Performance Comparison of Ofdm System Based on Dmwtcs, Dwt, and Fft Using Qam Modulation Technique

Orthogonal frequency division multiplexing (OFDM) is a popular modulation technique that is widely utilized in many wireless communication systems. Traditional OFDM based on fast Fourier transform (FFT) involves the use of a rectangular window; consequently, high side lobes are created. Hence, OFDM based on discrete multiwavelet critical sampling transform (DMWTCS) is proposed in this paper. DMWTCS is more flexible in terms of data rate and has much lower side lobes than OFDM based on FFT. Given that the multiwavelet can overlap both in time and frequency domains and eliminates the need for a cyclic prefix, OFDM based on DMWTCS has higher bandwidth efficiency than OFDM based on FFT. In this paper, the performance of OFDM based on DMWTCS is compared with that of traditional OFDM based on FFT and OFDM based on discrete wavelet transform (DWT) through the use of various quadrature amplitude modulation (QAM) constellation points, such as 4-QAM, 8-QAM, and 16-QAM. These systems are examined in additive white Gaussian noise (AWGN), flat fading, and frequency-selective fading channels through MATLAB software. Simulation results reveal that the performance of the proposed system is better than that of the other two systems in all types of channels. Keyword: OFDM, multiwavelet transform, critical sampling processing, QAM. INTRODUCTION The demand for high-speed mobile wireless communication is rapidly increasing. Orthogonal frequency division multiplexing (OFDM) technology promises to be a key technique to achieve high data capacity and spectral efficiency requirements for wireless communication systems in the near future. OFDM is a special form of multicarrier transmission where all subcarriers are orthogonal to one another [1]. The principle of OFDM involves splitting a wideband signal at a high symbol rate into several low-rate signals by dividing the input data stream into parallel sub-streams, with each stream being modulated on a set of sub-channels at different orthogonal carrier frequencies [2]. A frequency selective wideband channel is transformed into a group of nonselective narrowband channels in this technique; thus, large delay spreads are prevented by preserving orthogonality in the frequency domain [3]. OFDM is widely applied in different wireless communication standards, such as digital audio/video broadcasting, ETS1 HIPERLAN/2 standard, IEEE 802.11a standard for wireless local area networks (WLAN), and IEEE 802.16a standard for wireless metropolitan area networks (WMAN), because of its robustness to multipath fading and its capability to provide high bandwidth efficiency and high data rate transmission [4, 5]. Fast Fourier transform (FFT) is utilized to reduce implementation complexity and satisfy the required orthogonality between subcarriers [6]. A significant disadvantage of FFT is that it involves the use of a rectangular window, which creates high side lobes and results in increased sensitivity of the OFDM system to inter-carrier interference (ICI) and narrowband interference (NBI). Moreover, the pulse shaping function utilized to modulate each subcarrier extends to infinity in the frequency domain. This condition degrades performance and creates high interference [7]. Intersymbol interference (ISI) and ICI can be eliminated by adding a cyclic prefix (CP) into each OFDM symbol, which is a copy of several samples from the end of the OFDM symbol, and appending them to the beginning of the OFDM symbol; however, spectrum efficiency would be reduced [7]. Studies conducted in recent years aimed to enhance the performance of the OFDM system by reducing ISI and ICI and improving spectrum efficiency by reducing bandwidth waste, which is produced by adding CP. These studies were performed by replacing FFT with other transform methods. The authors of [8] observed that ISI and ICI, which are caused by the loss of orthogonality among subcarriers, can be reduced in OFDM systems by replacing FFT with discrete wavelet transform (DWT). The authors of [9] investigated the performance of the OFDM system based on a wavelet with different families, such as Haar, Daubechies, biorthogonal, and reverse bi-orthogonal wavelets. They found that the Haar wavelet provides a very good platform for wireless communication with minimum bit error rate (BER), ISI, and peak average power ratio (PAPR). Furthermore, the authors of [10] reported that OFDM systems become flexible, robust to narrowband interference, and spectrally efficient by replacing FFT with discrete wavelet packet transform (DWPT). Reference [11] presented OFDM systems that employ VOL. 9, NO. 12, DECEMBER 2014 ISSN 1819-6608 ARPN Journal of Engineering and Applied Sciences ©2006-2014 Asian Research Publishing Network (ARPN). All rights reserved. www.arpnjournals.com 2824 slantlet transform (SLT) instead of FFT to reduce the level of interference and therefore improve the bandwidth efficiency of OFDM by removing the need for a guard interval (GI). Multiwavelet is a new concept proposed recently [12]. Multiwavelet, which is a natural extension of wavelet, is designed to be simultaneously symmetric, orthogonal, and have short supports with high approximation power, which cannot be achieved simultaneously by wavelet using only one scaling function [12]. The idea is to increase the number of scaling functions to raise the approximation power rather than use one scaling function. Multiwavelet enhances the performance of many wavelet applications, such as image coding and denoising [12, 13]. Given its features, multiwavelet is suitable for OFDM systems. In this study, discrete multiwavelet critical sampling transform (DMWTCS) is utilized for OFDM systems to achieve better BER performance than conventional OFDM using FFT and DWT. The main objective of this study is to compare the performance of OFDM based on DMWTCS with that of two other systems through the use of various quadrature amplitude modulation (QAM) constellation points in a wireless channel. The rest of this paper is organized as follows. A brief introduction of multiwavelet transform is presented in section 2. The proposed system for OFDM based on DMWTCS is presented in section 3. The simulation results are discussed in section 4, and the conclusions are presented in section 5. MULTIWAVELET TRANSFORM Multiwavelet has two or more scaling and wavelet functions, whereas wavelet has one scaling and one wavelet function. The multiwavelets studied to date consist of two scaling and two wavelet functions. Multiwavelet scaling and wavelet functions can be represented by the following equations [14]. ( ) 2 (2 ) k k t H t k   