ZOHRA Zerdoumi

AOUINA Said , MELIANI Elmahdi

Candidate Waveforms in Future Wireless Communication Systems

Cheriat Mohamed Achraf , Ziam Saad Eddine

Filter Bank Multicarrier Modulation Techniques for 5G Communication Systems

AMAR CHEINE Mariem , MOHAMED VALL Nebghouha

Simulation d’un système MIMO-OFDM pour les transmissions sans fil

MECHETER Soumia

Implémentation sous SIMULINK d’un système de transmission MIMO à base d’OFDM

Belfarai Hanane , Yettou Bochra

Application de la transformée en ondelette discrète au système de transmission à base de l’OFDM

Saoud Noui , Hadjab mohamed Elaid

Etude des Performance d’un système MIMO-OFDM pour les communications sans fil

Ghellab Dounya , Doumi Meryem

Technique d’égalisation mono et multi-porteuses

BEN TALLAB NACERDINE , Benatia Djelloul

Etude des performances de la technique OFDM pour les communications sans fil

Slimani Hassen , Saiahi Youcef

Compensation des distorsions dans un système OFDM sous différent types de modulations numériques

Manaa Walid , Tiaiba Hamza

Compensation des distorsions des canaux de communication sous SIMULINK

BARMAKI ABDELLATIF

Etude des algorithmes d'égalisation des canaux de communications numériques

Benouchen Abdelhalim

Méthodes d’identification des systèmes non linéaires

Sid hassen

Méthodes d’égalisation pour les canaux de communication numériques

Fateh djeddi

égalisation non supervisée des canaux de communication numériques

Orthogonal Frequency Division Multiplexing (OFDM) technique has attracted major interest because of its robustness to time selective channels and its aptitude to accomplish high data rate. OFDM is the fundamental solution in 4G and 5G systems due to its simplicity of implementation and effectiveness in severe environments. Traditionally the Fast Fourier Transform (FFT) algorithm is adopted to implement OFDM transmitter. Discrete Wavelet Transform (DWT) is recognized as an improvement to Discrete Fourier Transform; therefore, many academics proposed it as alternative approach to FFT in OFDM transmission system. We propose to study the impact of DWT on the performance of the OFDM transmission system considering various modulation techniques and order in noisy and fading environments. We implement two approaches namely OFDM-FFT and OFDM-DWT, their performances respective are studied and compared. Through simulation examples, we notice the improvements obtained by performing the wavelet transform. The wavelet-based OFDM techniques perform better than OFDM-FFT. The results obtained demonstrate the improvements achieved by adopting the wavelet transform relatively to the FFT for all evaluation metrics used. OFDM-DWT cancels interferences, as we can learn from constellation diagrams, where symbols are delimited in their original zones. OFDM-DWT performs the lowest bit error rate (BER) and a reduced Complementary Cumulative Distribution Function (CCDF) of the Peak to Average Power Ratio (PAPR)

Citation

Zohra ZERDOUMI , ,(2025-11-12), Enhancing OFDM Performance Using Wavelet Transform Techniques in Wireless Systems,IConTES 2025: International Conference on Technology, Engineering and Science,Antalia, Turkey

Controlling asynchronous machines is complex because of the non-linearity of the model and the coupling between stator and rotor quantities. Thanks to advances in power electronics, decoupled control techniques have been developed to reproduce the performance of DC machines, while eliminating mechanical constraints. However, in the case of polyphase machines, these control strategies remain limited due of the harmonics generated by the inverter, which degrade power quality. To address this issue, a new fuzzy logic control strategy is proposed, aimed at reducing parasitic currents and improving dynamic performance in a five-phase asynchronous machine. A comparison between vector control using conventional PI and fuzzy PI is considered, based on the dynamic responses of speed, torque and harmonic distortion rate, especially under load variations and during rotational reversals. The simulation results obtained in MATLAB demonstrate a significant enhancement in speed stability and a reduction in ripples, confirming the effectiveness of the proposed approach

Citation

Zohra ZERDOUMI , Bureau de la stratégie de numérisation , MALIKA BOUDIA , ,(2025-11-12), Speed Control of the Pentaphase Asynchronous Machine: Comparative Study Between Vector Control with Conventional PI and Fuzzy PI,IConTES 2025: International Conference on Technology, Engineering and Science,antalia, Turkey

Multiphase motors are increasingly used in high-performance industrial applications due to their improved efficiency, reliability and fault tolerance compared to traditional three-phase machines. However, one of the persistent challenges in their control is the presence of speed ripples, which can degrade performance, increase mechanical stress and reduce system life time. This paper proposes a control strategy based on adaptive gain fuzzy logic applied to the vector control of a five-phase motor. Unlike conventional fixed-gain controllers, this approach allows the controller gains to be dynamically adjusted according to the state of the system, thus increasing robustness to disturbances and load variations. Fuzzy logic enables the controller's behaviour to be modelled according to linguistic rules inspired by human expertise, making the system more responsive and intelligent. Simulation results obtained using Matlab show a significant improvement in speed stability and a marked reduction in ripples, confirming the effectiveness of the proposed method.. Keywords – PI- controller; five-phase asynchronous machine; fuzzy logic, speed oscillations.

Citation

Zohra ZERDOUMI , Bureau de la stratégie de numérisation , MALIKA Fodil , Bureau de la stratégie de numérisation , Fadila BENMEDDOUR , ,(2025-04-30), Reduction of Speed Ripples in a Polyphase Motor Using Adaptive Gain Fuzzy Control,4th International Conference on Scientific and Innovative Studies ICSIS 2025 April 29 – 30 in 2025 at Konya/Turkey.,Konya, Turkey

The need for high-speed wireless telecommunications services has renewed attention to multi-carrier modulation, more explicitly the Orthogonal Frequency Division multiplexing (OFDM). The excellent performance of the OFDM in mitigating multipath propagation allowed its integration in current and future telecommunication system. Fast Fourier Transform based OFDM is widely used in standards such as LTE and Wi-Fi, and DVB. The OFDM simplicity and robustness beside multipath fading and high transmission efficiency makes it an attractive technique. To further enhance the OFDM performances, Discreet Wavelet Transform (DWT) is adopted as alternative to the Fast Fourier Transform (FFT) in the modem. DWT-based OFDM is gaining more attention in academic research for its potential performance advantages. DWT-based OFDM is more resilient to interference and channel dispersion owed to its multi-resolution abilities and good localization in both time and frequency. FFT-based OFDM is more sensitive and depend on the Cyclic Prefix (CP) to handle such impairments. We propose an analyze of the impact of DWT on the OFDM transmission system. The simulations we carried out allowed us to highlight the improvements obtained by the OFDM-DWT in term of the Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR), relatively to the OFDM-FFT. Among the wavelet types studied, the Haar wavelet provides the best performances.

Citation

Zohra ZERDOUMI , Bureau de la stratégie de numérisation , Bureau de la stratégie de numérisation , Bureau de la stratégie de numérisation , ,(2025-04-29), Analysis of FFT and DWT Based OFDM Techniques for improving Wireless Communication Performance,4th International Conference on Scientific and Innovative Studies ICSIS 2025 April 29 – 30 in 2025 at Konya/Turkey.,Konya, Turkey

Abstract – The resonant frequency and bandwidth of a printed antenna can be modified by varying the physical parameters of the structure. The circular printed antenna with an air-gap proposed here enables these characteristics to be modified without having to design and build a new printed antenna. Its resonant frequency can be modified by adjusting the height of the air gap between the substrate of the radiating element and the ground plane. In addition, the presence of an air gap significantly increases the bandwidth of the a printed antenna. Our first step was to characterize the resonance and bandwidth of this type of antenna theoretically, using the integral equation technique, the moments method via the Galerkin procedure applicable for numerical resolution. To achieve this, the mode systems (TM, TE) derived from the cavity model were used as Chebyshev basis functions to present the current distribution on the conductive disk. Our results are in good agreement with the theoretical results previously published in the literature. In order to validate this study, practical realizations of this type of structure were carried out at the IUT de Chartres -Institut PRISME- to compare our results with real measurements. Good agreement was again found, confirming the interest of this type of antenna. Keywords – air-gap ; physical parameters ; Chebyshev Basis Functions ; Galerkin procedure; theoretical results

Citation

Zohra ZERDOUMI , Bureau de la stratégie de numérisation , MALIKA Fodil , Bureau de la stratégie de numérisation , Fadila BENMEDDOUR , ,(2025-04-29), Analysis of a Circular Printed Antenna With Air Gap Using Chebyshev Basis Functions,4th International Conference on Scientific and Innovative Studies ICSIS 2025 April 29 – 30 in 2025 at Konya/Turkey.,Konya, Turkey

The human skin, being the largest organ of the body, plays a pivotal role in maintaining homeostasis and protecting the body from external threats. Understanding the morphology and composition of skin layers is essential for both medical and cosmetic applications. This study focuses on the morphological analysis of human skin layers utilizing advanced computational image segmentation techniques. The primary objectives of this research are twofold: first, to develop a robust computational image segmentation framework for accurately delineating the distinct layers of human skin, and second, to perform a comprehensive morphological analysis of these skin layers. The study leverages cutting-edge machine learning algorithms and image processing methodologies to achieve these objectives. To achieve accurate image segmentation, a combination of deep learning models and traditional image processing techniques is employed. Convolutional Neural Networks (CNNs) are trained on a dataset of high-resolution skin images to segment the epidermis, dermis, and subcutaneous layers. Post-processing steps, such as morphological operations and edge detection, are applied to refine the segmentation results.

Citation

Zohra ZERDOUMI , ,(2023-11-04), The Morphological Analysis of Human Skin Layers Using Computational Image Segmentation,2023 IEEE International Workshop on Mechatronics Systems Supervision,Hammamet-Tunisia

In nonlinear channel equalization, artificial neural networks (ANN) have attracted a significant interest. The ANN's primary drawback is their intensive training. We propose suggestions for enhancing their training capacities. The first involves applying a whitening technique to the input data by employing a lattice structure as the equalizer. Lattice equalizer therefore becomes insensitivity to the inputs correlation matrix. In the second strategy, we suggest modifying the slope of the activation function. Combining the two methods increases the ANN's nonlinear capabilities and adaptability. Through simulation tests, the offered methodologies efficacy is verified. The results demonstrate that the performance of the neural network-based lattice equalizer is greatly improved by whitening the received data using adaptive lattice channel equalization techniques in conjunction with an adjustable slope activation function.

Citation

Zohra ZERDOUMI , ,(2023-11-02), An improved learning algorithm for training neural network based lattice equalizer,2023 IEEE International Workshop on Mechatronics Systems Supervision,Hammamet-Tunisia

The main objective of our work is to study the resonance characteristics of a triangular microstrip antenna with 2D Photonic Gap Band (PGB) substrate. We study the influence of different parameters of this antenna: the dimensions of the patch, PBG substrate height and permittivity, the diameter and the different networks of holes on the resonance frequency, bandwidth and directivity, by using electromagnetic simulation tool in the frequency domain; CST based on the finite integration method.

Citation

Zohra ZERDOUMI , ,(2023-05-27), Parametric study of a triangular microstrip antenna with PBG substrate,First National Conference On Industrial Engineering And Sustainable Development CIESD’23,University of Relizane

The main objective of our work is to study the resonance characteristics of a triangular microstrip antenna with 2D Photonic Gap Band (PGB) substrate. We study the influence of different parameters of this antenna: the dimensions of the patch, PBG substrate height and permittivity, the diameter and the different networks of holes on the resonance frequency, bandwidth and directivity, by using electromagnetic simulation tool in the frequency domain; CST based on the finite integration method

Citation

Fadila BENMEDDOUR , ASMA Djellid , Zohra ZERDOUMI , BRIK FATIMA, DIB SAMIRA, ,(2023-05-27), Parametric study of a triangular microstrip antenna with PBG substrate,First National Conference On Industrial Engineering And Sustainable Development CIESD’23,University of Relizane, Algeria

Adaptive filters have been thoroughly investigated in digital communication. They are especially exploited as equalizers, to compensate for channel distortions, although equalizers based on linear filters perform poorly in nonlinear distortion. In this paper, a nonlinear equalizer based on a fuzzy filter is proposed and a new algorithm for the adaptation parameters is presented. The followed approach is based on a regularization of the Recursive Least Square (RLS) algorithm and an incorporation of fuzzy rules in the adaptation process. The proposed approach, named Improved Fuzzy Recursive Least Square (IFRLS), enhances significantly the fuzzy equalizer performance through the acquisition of more convergence properties and lower steady-state Mean Square Error (MSE). The efficiency of the IFRLS algorithm is confirmed through extensive simulations in a nonlinear environment, besides the conventional RLS, in terms of convergence abilities, through MSE, and the equalized signal behavior. The IFRLS algorithm recovers the transmitted signal efficiently and leads to lower steady-state MSE. An improvement in convergence abilities is noticed, besides the RLS.

Citation

Zohra ZERDOUMI , , (2023-05-17), An Improved Recursive Least Square Algorithm For Adapting Fuzzy Channel Equalizer, Engineering, Technology & Applied Science Research, Vol:13, Issue:4, pages:11124-11129, ETASR

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Citation

Zohra ZERDOUMI , ,(2022), Évitez le haut degré de similarité et écrire des citations de manière appropriée en utilisant Mendeley,Évitez le haut degré de similarité et écrire des citations de manière appropriée en utilisant Mendeley,Algérie,

Feed for word neural networks (FFNN) have attracted a great attention, in digital communication area. Especially they are investigated as nonlinear equalizers at the receiver, to mitigate channel distortions and additive noise. The major drawback of the FFNN is their extensive training. We present a new approach to enhance their training efficiency by adapting the activation function. Adapting procedure for activation function extensively increases the flexibility and the nonlinear approximation capability of FFNN. Consequently, the learning process presents better performances, offers more flexibility and enhances nonlinear capability of NN structure thus the final state kept away from undesired saturation regions. The effectiveness of the proposed method is demonstrated through different challenging channel models, it performs quite well for nonlinear channels which are severe and hard to equalize. The performance is measured throughout, convergence properties, minimum bit error achieved. The proposed algorithm was found to converge rapidly, and accomplish the minimum steady state value. All simulation shows that the proposed method improves significantly the training efficiency of FFNN based equalizer compared to the standard training one.

Citation

Fadila BENMEDDOUR , Zohra ZERDOUMI , Latifa ABDOU, Djamel BENATIA, ,(2021-11-04), An Adaptive Sigmoidal Activation Function for Training Feed Forward Neural Network Equalizer,IConTech 2021: International Conference on Technology 4th to 7th November 2021, Antalya, Lara, Turkey,Antalya, Lara, Turkey

Abstract: Feed for word neural networks (FFNN) have attracted a great attention, in digital communication area. Especially they are investigated as nonlinear equalizers at the receiver, to mitigate channel distortions and additive noise. The major drawback of the FFNN is their extensive training. We present a new approach to enhance their training efficiency by adapting the activation function. Adapting procedure for activation function extensively increases the flexibility and the nonlinear approximation capability of FFNN. Consequently, the learning process presents better performances, offers more flexibility and enhances nonlinear capability of NN structure thus the final state kept away from undesired saturation regions. The effectiveness of the proposed method is demonstrated through different challenging channel models, it performs quite well for nonlinear channels which are severe and hard to equalize. The performance is measured throughout, convergence properties, minimum bit error achieved. The proposed algorithm was found to converge rapidly, and accomplish the minimum steady state value. All simulation shows that the proposed method improves significantly the training efficiency of FFNN based equalizer compared to the standard training one.

Citation

Zohra ZERDOUMI , ,(2021), An Adaptive Sigmoidal Activation Function for Training Feed Forward Neural Network Equalizer,IConTech 2021: International Conference on Technology,antalia, Turkey

Abstract –Nonlinear channel equalization have attracted a great attention, in digital communication area. Especially artificial neural networks (ANN) are investigated as equalizers, to mitigate channel impairments. The major drawback of the ANN is their extensive training. We present a new learning approach to enhance their training efficiency by performing an adaptive activation function. The new learning procedure increases significantly the flexibility and the nonlinear approximation capability of ANN equalizer. The effectiveness of the proposed method is established via diverse challenging channel models. The proposed method is also performed on variant environment to check its tracking ability. Simulation results show that the proposed approach improves significantly the training efficiency of ANN based equalize compared to the standard training one.

Citation

Zohra ZERDOUMI , ,(2021), An improved learning algorithm for nonlinear channel equalization,1st International Conference on Applied Engineering and Natural Sciences,Konya, Turkey

L'instrumentation est un domaine très vaste qui fait appel à de nombreuses technologies, telles que : l’informatique, la vision artificielle, la régulation automatique. L'instrumentation constitue une activité capitale en automatisme étant donné qu'elle fournit les informations indispensables au contrôle des installations automatisées. L'exploitation des informations délivrées par des mesures en instrumentation peuvent être facilitées par des logiciels d'analyse du signal, de traitement et de visualisation de données. Dans ce contexte, ce support de cours a pour objet de présenter un large éventail des connaissances de base en instrumentation et mesure industrielle. Ce document est destiné aux étudiants de la formation de master II instrumentation dans le cadre du programme officiel de l’enseignement supérieur de la matière mesure et instrumentation industrielle. Ce cours introduit des notions de base en mesure telles que les caractéristiques métrologique (précision, résolution, temps de réponse, étendue de mesure, ...), les générateurs de tension (0- 10V), les générateurs d'intensité (0-20 mA et 4-20 mA) ainsi que les principes des appareils de mesures analogique et numérique. Ce document décrit aussi les maillons essentiels rencontrés dans une chaîne de mesure analogique et numérique, justifiant ainsi leurs rôles . Afin de donner un aperçu sur les systèmes de mesure industriels, ce support de cours présente une variante d’exemples de procédés de mesure tels que : le tachymètre, le PH-mètre, le débitmètre, les techniques spectrométriques ... Etant donné qu’en instrumentation, le bruit affecte tous les éléments de la chaine de mesure, il conditionne la précision de la mesure, il perturbe le fonctionnement des horloges, il génère des fluctuations de fréquence celles-ci peuvent limiter le débit de transmission des données.

Citation

ZohraZERDOUMI , ,(2021); cours Master2: Instrumentations et mesures industrielles,Mohammed Boudiaf Msila,

We present a new approach to enhance their training efficiency by adapting the slope of the sigmoidal activation function. Adapting procedure for activation function extensively increases the flexibility and the nonlinear approximation capability of ANN. Consequently, the learning process presents a better performance; the final state kept away from undesired saturation regions. The effectiveness of the proposed method is demonstrated through different challenging channel models, in terms of convergence properties, minimum bit error achieved. The tracking capability of the proposed method is also considered.

Citation

Zohra ZERDOUMI , ,(2018), Back propagation algorithm with adaptive slope sigmoidal activation function for mitigating channel impairments,Second International Conference on Electrical Engineering (ICEEB’2018),Biskra, Algeria

Neural network based equalizers can easily compensate channel impairments; such additive noise and inter symbol interference (ISI). The authors present a new approach to improve the training efficiency of the multilayer perceptron (MLP) based equalizer. Their improvement consists on modifying the back propagation (BP) algorithm, by adapting the activation function in addition to the other parameters of the MLP structure. The authors report on experiment results evaluating the performance of the proposed approach namely the back propagation with adaptive activation function (BPAAF) next to the BP algorithm.

Citation

Zohra ZERDOUMI , , (2016), Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channel, Int.J. of Mobile Computing and Multimedia Communications, Vol:7, Issue:3, pages:pp.16-31, IGI publisher

Our approach consists on modifying the conventional back propagation algorithm, through creating an adaptive nonlinearity in the activation function. Experiment results evaluates the performance of the MLPE trained using the conventional BP and the improved back propagation with adaptive gain (IBPAG). Due to the adaptability of the activation function gain the nonlinear capacity and flexibility of the MLP is enhanced significantly.

Citation

Zohra ZERDOUMI , , (2016), An improved back propagation algorithm for training neural network-based equaliser for signal restoration in digital communication channels, Int. J. Mobile Network Design and Innovation,, Vol:6, Issue:4, pages:pp.236-244,, inderscience

This paper presents the equalization of digital communication channels using artificial neural network structures. The performances of a nonlinear equalizer using multilayer perceptron (MLP) trained by the back propagation algorithm is compared with a conventional linear traversal equalizer (LTE). Simulation results show that the performances of the MLP based Equalizer surpass significantly the classical LTE in term of the restored signal, the steady state mean square error (MSE) achievable and the minimum bit error rate attainable. The consistency in performance is observed in minimum phase and non-minimum phase channels as well.

Citation

Zohra ZERDOUMI , , (2015), ‘Neural Networks Based Equalizer for Signal Restoration in Digital Communication Channels, International Letters of Chemistry, Physics and Astronomy, Vol:55, Issue:1, pages:pp 191-204, scipress

One of the main obstacles to reliable communications is the inter symbol interference (ISI). An adaptive equalizer is required at the receiver to mitigate the effects of non-ideal channel characteristics. The conventional way to combat with ISI is to include an equalizer in the receiver. This paper presents the equalization of communication channels using artificial neural network structures. The performances of a nonlinear equalizer using multilayer perceptron (MLP) trained by the back propagation algorithm is compared with a conventional linear traversal equaliser (LTE). Simulation results show that the performances of the MLP Equalizer surpass significantly the classical LTE in term of the equalized signal and the steady state mean square error (MSE) achievable.

Citation

Zohra ZERDOUMI , ,(2013), Adaptive Equalization of Digital Communication Channels Using Neural Network ,,International Conference On Signal, Image, Vision And Their Applications( SIVA’13),Guelma, Algeria.

This paper investigates the application of artificial neural network to the problem of nonlinear channel equalization. The difficulties caused by channel distortions such as inter symbol interference (ISI) and nonlinearity can overcome by nonlinear equalizers employing neural networks. It has been shown that multilayer perceptron based equalizer (MLPE) outperform significantly linear equalizers. We present a multilayer perceptron based equalizer with decision feedback (MLP DFE) trained with the back propagation algorithm. The capacity of the MLP DFE to deal with nonlinear channels is evaluated. It is shown from simulation results that performance of the MLP DFE surpass significantly the MLPE in term of eye pattern quality, steady state mean square error (MSE), and minimum Bit Error Rate (BER).

Citation

Zohra ZERDOUMI , ,(2013), Adaptive Decision Feedback Equalizer Based Neural Network for Nonlinear Channels,The third International Conference on Systems and Control (ICSC’13), IEEE conf,Hotel Hilton, Algeria.

Abstract – Multicarrier modulations have seen a great attention in recent years, especially Orthogonal Frequency Division Multiplexing (OFDM) which is widely employed in modern wireless communication systems. OFDM is often recognized by robustness against multipath channels and easiest implementation. Despite its adoption in many communication standard, OFDM suffers from several limitations, counting high out-of-band emissions (OOBE), and sensitivity to synchronization errors, and loss of spectral efficiency, owing to the cyclic prefix. Recent researches propose several waveforms in order to improve OFDM capabilities or as alternatives to OFDM, including Filter Bank Multicarrier (FBMC), Universal Filtered Multicarrier (UFMC), and Filtered-OFDM (F-OFDM). Among these multicarrier waveforms, F-OFDM has attracted important consideration since it is considered as an improvement of OFDM. The key issue of F-OFDM is apply sub-band filtering to OFDM signal, thus improves spectral confinement and reduces inter-band interference. This paper offers a comparative study of OFDM and F-OFDM in terms of spectral efficiency, Bit Error Rate (BER) and OOBE under severe channel conditions. Simulation results exhibits a significant reduction in out-of-band emissions whereas it maintain analogous Bit Error Rate (BER) performance to OFDM. F-OFDM offers similarly an improved spectral performance and ensure compatibility with existing OFDM-based systems. These enhancements in performance is at the cost of a moderate increase in implementation complexity. These results approve the suitability of F-OFDM as a promising development of OFDM, making it a robust candidate waveform for modern wireless communication systems. Keywords –Multicarrier modulatiom, OFDM, F-OFDM, Digital communications.

Citation

Zohra ZERDOUMI , ,(0026-12-18), Performance Evaluation of OFDM and Filtered-OFDM Waveforms for Wireless Communication Systems,4th International Conference on Pioneer and Innovative Studies ICPIS 2026,Konya, Turkey