Waleed Eid Abd Elrahman Alhanafy

N. F. Soliman, E. S.Hassan, A. A. Shaalan, M. M. Fouad, S. E. El-Khamy, Y. Albagory, M. A. M. El-Bendary, E.-S. M. El-Rabaie, M. I. Dessouky, S. A. El-Dolil, S. A. Alshebeili, and F. E. Abd El-Samie

01/08/2018

In this paper, a proposed method for Peak-to-Average Power Ratio (PAPR) reduction of Orthogonal Frequency Division Multiplexing (OFDM) signals based on discrete transforms is presented for robust image communication. One of the discrete transforms such as discrete wavelet transform, discrete cosine transform, or discrete sine transform is applied to modify the OFDM signal at the output of the inverse fast Fourier transform stage. We first present the proposed OFDM system model with trigonometric transforms for PAPR reduction. Trigonometric transforms improve the performance of the OFDM system, and reduce the PAPR of the OFDM signal. Then, this scheme has been utilized for progressive image transmission using low-density parity-check coded OFDM over frequency-selective fading channels. The set partitioning in hierarchical trees algorithm is used for source coding of the images to be transmitted. The proposed scheme effectively resists the fading impact of frequency-selective fading channels using simple frequency-domain equalization. Simulation experiments are performed for a variety of multipath fading channels. We also propose a chaotic interleaving scheme based on the 2-D chaotic Baker map for PAPR reduction of OFDM signals. The distinctive feature of this scheme is that the transmitted signal has less correlation between samples, and hence the PAPR is minimized.

Waleed Eid Abd Elrahman Alhanafy

Najib A. Odhah, Emad S. Hassan, Mohamad Abdelnaby, Moawad I. Dessouky, Saleh A. Alshebeili, and Fathi E. Abd El-Samie

01/01/2018

This paper presents adaptive per-spatial stream power allocation algorithms for Single User Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (SU MIMO-OFDM) systems. Three efficient and low-complexity Greedy Power Allocation (GPA) algorithms are proposed to maximize the throughput and spectral efficiency of the SU MIMO-OFDM systems. Firstly, the low-complexity pre-coded GPA algorithms are developed for the MIMO systems. The spatial sub-channels are created by applying the so-called Singular Value Decomposition (SVD) technique on the MIMO channel matrix, and then the Pre-GPA algorithms are applied to exploit the multi-path and spatial diversities. Secondly, the spatial and frequency diversities are exploited by adaptively allocating the system sub-carriers to the spatial sub-channels followed by Per-Spatial GPA (PSGPA). Finally, spatial multiplexing-based GPA algorithms are proposed to optimize the spectral efficiency of the SU MIMO-OFDM system. An optimal two-dimensional Spatial-Frequency GPA (SFGPA) algorithm is proposed to efficiently improve the average system spectral efficiency. The high computational complexity of the optimal SFGPA solution is simplified by proposing a low-complexity Per-Spatial GPA with Excess Power Moving down (PSGPA-EPMd) algorithm, which moves the per-spatial excess power downwards to enhance the spectral efficiency of the spatial multiplexing-based SU MIMO-OFDM systems. The proposed algorithms achieve better spectral efficiency and maximize the throughput in comparison with conventional algorithms.

Waleed Eid Abd Elrahman Alhanafy

Yasser M. Abd El-Hameed, Adel Saleeb, Adel Elfishawy, Ghada El-Banby, Eman Soltan, and Fathi Abd El-Samie

01/05/2014

This paper focuses on solving the image interpolation problem of noisy images as an inverse problem considering the mathematical model which relates the available noisy low resolution (LR) image to the required high resolution (HR) image. The paper presents four different solutions to this problem and compares their performance. First, an adaptive least squares interpolation algorithm is presented. Second, a Linear Minimum Mean Square Error (LMMSE) solution is suggested. An efficient implementation of this solution as a single sparse matrix inversion is presented. The sensitivity of this solution to the estimates of noise variance and the HR image autocorrelation is studied. Third, a mathematical model is derived for image interpolation based on the maximization of entropy of the required HR image a priori. This model is implemented as a single sparse matrix inversion. Finally, a sectioned implementation of regularized image interpolation is presented and implemented as a single matrix inversion as well. The effect of the choice of the regularization parameter on this solution is studied. The performance of all the above mentioned algorithms is compared from the PSNR, the computation cost and the edge preservation ability points of view.

Waleed Eid Abd Elrahman Alhanafy

Stephan Weiss

01/12/2013

We consider low cost discrete bit loading based on greedy power allocation (GPA) under the constraints of total transmit power budget, target BER, and maximum permissible QAM modulation order. Compared to the standard GPA, which is optimal in terms of maximising the data throughput, three suboptimal schemes are proposed, which perform GPA on subsets of subchannels only. These subsets are created by considering the minimum SNR boundaries of QAM levels for a given target BER. We demonstrate how these schemes can significantly reduce the computational complexity required for power allocation, particularly in the case of a large number of subchannels. Two of the proposed algorithms can achieve near optimal performance including a transfer of residual power between subsets at the expense of a very small extra cost. By simulations, we show that the two near optimal schemes, while greatly reducing complexity, perform best in two separate and distinct SNR regions.

Waleed Eid Abd Elrahman Alhanafy

Stephan Weiss

01/06/2012

This study aims to maximise the rate over a multiple-in multiple-out (MIMO) link using incremental power and bit allocation. Two different schemes, greedy power allocation (GPA) and greedy bit allocation (GBA), are addressed and compared with the standard uniform power allocation (UPA). The design is constrained by the target bit error ratio (BER), the total power budget and fixed discrete modulation orders. The authors demonstrate through simulations that GPA outperforms GBA in terms of throughput and power conservation, whereas GBA is advantageous when a lower BER is beneficial. Once the design constraints are satisfied, remaining power is utilised in two possible ways, leading to improved performance of GPA and UPA algorithms. This redistribution is analysed for fairness in BER performance across all active subchannels using a bisection method.

Waleed Eid Abd Elrahman Alhanafy

F. S. Al-Kamali, M. I. Dessouky, B. M. Sallam, F. Shawki, and F. E. Abd El-Samie

01/03/2012

Due to their noise amplification, conventional Zero-Forcing (ZF) equalizers are not suited for interference-limited environments such as the Single-Carrier Frequency Division Multiple Access (SC-FDMA) in the presence of Carrier-Frequency Offsets (CFOs) . Moreover, they suffer increasing complexity with the number of subcarriers and in particular with Multiple-Input Multiple-Output (MIMO) systems. In this letter, we propose a Joint Low-Complexity Regularized ZF (JLRZF) equalizer for MIMO SC-FDMA systems to cope with these problems. The main objective of this equalizer is to avoid the direct matrix inversion by performing it in two steps to reduce the complexity. We add a regularization term in the second step to avoid the noise amplification. From the obtained simulation results, the proposed scheme is able to enhance the system performance with lower complexity and sufficient robustness to estimation errors.