits data by using a large number of narrow bandwidth carriers. These carriers are regularly spaced in frequency, forming a block of spectrum. The next generation wireless communications systems need to be of a higher standard in order to provide the customers with the multitude of high quality services they demand Coded Orthogonal Frequency Division Multiplexing (COFDM) has been successfully used in terrestrial digital video broadcasting and showed it is a strong candidate for the modulation technique of future wireless systems. This Paper is concerned with how well COFDM performs when data is transmitted over an Additive White Gaussian Noise (AWGN) channel using Reed Solomon (FEC Codes), double error correcting code as well as channel estimation techniques. In order to investigate this, a simulation model is created and implemented using MATLAB. The COFDM signal was transmitted over AWGN channel for various ratio of symbol energy to noise power spectral density (Es/No) values. To evaluate the performance, for each Es/No level, the received signal is demodulated and the received data is compared to the original information. At the transmission channel the data is subjected to Additive White Gaussian Noise (AWGN) with the following parameters: - Mode is Signal to Noise Vector ( Es / No ), Es / No is Varied according to the different types of modulation techniques used. In put Signal Power in watts is (2.8e-6) in the complex signals, the AWGN Channel block relates, Es / No following: Where: - Es = Signal energy in joules Es / No = SNR( T sym/tsamp) (1) Es / No = Eb / No + 10 Log10( k) (2)

2 Performance Evaluation of COFDM in Time Varying Environment 295 Eb = Bit energy in joules No = Noise power spectral density (watts/hz) Tsym = is the symbol period parameters of the block in Es/No mode K = is the number of information bits per input symbol Tsamp = is the inherited sample time of the block, in seconds Simulink Modal of COFDM 1.2. Description of Simulink Modal: Figure 1 Simulink modal of COFDM In This Modal, the Bernoulli Binary Generator block generates random binary numbers using a Bernoulli distribution. The Bernoulli distribution with parameter p produces zero with probability p and one with probability 1- p. the random data of Bernoulli distribution is fed to the Binary-Input RS Encoder block which creates a Reed Solomon code with message length K and codeword length N. The input and output are binary-valued signals that represent messages and code words, respectively. The QPSK modulation scheme is a mapping of data words to a real (In phase) and imaginary (Quadrature) constellation, also known as an IQ constellation. For coherent modulation schemes estimation of the wideband OFDM channel consisting of large number of subcarriers is important for receiver equalization and data detection. Specifically when the mobility of the receivers is high (high Doppler channels) channel estimation becomes a challenging task. The conventional channel estimation techniques for OFDM use known symbols or pilots. In these techniques pilots and information symbols are multiplexed in time and/or frequency. Wiener filtering, we propose combining separable Wiener filters with superimposed training. Since the performance of optimal time-frequency sample selection scheme as well as channel

3 IJECSE,Volume1,Number 2 Karan Singh Gaur et al. 296 estimation scheme depends on the channel s fading statistics (Doppler frequency and delay spread), an analysis is presented to study the sensitivity of the proposed schemes to statistical mismatches Case 1: Absence of AWGN 2. SIMULATION RESULTS Figure 1 shows the power spectrum of COFDM without AWGN Channel. Some distortion is unavoidable and causes the generation of inter modulation products that appear as outgrowths on the transmitted signal (ideal signal would be rectangular in shape) this widening of the signal is often referred to as spectral re-growth. Spectral regrowth is visible on either side of the transmitted signal using a spectrum analyzer. Figure 2 COFDM Transmitted and Receiver Power Spectrum Figure 2 shows that the received COFDM power spectrum is exact in rectangular in shape because there is no distortion in the channel. As shown in figure 1 all the side lobes are removed as the ideal case. Figure 3 Constellation Diagram OF 4QPSK before and after Channel Estimation

4 Performance Evaluation of COFDM in Time Varying Environment 297 Figure 4 COFDM Transmitted and Received Signal Real Part and Imaginary Part Figure 4 shows the real and imaginary part of the transmitted and received signal. It clearly shows that the transmitted and received pictures are exactly same. As shown in figure 3 we conclude that the constellation diagram for transmitter and receiver is exactly same. We will assume this result for the base of other comparison as we include the AWGN Channel Case II: Including AWGN Channel Figure 5 Simulink Model Considering Only AWGN Channel

5 IJECSE,Volume1,Number 2 Karan Singh Gaur et al. 298 Figure. 6 Transmitted and received Signal real and imaginary part-considering AWGN Channel In case II, if we compare the real and imaginary part of the transmitted and received signal then we find that they are exactly same, hence we conclude that the AWGN channel does not interfere to the real and imaginary part of the signal. Figure 7 COFDM Transmitted and received power Spectrum-Considering AWGN Channel Figure 8 Constellation Diagram OF 4QPSK before and after Channel Estimation Considering AWGN Channel Figure 5 show that there is no Symbol error when we consider AWGN channel. Figure 8 shows the constellation diagram before and after channel estimation. As Shown in Figure 7 the received power spectrum is almost rectangular in shape. As there is only Gaussian noise in the channel and AWGN channel adds White Gaussian noise only to the signal passes through it.

6 Performance Evaluation of COFDM in Time Varying Environment Case I: Es/No (db) = EFFECT OF DIFFERENT E S /N 0 (DB) IN AWGN CHANNEL Figure.9 Constellation Diagram and Power spectrum Diagram of Transmitter and Receiver considering AWGN channel when Es/No (db) = Case II: Es/No (db) = 20 Figure.10 Constellation Diagram and Power spectrum Diagram of Transmitter and Receiver considering AWGN channel when Es/No (db) = Case III: Es/No (db) =25 Figure11 Constellation Diagram and Power spectrum Diagram of Transmitter and Receiver considering AWGN channel when Es/No (db) = Case IV: Es/No (db) =30 Figure 12 Constellation Diagram and Power spectrum Diagram of Transmitter and Receiver considering AWGN channel when Es/No (db) =30

7 IJECSE,Volume1,Number 2 Karan Singh Gaur et al Case V: Es/No (db) =28 Figure 13 Constellation Diagram and Power spectrum Diagram of Transmitter and Receiver considering AWGN channel when Es/No (db) =28 Above picture clearly shows that the best suited Es/No (db) is 28. It illustrates that how signal to noise ratio effects on the power spectrum of the signal. It is clear that as the SNR is increased the received constellation gets less affected by the noise; hence there will be fewer errors. However, for low values of SNR we have ISI introduced by the noise at the receiver side. 4. CONCLUSION We have successfully implemented Coded OFDM over AWGN Channel. We analyzed the performance of Reed Solomon coding for Double error Correcting. Errors occurring in pairs of adjacent symbols are not uncommon in certain communication schemes. This means, codeword entering a decoder have errors mostly occurring in pairs of symbols. Here we studied the performance of R-S coding on the behavior of AWGN channel. We have taken different graph for the different parameters of the AWGN Channel. First of all we have send the data in the absence of any channel interference as a ideal channel and taken the result. Then we have considered only AWGN channel and studied how AWGN channel add the noise to the channel. Then we have plotted constellation diagram, power spectrum, real and imaginary part of the transmitted and received signal respectively. We compared all the data and studied that how the signal behaves in the Multipath Fading environment. We have tested the performance of model for the different Doppler shift of Multipath and tested the model over the different signal to noise ratio and studied that how the signal behaves for different Es/No of AWGN channel. REFERENCE [1] Gordon L. Stuber, Fellow, IEE John R. Barry, Broad Band MIMO-OFDM Wireless Communications, Proceeding of the IEEE, VOL. 92, No. 2, February [2] C. GONZALEZ-CONCEJERO, V RODELLAR, A Portable Hardware Design of FFT Algorithm, Latin American Applied research, 37:79-82, [3] Mohamed Ahmed Mohamedian, Iman Abuel Maaly A/ Elrahman and lzz Eldin Mahamed Osman, Performance of Orthogonal Frequency Division Multiplexing (OFDM) under the effect of Wireless Transmission System Drawback, Sudan Engineering Society Journal, September 2007, Volume 52 No. 49. [4] Hamood Shehab & Wihad Ismail, The Development & Implementation of Reed Solomon Codes for OFDM using Software-Defined Radio Platform, International Journal of Computer Science, Vol. No. 1, January-June 20101, pp [5] T. J. Richardson, M. A. Shokrollahi, and R. L. Urbanke, Design of Capacity-approaching Irregular Low-density Parity Check Codes, IEEE Trans. on Information Theory, 47, pp [6] Botaro Hirosaki, An Orthogonal Multiplexed QAM System Using the Discrete Fourier Transform, IEEE Transaction on Communication, Vol. COM- 29, July [7] A. Peled and A. Ruiz, Frequency domain data transmission using reduced computational complexity algorithms, Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '80, vol. 5, pp , Apr [8] L. J. Cimini, Analysis and simulation of a digital mobile channel using orthogonal [9] H. Schulze, and C. Luders, Theory and Applications of OFDM and CDMA Wideband Wireless Communications, John Wily & Sons, Ltd, 2005 [10] Li-Chung Chnag, James V. Krognier, Power Optimization of QAM system with Data Predistortion, National Taiban University of science & Technology, Taiwan

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