Discrete Wavelet Transform Based OFDM System using Convolutional Encoding

Abstract

The rapidly growing technology has made it possible for the communication systems to transfer data almost everywhere on this planet. But the limited bandwidth allocated to a large number of users restricts the bandwidth availability to the users. This scenario creates a technological challenge to develop the data transmission schemes which are bandwidth efficient. Multicarrier modulation is such a scheme that transmits the data by dividing the serial high data rate streams into a number of low data rate parallel data streams. Orthogonal Frequency Division Multiplexing (OFDM) is a kind of multi-carrier modulation, which divides the available spectrum into a number of parallel subcarriers and each subcarrier is then modulated by a low rate data stream at different carrier frequency. The conventional OFDM systems make use of IFFT and FFT at the transmitter and receiver respectively but DWT-OFDM is an alternative approach to this conventional FFT based OFDM system. Discrete Wavelet Transform (DWT) is broadly considered as an efficient approach to replace FFT in the conventional OFDM systems due to its better time-frequency localization, bit error rate improvement, interference minimization, improvement in bandwidth efficiency and many more advantages. Moreover, Convolutional codes are used in DWT based OFDM system which improves the bit error rate performance of the system. In communication systems, when the signal is transmitted over the channel, noise and unwanted interferences are introduced which leads to the distortion of transmitted signal. Hence, error control coding techniques are used to mitigate the effect of such channel distortions. The original data sequence is appended with redundant bits to increase the reliability of the system by adding cyclic prefix; which also answers the problem of ISI. DWT is an effective tool to study the signals in time frequency joint domain as it is capable of providing simultaneous information about time and frequency, thus gives the time frequency representation of signal. Wavelet based OFDM is employed in order to remove the use of cyclic prefix which decreases the bandwidth wastage and the transmission power is also reduced. The BER performance of the OFDM system had been significantly improved by 4 dB at BER of 10-2.9 when DWT was used in place of conventional FFT method. Afterwards, all the wavelets were compared to find the optimum wavelet among all. The results achieved had shown that the wavelet „bior5.5‟ outperformed all the other wavelets as well as FFT-OFDM system because it makes use of two wavelets, one for decomposition and the other for reconstruction instead of the single one. Finally, the performance of DWT OFDM system using Convolutional codes and without encoding is compared under AWGN as well as Rayleigh channel. The results show that there is an improvement of 2.5 dB at BER of 10-2.92 when AWGN channel is used. In case of Rayleigh channel, an improvement of 3.5 dB has been achieved at BER of 10-4.9. It is because the Convolutional encoding is very effective in removing the burst errors and distortions introduced by the channel. Moreover, the BER performance of a system is affected by the outage probability which occurs when the required data rate is not supported by the specific channel due to variable SNR. Convolutional encoding reduces the outage probability at higher SNR. Thus, DWT based OFDM with encoding performs significantly better at higher SNR.