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23 articles for “Channel Models”
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Research ArticleOpen accessPhrase in the titleCyclic Prefix Length Determination for Orthogonal Frequency Division Multiplexing System over Different Wireless Channel Models Based on the Maximum Excess Delay SpreadAmar Al-Jzari, Kostanic IvivaCyclic Prefix (CP) is one of the key OFDM parameters. It is used to completely eliminate both Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI) as long as the CP length is greater than the channel delay spread. By eliminating the ISI and ICI, the CP compensates for the effect of the multi-path dispersion; but it consumes a considerable amount of … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 1 · 13 Apr 2015 · 8,563 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePerformance Evaluation of Channel Propagation Models and Developed Model for Mobile CommunicationYahia ZakariaPropagation models represent a solidifying of mathematical equations and algorithms that are used for radio signal propagation prediction in specific regions. In this research different propagation models are analyzed and compared. These propagation models have been proposed at the operating frequency of 3.8 GHz for different transmitter antenna heights in all types of terrain. These propagation models depend on location, … …American Journal of Applied Sciences, Vol. 14, Issue 2 · 25 Feb 2017 · 8,409 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCombining Q-Learning and Multi-Layer Perceptron Models on Wireless Channel Quality PredictionAndrea L. Piroddi, Maurizio TorregianiOne of the most complex challenges that wireless communication systems will face in the coming years is the management of the radio resource. In the next years, the growth of mobile devices, forecast (CISCO, 2020), will lead to the coexistence of about 8.8 billion mobile devices with a growing trend for the following years. This scenario makes the reuse of … …American Journal of Engineering and Applied Sciences, Vol. 14, Issue 1 · 10 Mar 2021 · 6,761 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSymbol Timing Estimation in Multiband Orthogonal Frequency Division Multiplexing based Ultrawide band SystemM. N. Suresh, S. J. Thiruvengadam, V. AbhaikumarProblem statement: The Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) Based Ultra Wideband system (UWB) is highly susceptible to symbol timing error. Symbol timing estimation in MB-OFDM based UWB is difficult due to the presence of strongest path at delayed instant. Approach: Symbol timing estimation has two steps namely a coarse estimation and a fine estimation. In this study, a maximum … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 10 Feb 2012 · 7,101 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Return-Stroke of Lightning Current, Source of Electromagnetic Fields (Study, Analysis and Modelling)Dib Djalel, Haddouche Ali, Chemam FayçalIn this study we present and analysis of the return-stroke lightning current and described their models which existing in the literature by several authors for the evaluation of radiated electromagnetic fields and modelling the coupling with electrical systems based on the calculation of induced voltages. The objective of this work is to take part in the improvement of the coordination … …American Journal of Applied Sciences, Vol. 4, Issue 1 · 30 Apr 2007 · 7,546 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,393 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel River Meander Migration and Cutoff Model: A New PerspectiveYoussef Ismail HafezAccurate prediction of river meander migration is crucial for effective river management and operation, particularly in light of climate changes and human-induced interventions. Existing models often rely on single-equation approaches, such as bank erosion rate versus excess bank velocity or excess bank shear stress, which limit their ability to comprehensively capture the complex dynamics of meander evolution. This study presents … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 21 Mar 2025 · 7,683 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Comprehensive Review of Post-Quantum Cryptography AlgorithmsSamandeep Kaur, Jaswinder SinghThe development of quantum computing has been rapid, and an existential threat to computational hardness assumptions that underlie today's public-key cryptography has been encountered. This manuscript is a complete and thoroughly organized review of Post-Quantum Cryptography (PQC), discussing the mathematical concepts, complexity, and mechanisms of the algorithms that underpin quantum-safe security infrastructures. Rather than the principles of quantum mechanics, the … …Journal of Computer Science, Vol. 22, Issue 9 · 25 Sep 2026 · 723 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractXAI_MLPCNN: A Novel Explainable AI-Based Deep Learning Framework for Stress IdentificationFateh Bahadur Kunwar, Rakesh Kumar Yadav, Hitendra Singh, Nitin TripathiOver the past ten years, there has been a lot of emphasis focusedon the development of Artificial Intelligence (AI) and Machine Learning(ML)-based mental health treatments. To increase practitioners' and patients'trust in AI applications, AI systems need to explain their actions. This iscalled Explainable AI (XAI). While significant progress has been achievedin stress prediction models, XAI has not advanced as much. … …Journal of Computer Science, Vol. 21, Issue 5 · 6 May 2025 · 6,161 accessesView PDFCite