In this paper, the discrete cosine transform (DCT) is utilized for single carrier frequency division multiple access (SC-FDMA) transmission. Firstly, an improved DCTbased SC-FDMA (DCT SC-FDMA) system is introduced. Then, the paper presents a new transceiver architecture design for the uplink SC-FDMA system that implements a cosine basis function or a complex exponential Fourier basis function. The proposed architecture uses the discrete wavelet transform and a hybrid companding and clipping method for peak-to-average power ratio (PAPR) reduction. From the simulation results, it is shown that the DCT SC-FDMA system achieves a superior bit error rate (BER) performance than that of the discrete Fourier transform based SC-FDMA (DFT SC-FDMA) system. The results also show that the proposed wavelet based transceiver architectures for the DFT SC-FDMA system and the DCT SC-FDMA system can provide a better BER performance and a lower PAPR than the conventional DFT SC-FDMA system.

In this paper, the impact of carrier frequency offset (CFO) and CFO compensation on the transmission of encrypted images with different orthogonal frequency division multiplexing (OFDM) versions is studied. The investigated OFDM versions are the fast Fourier transform OFDM, the discrete cosine transform OFDM, and the discrete wavelet transform OFDM. A comparison between four encryption algorithms with images transmitted through different OFDM versions is presented. These algorithms are data encryption standard, advanced encryption standard, RC6, and chaotic Baker map. This comparison aims to select the most appropriate version of OFDM, and the most suitable image encryption algorithm for efficient image transmission. In the simulation experiments, the peak signal-to-noise ratio at the receiver is used as an evaluation metric for the decrypted image quality.

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Automatic Digital Modulation Recognition (ADMR) is becoming an interesting problem with various civil and military applications. In this paper, an ADMR algorithm in Multi-Carrier Code Division Multiple Access (MC-CDMA) systems using Discrete Transforms (DTs) and Mel-Frequency Cepstral Coefficients (MFCCs) is proposed. This algorithm uses various DT techniques such as the Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) with MFCCs to extract features from the modulated signal and a Support Vector Machine (SVM) to classify the modulation orders. The proposed algorithm avoids over fitting and local optimal problems that appear in Artificial Neural Networks (ANNs). Simulation results shows the classifier is capable of recognizing the modulation scheme with high accuracy up to 90% - 100% using DWT, DCT and DST for some modulation schemes over a wide Signal-to-Noise Ratio (SNR) range in the presence of Additive White Gaussian Noise (AWGN) and Rayleigh fading channel, particularly at a low Signal-to-Noise ratios (SNRs).

Speech enhancement is a very important preprocessing step in various speech processing applications such as speech recognition, speaker identification, speech coding, and speech synthesis. In this paper, we focus on speech enhancement prior to speaker identification, because the degradations of the speech signals may cause difficulties in hearing, understanding, and speaker recognition. The paper presents a hybrid speech enhancement method based on empirical mode decomposition combined with spectral subtraction to improve the quality of speech signals prior to speaker identification. Simulation results show an improvement in speaker recognition rates with the proposed speech enhancement method as a pre-processing step.