Bassiouny M. Sallam

A new single carrier FDMA system based on the discrete cosine transform

In this paper, a new single carrier frequency division multiple access (SC-FDMA) system based on the discrete cosine transform (DCT) for uplink wireless transmissions, is introduced. The time domain expressions of the DCT SC-FDMA signals are derived. The peak to average power ratio (PAPR) of the DCT SC-FDMA signals is compared with that of the discrete Fourier transform (DFT) SC-FDMA and orthogonal frequency division multiple access (OFDMA) signals. Simulation results show that the proposed DCT SC-FDMA system provides a better bit error rate (BER) performance than the DFT SC-FDMA and the OFDMA systems. In addition, it is found that the PAPR of the DCT SC-FDMA signals is lower than that of OFDMA signals.

A hybrid algorithm for fingerprint enhancement

Quality enhancement of fingerprint images is important for a good performance of Automatic Fingerprint Identification System (AFIS). In this paper, a hybrid fingerprint enhancement algorithm is presented. This algorithm is based on morphological enhancement in the additive wavelet transform domain and Wave Atom denoising. The performance of the proposed algorithm has been evaluated on a set of images. The results are compared with the results obtained using morphological enhancement, only. Our proposed algorithm has given a better performance than using morphological enhancement, only.

A new approach for fingerprint recognition based on mel frequency cepstral coefficients

This paper presents a new fingerprint identification method based on mel frequency cepstral coefficients (MFCCs). This method is based on the transformation of the fingerprint images into a 1-D signals and the extraction of the MFCCs from these signals. Feature matching is performed in the proposed method using neural networks. Wavelet transform of the 1-D fingerprint signals can be used for extraction of much more MFCCs to assist in the recognition process. Also wavelet denoising can be used to reduce noise. Experimental results show that the proposed method is robust in the presence of noise.

Carrier frequency offsets problem in DCT-SC-FDMA system: investigation and compensation

Single-carrier frequency division multiple access (SC-FDMA) is one well-known scheme, which has recently become a preferred choice for uplink channels. In this system, the carrier frequency offsets (CFOs) disrupt the orthogonality between subcarriers and give rise to inter-carrier interference (ICI), and multiple access interference (MAI) among users. In this paper, firstly, the impact of the CFOs on the performance of the discrete cosine transform (DCT) SC-FDMA (DCT SC-FDMA) system is investigated. Then, a new low-complexity joint equalization and CFOs compensation scheme is proposed to cancel the interference in frequency domain. It is called minimum mean square error (MMSE) equalizer. A hybrid scheme comprising the proposed MMSE scheme and a parallel interference cancellation (PIC) (MMSE+PIC) is also suggested and investigated to further enhance the performance of the interleaved DCT-SC-FDMA. From the obtained simulation results, it is found that CFOs disrupt the orthogonality between the subcarriers in DCT-SC-FDMA systems and degrade the bit error rate (BER) performance. The proposed compensation schemes are found to be able to enhance the system performance, even in the presence of the estimation errors.

Complex Envelope Second-Order Statistics in High-Altitude Platforms Communication Channels

High-altitude platforms are one of the most promising alternative infrastructures for realizing next generation high data rate wireless networks. This paper presents a three-dimensional (3-D) scattering model for land mobile stratospheric multipath-fading channel with its complex faded envelope. From the scattering model and the complex envelope second-order statistics are derived for a 3-D non-isotropic scattering environment. When we discuss on the second-order statistics we refer to the level crossing rate and the average fade duration, whichare two main parameters in describing the fading severity over time and are very important in assess system characteristics such as hand off, velocities of the transmitter and receiver and fading rate. Numerical calculations have been carried out to demonstrate theoretical derivations and the utility of the proposed model.

Utilization of discrete transforms to conquer the problems of multi-tone systems

Abstract This paper presents a new implementation of discrete multi-tone (DMT) systems based on different discrete transforms that include the discrete sine transform (DST), discrete cosine transform (DCT), and discrete wavelet transform (DWT). The implementation also considers time-domain equalization to mitigate channel distortion. Compared to the fast Fourier transform discrete multi-tone (FFT-DMT) system, the proposed implementations have an advantage in that their energy-compaction property helps in reducing the channel effects. The performance of the DST-DMT, DCT-DMT, DWT-DMT, and FFT-DMT systems, employing a time-domain equalizer (TEQ), is investigated in the paper. It has been demonstrated by computer simulations that the proposed implementations outperform the FFT-DMT system and that the utilization of the TEQ can lead to higher bit rates

An Efficient Transceiver Scheme for SC-FDMA Systems Based on Discrete Wavelet Transform and Discrete Cosine Transform

Abstract In this paper, the discrete cosine transform (DCT) is utilized for single carrier frequency division multiple access (SC-FDMA) transmission. Firstly, an improved DCT-based 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.

Sensitivity of automatic speaker identification to SVD digital audio watermarking

This paper proposes the utilization of SVD digital audio watermarking to increase the security of automatic speaker identification (ASI) systems and presents a study for the effect of watermarking on the ASI system performance. The SVD audio watermarking algorithm can be implemented on audio signals in time domain or in another appropriate transform domain and can be applied to the audio signal as a whole or on a segment-by-segment basis. The speaker recognition system works by generating a database of speaker’s features using the MFCCs and polynomial shape coefficients extracted from each speaker after they are lexicographically ordered into 1-D signals. A matching process is performed for any new speaker to determine if he is belonging to the database or not, using a trained neural network. Experimental results show that the SVD audio watermarking doesn’t degrade the ASI system performance severely. So, it can be used with ASI to increase security. Also, it was shown the segment by segment watermarking in the time domain achieves the highest detectability of the watermark. So, we can say that it is recommended to use SVD segment by segment audio watermarking with ASI systems implementing features extracted from the DCT or the DWT.

DCT assisted speaker identification in the presence of noise and channel degradation

This paper presents a robust speaker identification method from degraded speech signals. This proposed method depends on the Mel-frequency cepstral coefficients (MFCCs) for feature extraction from the degraded speech and its discrete cosine transform (DCT). It is known that the MFCCs based speech recognition methods are not robust enough in the presence of noise and channel degradation. So, the feature extraction from the DCT of the signal will assist in achieving a higher recognition rate. The artificial neural network (ANN) classification technique is used in the proposed method. The comparison between the proposed method and the method using the MFCCs only for feature extraction from noisy speech signals and telephone-like degraded signals shows that the proposed method improves the recognition rate in the presence of noise or degradation.