Special Issue On: Optimization of Modelling & Simulation in Wireless Networks for Interference Management of Dense Networks

Submission Due Date: August 10, 2023

Proposal Overview: Dense wireless environments strain network capacity and quality due to severe co-channel interference. Optimizing modelling and simulation frameworks is essential for evaluating and mitigating these effects. By integrating advanced interference models with multi-objective optimization algorithms, such as genetic algorithms, particle swarm optimization, and reinforcement learning, researchers can fine-tune power control, channel allocation, and beamforming strategies. High-fidelity simulators incorporating stochastic user behavior, spatial traffic distributions, and hardware impairments enable scalable “what-if” analyses, while real-time emulation platforms facilitate validation under realistic dynamics. This Special Issue aims to gather contributions that advance robust modelling and simulation tools to drive effective interference management, enhancing throughput, reliability, and latency in next-generation dense networks. Potential Topics: • Metaheuristic Optimization of Power Control Models • Machine Learning–Augmented Interference Prediction in Large-Scale Simulations • Cross-Layer Co-Simulation Frameworks for Joint Scheduling and Interference Mitigation • Stochastic Geometry–Based Models with Optimized Parameter Estimation • Reinforcement Learning–Driven Beamforming in Ultra-Dense Networks • Hybrid Analytical–Simulation Approaches for Fast “What-If” Interference Analysis • Scalable GPU-Accelerated Simulators for Real-Time Interference Optimization • Multi-Objective Optimization of Spectrum Allocation under Dense Deployment • Edge-Cloud Co-Simulation Architectures for Distributed Interference Management • Adaptive Dense Network Topology Modelling with Optimized Node Placement Important Dates: Deadline for Submission: 15 April 2026 Notification to Authors: 15 May 2026 Revised Paper Submission: 20 July 2026 Acceptance Deadline: 15 September 2026

This Special Issue seeks original, high-quality submissions in the domain of creations in new security and privacy methods, a significant area of research in deep learning-assisted intelligent HCI. We welcome submissions addressing scalability and sustainability for real-world applications and also encourage research that investigates new emerging sensing technologies still at the proof-of-concept stage.

Topics of interest include but are not limited to, the following:

• Employing deep learning techniques for improving gesture recognition in HCI
• Text categorization Based on Deep Learning: A Systematic Analysis
• A Decentralised System for Human-Computer Interaction in IoT Applications: Ubiquitous Learning
• An overview of vision-based human action recognition and associated practical challenges
• Computer service supplier social media advertising: a concept-linking mining technique analyses
• Virtual and augmented reality human-computer interaction using intelligent deep learning models
• Multimodal Human-Computer Interaction on Several Technologies with Artificial System
• Deep Learning assisted HCI systems for disease diagnosis in 5G-enabled eHealth systems
• Intelligent System for Heterogeneous Human-Computer Interaction on Multiple Platforms
• Deep learning for resolving the granular task ambiguity in HCI systems
• HCI-based on emotion-infused deep learning and neural network systems

Tentative Timeline for this Special Issue:

Submission deadline  :           February 10, 2024

Author notification     :           April 30, 2024

Revised papers due    :           June 30, 2024

Final notification        :           August 30, 2024

The Publication of the special issue will as per the policy of journal

Guest Editor Information:

Dr. Jungpil Shin [Managing Guest Editor]

Professor,

School of Computer Science and Engineering,

The University of Aizu,

Aizuwakamatsu, Japan

Email: jpshin@u-aizu.ac.jp, jpshin.uoa@gmail.com 

Google Scholar: https://scholar.google.com/citations?user=x8__gM4AAAAJ&hl=ja&oi=ao

Biography: Dr. Jungpil Shin is a professor of School of Computer Science and Engineering, The University of AIZU and Supervisor of Pattern Processing Lab, The University of AIZU. He is serving to the University of AIZU as an academician since 1999. His current research interests are pattern recognition, HCI (Human Computer Interaction), image processing, computer vision, and medical diagnosis. He is currently doing research on developing algorithms and systems for non-Touch input interfaces to recognize and identify the Human and Gesture, Non-touch character input system based on hand tapping gestures, Gesture based non-touch flick character input system, automatic diagnosis and clinical evaluation of neurological movement disorders disease, lung disease prediction and diagnosis using advanced image processing and machine intelligence techniques.

Dr. Md. Al Mehedi Hasan [Co-Guest Editor]

Professor,

Dept. of Computer Science and Engineering,

Rajshahi University of Engineering and Technology,

Rajshahi, Bangladesh

Email: mehedi_ru@yahoo.com

Google Scholar: https://scholar.google.com/citations?user=kMspjFIAAAAJ&hl=en

Biography: Md. Al Mehedi Hasan received his B.Sc. degree in computer science and engineering from the University of Chittagong, Bangladesh, and the Combined M.S. and Ph.D. degree in electrical engineering from the University of Ulsan, Korea, in 2009 and 2019, respectively. From 2012 to 2014 he worked as a software engineer in two different leading software development companies in Bangladesh. At present, he is with the American International University - Bangladesh (AIUB) as an Assistant Professor in the Department of Computer Science and Engineering. His current research interests include mobile network optimization, energy-efficient mobile communication, mobility management, traffic offloading, and load balancing.

Dr. Yong Seok Hwang [Co-Guest Editor]

Holodigilog Human Media Research Center (HoloDigilog),

Nano Device Application Center (NDAC),

Kwangwoon University, Seoul, Korea

Email: thestone@kw.ac.kr

Google Scholar: https://scholar.google.com/citations?user=xem3aGwAAAAJ&hl=en&oi=sra

Biography: Dr. Yong Seok Hwang received his Dept. of Electronics Engineering, Pusan National University, Pusan, Korea in 2004. He completed his B.Sc., and M.Sc., from the Dept. of Electronics Engineering Pukyong National University, Pusan, Korea. He is currently working as Professor in Nano Device Application Center (NDAC), Kwangwoon University, Seoul, Korea. His research interest include Hologram image processing, Machine learning, human-computer interaction, non-touch interfaces, human gesture recognition, Digital therapeutics for autism diagnosis.