Abdelmalek Zidouri | King Fahd University of Petroleum and Minerals (original) (raw)

Papers by Abdelmalek Zidouri

This paper proposes the use of sufficient cyclic prefix (CP) OFDM synthetic aperture radar (SAR) ... more This paper proposes the use of sufficient cyclic prefix (CP) OFDM synthetic aperture radar (SAR) for foliage penetration (FOPEN). The foliage introduces phase and amplitude fluctuation which cause the sidelobes to increase and affects the final image of the obscured targets. The wideband CP-based OFDM SAR inherently eliminates the sidelobes that arise from the interference between targets on the same range line. The integrated sidelobe level ratio (ISLR) of the CP-based OFDM signal along the range direction is lower than that of the random noise signal by 2 dB for foliage penetration application, while the peak sidelobe level ratio (PSLR) are almost the same of both of the two signals.

Pattern Recognition, 2015

In this paper, we present an Arabic handwriting synthesis system. Two concatenation models to syn... more In this paper, we present an Arabic handwriting synthesis system. Two concatenation models to synthesize Arabic words from segmented characters are adopted: Extended-Glyphs connection and Synthetic-Extensions connection. We use our system to synthesize handwriting from a collected dataset and inject it into an expanded dataset. We experiment by training a state-of-the-art Arabic handwriting recognition system on the collected dataset, as well as on the expanded dataset, and test it on the IFN/ ENIT Arabic benchmark dataset. We show significant improvement in recognition performance due to the data that was synthesized by our system. & 2014 Elsevier Ltd. All rights reserved. characters take one of four character-shapes: Beginning (B), Middle (M), Ending (E), and Alone (A); the few characters that do not connect to their successors can only take the (E) or (A) character-shapes. These characters cause Arabic words to break into Pieces of Arabic Words (PAWs). From right to left, a multicharacter PAW consists of one (B) character-shape followed by zero or more (M) character-shapes and is terminated by one (E) character-shape. A PAW that consists solely of one character always takes the (A) character-shape. Characters connect in Arabic via a stroke called the Kashida [21]. Kashida are semi-horizontal strokes that often lie in the Contents lists available at ScienceDirect

PeerJ Computer Science, 2022

Training deep learning based handwritten text recognition systems needs a lot of data in terms of... more Training deep learning based handwritten text recognition systems needs a lot of data in terms of text images and their corresponding annotations. One way to deal with this issue is to use data augmentation techniques to increase the amount of training data. Generative Adversarial Networks (GANs) based data augmentation techniques are popular in literature especially in tasks related to images. However, specific challenges need to be addressed in order to effectively use GANs for data augmentation in the domain of text recognition. Text data is inherently imbalanced in terms of frequency of different characters appearing in training samples and the training data as a whole. GANs trained on the imbalanced dataset leads to augmented data that does not represent the minority characters well. In this paper, we present an adaptive data augmentation technique using GANs that deals with the issue of class imbalance arising in text recognition problems. We show, using experimental evaluatio...

International Journal on Document Analysis and Recognition (IJDAR), 2014

Handwriting synthesis is the automatic generation of data that resemble natural handwriting. Alth... more Handwriting synthesis is the automatic generation of data that resemble natural handwriting. Although handwriting synthesis has recently gained increasing interest, the area still lacks a stand-alone review. This paper provides classifications for the different aspects of handwriting synthesis. It presents the applications, techniques, and evaluation methods for handwriting synthesis based on the several aspects that we identify. Then, it discusses various synthesis techniques. To the best of our knowledge, this paper is the only stand-alone survey on this topic, and we believe it can serve as a useful reference for the researchers in the field of handwriting synthesis.

Attribution License, which permits unrestricted use, distribution, and reproduction in any medium... more Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A novel algorithm, called the signed regressor least mean fourth (SRLMF) adaptive algorithm, that reduces the computational cost and complexity while maintaining good performance is presented. Expressions are derived for the steady-state excess-mean-square error (EMSE) of the SRLMF algorithm in a stationary environment. A sufficient condition for the convergence in the mean of the SRLMF algorithm is derived. Also, expressions are obtained for the tracking EMSE of the SRLMF algorithm in a nonstationary environment, and consequently an optimum value of the step-size is obtained. Moreover, the weighted variance relation has been extended in order to derive expressions for the mean-square error (MSE) and the mean-square deviation (MSD) of the proposed algorithm during the transient phase. Computer simulations are carried out to corroborate the ...

Since stroke components are the most basic structural featurea of patterns like ch.aracters or li... more Since stroke components are the most basic structural featurea of patterns like ch.aracters or linea in im.ages. Prom a tiieui point of bein.g applicable to docum.en.t image understandin.g, it ia necessary to provide a good represen.tation th.at can. express such features, so th,at an interpretation of im.ages can be facilita.ted. Th.is article pre,qen.ta a new tech,n.ique used for ezpressin.g bin.ary doczim.ent im.agea. The proposed technique derieloped from the Minimum. Coverin.g Run (MCR) expression to extract stroke components of patterns in, images accurately. 1

Abstract: In this study, we propose a new sub-word segmentation and recognition scheme, which is ... more Abstract: In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. Different ways of recognition are attempted namely Neural Net, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

License, which permits unrestricted use, distribution, and reproduction in any medium, provided t... more License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A newly developed adaptive scheme for system identification is proposed. The proposed algorithm is a mixture of two norms, namely, the l2-norm and the lp-norm (p ≥ 1), where a controlling parameter in the range [0, 1] is used to control the mixture of the two norms. Existing algorithms based on mixed norm can be considered as a special case of the proposed algorithm. Therefore, our algorithm can be seen as a generalization to these algorithms. The derivation of the algorithm and its convexity property are reported and detailed. Also, the first moment behaviour as well as the second moment behaviour of the weights is studied. Bounds for the step size on the convergence of the proposed algorithm are derived, and the steady-state analysis is carried out. Finally, simulation results are performed and are found to corroborate with the theory developed. 1.

Although, optical character recognition has made tremendous achievements in the area of desktop p... more Although, optical character recognition has made tremendous achievements in the area of desktop publishing, yet a huge amount of work is required to be done. Unlike Roman like languages, there are various languages possessing a large number of fonts and/or having complicated shapes. Arabic language is one of those languages, which is somewhat complicated in its construction. Although a reasonable amount of work has been reported so far for Arabic language but still a good amount of work is needed to be developed. In addition, many other languages also need considerable attention for automatic generation in their recognition. Efficient, robust, and error free methodologies are required to develop systems for such languages so that the recent hardware technologies, to display and print, can be utilized. This work is devoted to one way of addressing the problem of recognition of the Arabic alphabet. We give a brief survey of the state of the art in Arabic Character Recognition and diff...

IEICE Transactions on Information and Systems, 1994

Summary. Japanese Page. ...

Character recognition is one of the oldest fields of research. It is the art of automating both t... more Character recognition is one of the oldest fields of research. It is the art of automating both the process of reading and keyboard input of text in documents. A major part of information in documents is in the form of alphanumeric text. However, characters’ automatic recognition is not an easy problem, especially for languages using the Arabic script. Arabic is written cursively (connected) even when machine printed or typed. Despite the rapidly increasing electronic sources and libraries, paper documents will live with us for a long time to come. Automatic handling of such documents needs robust and reliable document understanding techniques. For Chinese, Japanese, and Roman characters based languages, the problem of recognizing well formed and neat characters have been largely solved, There are several commercial OCR’s available in the market today, example Omnipage, Recognita, IRISpen, Kanjiscan, YondeKoko to name just a few. Research is now being focused on more challenging pro...

Research Journal of Applied Sciences, Engineering and Technology, 2010

In this study, we propose a new sub-word segmentation and recognition scheme, which is independen... more In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. Different ways of recognition are attempted namely Neural Net, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

Document Analysis and Recognition – ICDAR 2021 Workshops

IEEE Access

Recognition of cursive handwritten Arabic text is a difficult problem because of contextsensitive... more Recognition of cursive handwritten Arabic text is a difficult problem because of contextsensitive character shapes, the non-uniform spacing between words and within a word, diverse placements of dots, and diacritics, and very low inter-class variation among individual classes. In this paper, we review and investigate different deep learning architectures and modeling choices for Arabic handwriting recognition. Further, we address the problem that imbalanced data sets present to deep learning systems. In order to address this issue, we are presenting a novel adaptive data-augmentation algorithm to promote class diversity. This algorithm assigns a weight to each word in the database lexicon. This weight is calculated based on the average probability of each class in a word. Experimental results on the IFN/ENIT and AHDB databases have shown that our presented approach yields state-of-the-art results. INDEX TERMS Arabic handwriting recognition (AHR), deep learning neural network (DLNN), convolutional neural networks (CNN), connectionist temporal classification (CTC), recurrent neural network (RNN), IFN/ENIT database, long short-term memory (LSTM), bi-directional long short-term memory (BLSTM), word beam search (WBS).

International Journal of Advanced Computer Science and Applications

Arabic script is inherently cursive, even when machine-printed. When connected to other character... more Arabic script is inherently cursive, even when machine-printed. When connected to other characters, some Arabic characters may be optionally written in compact aesthetic forms known as ligatures. It is useful to distinguish ligatures from ordinary characters for several applications, especially automatic text recognition. Datasets that do not annotate these ligatures may confuse the recognition system training. Some popular datasets manually annotate ligatures, but no dataset (prior to this work) took ligatures into consideration from the design phase. In this paper, a detailed study of Arabic ligatures and a design for a dataset that considers the representation of ligative and unligative characters are presented. Then, pilot data collection and recognition experiments are conducted on the presented dataset and on another popular dataset of handwritten Arabic words. These experiments show the benefit of annotating ligatures in datasets by reducing error-rates in character recognition tasks.

EURASIP Journal on Advances in Signal Processing, 2016

Adaptive filtering algorithms promise an improvement of the active noise control (ANC) problem en... more Adaptive filtering algorithms promise an improvement of the active noise control (ANC) problem encountered in many scenarios. Just to name a few, the Filtered-X Least Mean Square (FXLMS) algorithm, the Leaky FXLMS (LFXLMS) algorithm, and other modified LMS-based algorithms have been developed and utilized to combat the ANC problem. All of these algorithms enjoy great performance when the signal-to-noise ratio (SNR) is high. On the other hand, when the SNR is low, which is a known trend in ANC scenarios, the performance of these algorithms is not attractive. The performance of the Least Mean Fourth (LMF) algorithm has never been tested on any ANC scenario under low or high SNR. Therefore, in this work, reflecting the development in the LMS family on the LMF, we are proposing two new adaptive filtering algorithms, which are the Filtered-X Least Mean Fourth (FXLMF) algorithm and the Leakage-based variant (LFXLMF) of the FXLMF algorithm. The main target of this work is to derive the FXLMF and LFXLMF adaptive algorithms, study their convergence behaviors, examine their tracking and transient conduct, and analyze their performance for different noise environments. Moreover, a convex combination filter utilizing the proposed algorithm and algorithm robustness test is carried out. Finally, several simulation results are obtained to validate the theoretical findings and show the effectiveness of the proposed algorithms over other adaptive algorithms.

EURASIP Journal on Advances in Signal Processing, 2016

Single-carrier frequency division multiple access (SC-FDMA) has been adopted and employed as the ... more Single-carrier frequency division multiple access (SC-FDMA) has been adopted and employed as the standard in the 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) uplink multiple-access scheme. It offers comparable performance and complexity to orthogonal frequency multiple access scheme (OFDMA) with a lower peak to average power ratio (PAPR) offering power-efficient transmission and longer battery life to mobile terminals. However, due to its single-carrier nature, SC-FDMA performance degrades in channels with long impulse responses and becomes prohibitive to equalize when implemented in time domain (TD). Furthermore, of the seven SC-FDMA symbols in the LTE uplink slot, one full symbol is used for channel estimation leading to about 14 % throughput degradation. In this work, a novel frequency domain soft-constraint satisfaction multimodulus blind algorithm (FDSCS-MMA) is developed and proposed. The frequency domain approach results in computational complexity reduction while blind implementation ensured improved spectral efficiency and throughput. The algorithm convergence is further improved by normalization of each of the frequency bin in the weight update. Simulation results show superior performance of the developed algorithm over other blind algorithms.

2016 13th International Multi-Conference on Systems, Signals & Devices (SSD), 2016

Ieice Transactions on Information and Systems, Apr 25, 1995

This paper proposes the use of sufficient cyclic prefix (CP) OFDM synthetic aperture radar (SAR) ... more This paper proposes the use of sufficient cyclic prefix (CP) OFDM synthetic aperture radar (SAR) for foliage penetration (FOPEN). The foliage introduces phase and amplitude fluctuation which cause the sidelobes to increase and affects the final image of the obscured targets. The wideband CP-based OFDM SAR inherently eliminates the sidelobes that arise from the interference between targets on the same range line. The integrated sidelobe level ratio (ISLR) of the CP-based OFDM signal along the range direction is lower than that of the random noise signal by 2 dB for foliage penetration application, while the peak sidelobe level ratio (PSLR) are almost the same of both of the two signals.

Pattern Recognition, 2015

In this paper, we present an Arabic handwriting synthesis system. Two concatenation models to syn... more In this paper, we present an Arabic handwriting synthesis system. Two concatenation models to synthesize Arabic words from segmented characters are adopted: Extended-Glyphs connection and Synthetic-Extensions connection. We use our system to synthesize handwriting from a collected dataset and inject it into an expanded dataset. We experiment by training a state-of-the-art Arabic handwriting recognition system on the collected dataset, as well as on the expanded dataset, and test it on the IFN/ ENIT Arabic benchmark dataset. We show significant improvement in recognition performance due to the data that was synthesized by our system. & 2014 Elsevier Ltd. All rights reserved. characters take one of four character-shapes: Beginning (B), Middle (M), Ending (E), and Alone (A); the few characters that do not connect to their successors can only take the (E) or (A) character-shapes. These characters cause Arabic words to break into Pieces of Arabic Words (PAWs). From right to left, a multicharacter PAW consists of one (B) character-shape followed by zero or more (M) character-shapes and is terminated by one (E) character-shape. A PAW that consists solely of one character always takes the (A) character-shape. Characters connect in Arabic via a stroke called the Kashida [21]. Kashida are semi-horizontal strokes that often lie in the Contents lists available at ScienceDirect

PeerJ Computer Science, 2022

Training deep learning based handwritten text recognition systems needs a lot of data in terms of... more Training deep learning based handwritten text recognition systems needs a lot of data in terms of text images and their corresponding annotations. One way to deal with this issue is to use data augmentation techniques to increase the amount of training data. Generative Adversarial Networks (GANs) based data augmentation techniques are popular in literature especially in tasks related to images. However, specific challenges need to be addressed in order to effectively use GANs for data augmentation in the domain of text recognition. Text data is inherently imbalanced in terms of frequency of different characters appearing in training samples and the training data as a whole. GANs trained on the imbalanced dataset leads to augmented data that does not represent the minority characters well. In this paper, we present an adaptive data augmentation technique using GANs that deals with the issue of class imbalance arising in text recognition problems. We show, using experimental evaluatio...

International Journal on Document Analysis and Recognition (IJDAR), 2014

Handwriting synthesis is the automatic generation of data that resemble natural handwriting. Alth... more Handwriting synthesis is the automatic generation of data that resemble natural handwriting. Although handwriting synthesis has recently gained increasing interest, the area still lacks a stand-alone review. This paper provides classifications for the different aspects of handwriting synthesis. It presents the applications, techniques, and evaluation methods for handwriting synthesis based on the several aspects that we identify. Then, it discusses various synthesis techniques. To the best of our knowledge, this paper is the only stand-alone survey on this topic, and we believe it can serve as a useful reference for the researchers in the field of handwriting synthesis.

Attribution License, which permits unrestricted use, distribution, and reproduction in any medium... more Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A novel algorithm, called the signed regressor least mean fourth (SRLMF) adaptive algorithm, that reduces the computational cost and complexity while maintaining good performance is presented. Expressions are derived for the steady-state excess-mean-square error (EMSE) of the SRLMF algorithm in a stationary environment. A sufficient condition for the convergence in the mean of the SRLMF algorithm is derived. Also, expressions are obtained for the tracking EMSE of the SRLMF algorithm in a nonstationary environment, and consequently an optimum value of the step-size is obtained. Moreover, the weighted variance relation has been extended in order to derive expressions for the mean-square error (MSE) and the mean-square deviation (MSD) of the proposed algorithm during the transient phase. Computer simulations are carried out to corroborate the ...

Since stroke components are the most basic structural featurea of patterns like ch.aracters or li... more Since stroke components are the most basic structural featurea of patterns like ch.aracters or linea in im.ages. Prom a tiieui point of bein.g applicable to docum.en.t image understandin.g, it ia necessary to provide a good represen.tation th.at can. express such features, so th,at an interpretation of im.ages can be facilita.ted. Th.is article pre,qen.ta a new tech,n.ique used for ezpressin.g bin.ary doczim.ent im.agea. The proposed technique derieloped from the Minimum. Coverin.g Run (MCR) expression to extract stroke components of patterns in, images accurately. 1

Abstract: In this study, we propose a new sub-word segmentation and recognition scheme, which is ... more Abstract: In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. Different ways of recognition are attempted namely Neural Net, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

License, which permits unrestricted use, distribution, and reproduction in any medium, provided t... more License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A newly developed adaptive scheme for system identification is proposed. The proposed algorithm is a mixture of two norms, namely, the l2-norm and the lp-norm (p ≥ 1), where a controlling parameter in the range [0, 1] is used to control the mixture of the two norms. Existing algorithms based on mixed norm can be considered as a special case of the proposed algorithm. Therefore, our algorithm can be seen as a generalization to these algorithms. The derivation of the algorithm and its convexity property are reported and detailed. Also, the first moment behaviour as well as the second moment behaviour of the weights is studied. Bounds for the step size on the convergence of the proposed algorithm are derived, and the steady-state analysis is carried out. Finally, simulation results are performed and are found to corroborate with the theory developed. 1.

Although, optical character recognition has made tremendous achievements in the area of desktop p... more Although, optical character recognition has made tremendous achievements in the area of desktop publishing, yet a huge amount of work is required to be done. Unlike Roman like languages, there are various languages possessing a large number of fonts and/or having complicated shapes. Arabic language is one of those languages, which is somewhat complicated in its construction. Although a reasonable amount of work has been reported so far for Arabic language but still a good amount of work is needed to be developed. In addition, many other languages also need considerable attention for automatic generation in their recognition. Efficient, robust, and error free methodologies are required to develop systems for such languages so that the recent hardware technologies, to display and print, can be utilized. This work is devoted to one way of addressing the problem of recognition of the Arabic alphabet. We give a brief survey of the state of the art in Arabic Character Recognition and diff...

IEICE Transactions on Information and Systems, 1994

Summary. Japanese Page. ...

Character recognition is one of the oldest fields of research. It is the art of automating both t... more Character recognition is one of the oldest fields of research. It is the art of automating both the process of reading and keyboard input of text in documents. A major part of information in documents is in the form of alphanumeric text. However, characters’ automatic recognition is not an easy problem, especially for languages using the Arabic script. Arabic is written cursively (connected) even when machine printed or typed. Despite the rapidly increasing electronic sources and libraries, paper documents will live with us for a long time to come. Automatic handling of such documents needs robust and reliable document understanding techniques. For Chinese, Japanese, and Roman characters based languages, the problem of recognizing well formed and neat characters have been largely solved, There are several commercial OCR’s available in the market today, example Omnipage, Recognita, IRISpen, Kanjiscan, YondeKoko to name just a few. Research is now being focused on more challenging pro...

Research Journal of Applied Sciences, Engineering and Technology, 2010

In this study, we propose a new sub-word segmentation and recognition scheme, which is independen... more In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. Different ways of recognition are attempted namely Neural Net, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

Document Analysis and Recognition – ICDAR 2021 Workshops

IEEE Access

Recognition of cursive handwritten Arabic text is a difficult problem because of contextsensitive... more Recognition of cursive handwritten Arabic text is a difficult problem because of contextsensitive character shapes, the non-uniform spacing between words and within a word, diverse placements of dots, and diacritics, and very low inter-class variation among individual classes. In this paper, we review and investigate different deep learning architectures and modeling choices for Arabic handwriting recognition. Further, we address the problem that imbalanced data sets present to deep learning systems. In order to address this issue, we are presenting a novel adaptive data-augmentation algorithm to promote class diversity. This algorithm assigns a weight to each word in the database lexicon. This weight is calculated based on the average probability of each class in a word. Experimental results on the IFN/ENIT and AHDB databases have shown that our presented approach yields state-of-the-art results. INDEX TERMS Arabic handwriting recognition (AHR), deep learning neural network (DLNN), convolutional neural networks (CNN), connectionist temporal classification (CTC), recurrent neural network (RNN), IFN/ENIT database, long short-term memory (LSTM), bi-directional long short-term memory (BLSTM), word beam search (WBS).

International Journal of Advanced Computer Science and Applications

Arabic script is inherently cursive, even when machine-printed. When connected to other character... more Arabic script is inherently cursive, even when machine-printed. When connected to other characters, some Arabic characters may be optionally written in compact aesthetic forms known as ligatures. It is useful to distinguish ligatures from ordinary characters for several applications, especially automatic text recognition. Datasets that do not annotate these ligatures may confuse the recognition system training. Some popular datasets manually annotate ligatures, but no dataset (prior to this work) took ligatures into consideration from the design phase. In this paper, a detailed study of Arabic ligatures and a design for a dataset that considers the representation of ligative and unligative characters are presented. Then, pilot data collection and recognition experiments are conducted on the presented dataset and on another popular dataset of handwritten Arabic words. These experiments show the benefit of annotating ligatures in datasets by reducing error-rates in character recognition tasks.

EURASIP Journal on Advances in Signal Processing, 2016

Adaptive filtering algorithms promise an improvement of the active noise control (ANC) problem en... more Adaptive filtering algorithms promise an improvement of the active noise control (ANC) problem encountered in many scenarios. Just to name a few, the Filtered-X Least Mean Square (FXLMS) algorithm, the Leaky FXLMS (LFXLMS) algorithm, and other modified LMS-based algorithms have been developed and utilized to combat the ANC problem. All of these algorithms enjoy great performance when the signal-to-noise ratio (SNR) is high. On the other hand, when the SNR is low, which is a known trend in ANC scenarios, the performance of these algorithms is not attractive. The performance of the Least Mean Fourth (LMF) algorithm has never been tested on any ANC scenario under low or high SNR. Therefore, in this work, reflecting the development in the LMS family on the LMF, we are proposing two new adaptive filtering algorithms, which are the Filtered-X Least Mean Fourth (FXLMF) algorithm and the Leakage-based variant (LFXLMF) of the FXLMF algorithm. The main target of this work is to derive the FXLMF and LFXLMF adaptive algorithms, study their convergence behaviors, examine their tracking and transient conduct, and analyze their performance for different noise environments. Moreover, a convex combination filter utilizing the proposed algorithm and algorithm robustness test is carried out. Finally, several simulation results are obtained to validate the theoretical findings and show the effectiveness of the proposed algorithms over other adaptive algorithms.

EURASIP Journal on Advances in Signal Processing, 2016

Single-carrier frequency division multiple access (SC-FDMA) has been adopted and employed as the ... more Single-carrier frequency division multiple access (SC-FDMA) has been adopted and employed as the standard in the 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) uplink multiple-access scheme. It offers comparable performance and complexity to orthogonal frequency multiple access scheme (OFDMA) with a lower peak to average power ratio (PAPR) offering power-efficient transmission and longer battery life to mobile terminals. However, due to its single-carrier nature, SC-FDMA performance degrades in channels with long impulse responses and becomes prohibitive to equalize when implemented in time domain (TD). Furthermore, of the seven SC-FDMA symbols in the LTE uplink slot, one full symbol is used for channel estimation leading to about 14 % throughput degradation. In this work, a novel frequency domain soft-constraint satisfaction multimodulus blind algorithm (FDSCS-MMA) is developed and proposed. The frequency domain approach results in computational complexity reduction while blind implementation ensured improved spectral efficiency and throughput. The algorithm convergence is further improved by normalization of each of the frequency bin in the weight update. Simulation results show superior performance of the developed algorithm over other blind algorithms.

2016 13th International Multi-Conference on Systems, Signals & Devices (SSD), 2016

Ieice Transactions on Information and Systems, Apr 25, 1995