Its request for matlab code for wavelet based ofdm transmitter

Introduction

Orthogonal Frequency Division Multiplexing (OFDM) is a multiple carrier modulation system. The transmission channel is divided into a subchannel number in which each subchannel is assigned to a subcarrier. Conventional OFDM systems use IFFT and FFT algorithms on the transmitter and receiver respectively to multiplex the signals and transmit them simultaneously over a number of subcarriers. The system uses guard intervals or cyclic prefixes (CP) so that the channel delay propagation becomes longer than the channel impulse response (Peled and Ruiz, 1980; Bahai and Saltsburg, 1999; Kalet, 1994; Beek Et al., 1999; Bingham, 1990, Nee and Prasad, 2000). The system must ensure that the cyclic prefix is a small fraction of the duration of the symbol per bearer (Beek et al., 1999, Steendam & Moeneclaey, 1999). The purpose of using the CP is to minimize interference between symbols (ISI). However, a CP reduces energy efficiency and data performance. The CP also has the disadvantage of reducing the spectral containment of the channels (Ahmed, 2000; Dilmirghani & Ghavami, 2007, 2008). Due to these problems, an alternative method is to use the wavelet transform to replace IFFT and FFT blocks (Ahmed, 2000; Dilmirghani and Ghavami, 2007, Akansu and Xueming, 1998). The wavelet transform is called the Discrete Wheretata Transform OFDM (DWT-OFDM). By using the transform, the spectral containment of the channels is better since they are not using CP (Ahmed, 2000; Dilmirghani & Ghavami, 2007, 2008). The illustration of the containment attributes of the upper wavelet subchannel has been described in detail by (Sandberg and Tzannes, 1995) as compared to Fourier. The wavelet transform also employs low-pass filter (LPF) and high pass filter (HPF) that function as quadrature mirror filters that satisfy the perfect reconstruction properties and orthonormal basis. It uses filter coefficients as approximate and detail in LPF and HPF respectively. The approximate coefficients are sometimes referred to as scale coefficients, while the detailed ones refer to wavelet coefficients (Abdullah et al., 2009, Weeks, 2007). In some literatures, these two filters are also called subband coding since the signals are divided into low and high frequency sub-signals, respectively. The purpose of this chapter is to show the simulation study of the use of Matrices Laboratory (MATLAB) in wavelet-based OFDM, in particular DWT OFDM as alternative substitutions for Fourier-based OFDM. MATLAB is preferred for this approach as it offers a very powerful matrix calculation with a wide range of enriched toolboxes and simulation tools. To the best of the authors' knowledge, there is no study on the descriptive procedures of simulations using MATLAB with respect to flexible transformed models in an OFDM system, especially when dealing with wavelet transformation. Therefore, this chapter is divided into three main sections: section 2 will explain the conventional FFT-OFDM, section 3 will describe in detail the models for the DWT-OFDM and section 4 will discuss the result of the bit error rate (BER) Platforms, DWT-OFDM versus FFTOFDM.