Speech transmission with COFDM based on different discrete transforms

Recently, the multimedia and cellular technologies have spread dramatically. Therefore, the demand for digital information has increased. Speech compression is one of the most effective forms of communication. This paper presents three approaches for the transmission of compressed speech signals over convolutional Coded Orthogonal Frequency Division Multiplexing (COFDM) system with a chaotic interleavering technique. The speech signal has is compressed using the Set Partitioning In Hierarchical trees (SPIHT) algorithm, which is an improved version of EZW and which is characterized by a simple and effective method for further compression. For mitigation of the fading due to multipath wireless channels, this paper proposes a COFDM system based on fractional Fourier transform (FrFT), a COFDM system based on discrete Cosine transform (DCT), and a COFDM system based on discrete wavelet transform (DWT). The FrFT has the ability of solving the frequency offset problem, which causes the received frequency-domain sub-carriers to be shifted, and therefore, the orthogonality between subcarriers deteriorates even with equalization. The DCT has an advantage of increased computational speed as only real calculations are required. The DWT is spectrally efficient since it does not utilize cyclic prefix (CP). These systems have been designed under the assumption that corruptive background noises are absent. Therefore, denoising techniques, namely wavelet denoising and Wiener filtering methods are suggested at the receiver to achieve enhancement in the speech quality. The simulation experiments shows that the proposed COFDM–DWT with Wiener filtering at the receiver has a better trade-off between BER, spectral efficiency and signal distortion. Hence, the BER performance is improved with small bandwidth occupancy. Moreover, due to the denoising stage, the speech quality is improved to achieve good intelligibility.