Special Issues
Table of Content

Intelligent Computing Techniques for Communication Systems

Submission Deadline: 27 September 2021 (closed) View: 1

Guest Editors

Dr. Nitish Pathak, Guru Gobind Singh Indraprastha University (GGSIPU), India.
Prof. Joel J. P. C. Rodrigues, Federal University of Piauí (UFPI), Brazil.
Dr. Karan Singh, Jawaharlal Nehru University (JNU), India.
Ms. Neelam Sharma, Guru Gobind Singh Indraprastha University (GGSIPU), India.


Intelligent Computing Techniques in communication systems will facilitate many new features in network management and operations. Artificial Intelligence, Intelligent Computing Techniques, IoT in Communication Systems and Deep Learning are offering practical tools for many engineering applications. Recent Intelligent Computing Techniques are giving unexpected solutions for Wireless network applications. Wireless network applications, such as real-time traffic data, sensor data from driverless cars, or entertainment streaming recommendations, generate enormous quantities of data for real-time collection and processing. These requirements can only be met through the integration of artificial intelligence (AI) and deep learning techniques in wireless infrastructure and end-user devices. Fifth-generation (5G) and beyond communication systems are expected to provide services with massive connectivity, ultra-low latency, extremely high security, extremely low energy consumption, and ultra-high data-rate. The varying IoT infrastructures (e.g., cloud, edge, fog) and the limitations of the communication protocols in transmitting/receiving messages become the barriers in creating an intelligent IoT system. These barriers prevent current intelligent communication applications to adaptively learn from other multimedia communication systems.


The objective of this Special issue is to explore Intelligent Computing Techniques to address practical challenges in wireless networks. We hope to bring researchers and academics together to present their latest work on network modelling and architecture, networking applications, security and privacy, load balancing, and various challenges related to the design of future wireless networks using AI and deep learning methods.

In this thematic issue, we solicit the submission of high-quality original research and articles closely related to the following topics, particularly interdisciplinary submissions that bring together next generation Intelligence of Things, IoT security, 5G and IoT for communication systems, social networks, delay tolerant networks, wireless sensor networks, vehicular networks, and other new trend topics about wireless communications and networking. We hope that this Special Issue helps identify promising directions and future trends for those seeking to contribute to the future of the Internet of Things in communication systems.


We seek original and high-quality submissions on, but not limited to, one or more of the following topics:

• Intelligent Computing Techniques for communication systems

• Innovative intelligent computing architecture/algorithms for wireless networks

• Edge computing using AI for QoS provisioning in wireless networks

• The effectiveness of combining 6G and IoT for communication systems

• Novel algorithms, models, frameworks, and platforms in big-data-driven IoT for communication systems

• Resource allocation for shared/virtualized networks using machine learning

• AI-based resource allocation, optimization and energy-efficient networking techniques

• AI-driven cloud/fog-assisted wireless communications

• Big-data intelligent analytic frameworks for networking data

• Tools and frameworks for designing, deploying, and maintaining intelligent IoT networks in communication systems

• Deep learning methods for applications in object detection and identification, object tracking, human action recognition, cross-modal and multimodal data analysis

• High performance Computing systems for applications in Autonomous driving, Healthcare and recommendation

• AI Role, techniques and optimization algorithms for industrial-level applications


• 5G,6G and Wireless Sensor Networks
• Intelligent Computing Techniques
• Internet of things in communication systems
• IoT in Wireless communications and networks
• QoS provisioning in wireless networks

Published Papers

  • Open Access


    A New Handover Management Model for Two-Tier 5G Mobile Networks

    Mohammad Arifin Rahman Khan, Mohammed Golam Kaosar, Mohammad Shorfuzzaman, Kire Jakimoski
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5491-5509, 2022, DOI:10.32604/cmc.2022.024212
    (This article belongs to the Special Issue: Intelligent Computing Techniques for Communication Systems)
    Abstract There has been an exponential rise in mobile data traffic in recent times due to the increasing popularity of portable devices like tablets, smartphones, and laptops. The rapid rise in the use of these portable devices has put extreme stress on the network service providers while forcing telecommunication engineers to look for innovative solutions to meet the increased demand. One solution to the problem is the emergence of fifth-generation (5G) wireless communication, which can address the challenges by offering very broad wireless area capacity and potential cut-power consumption. The application of small cells is the… More >

  • Open Access


    Sum Rate Maximization-based Fair Power Allocation in Downlink NOMA Networks

    Mohammed Abd-Elnaby
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5099-5116, 2022, DOI:10.32604/cmc.2022.022020
    (This article belongs to the Special Issue: Intelligent Computing Techniques for Communication Systems)
    Abstract Non-orthogonal multiple access (NOMA) has been seen as a promising technology for 5G communication. The performance optimization of NOMA systems depends on both power allocation (PA) and user pairing (UP). Most existing researches provide sub-optimal solutions with high computational complexity for PA problem and mainly focuses on maximizing the sum rate (capacity) without considering the fairness performance. Also, the joint optimization of PA and UP needs an exhaustive search. The main contribution of this paper is the proposing of a novel capacity maximization-based fair power allocation (CMFPA) with low-complexity in downlink NOMA. Extensive investigation and… More >

  • Open Access


    Network Quality Assessment in Heterogeneous Wireless Settings: An Optimization Approach

    Sultan H. Almotiri, Mohammed A. Al Ghamdi
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 439-455, 2022, DOI:10.32604/cmc.2022.021012
    (This article belongs to the Special Issue: Intelligent Computing Techniques for Communication Systems)
    Abstract The identification of an effective network which can efficiently meet the service requirements of the target, while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless medium. The wrong selection can contribute to unwanted situations like frustrated users, slow service, traffic congestion issues, missed and/or interrupted calls, and wastefulness of precious network components. Conventional schemes estimate the handoff need and cause the network screening process by a single metric. The strategies are not effective enough because traffic characteristics, user expectations, network terminology and other essential device metrics are… More >

  • Open Access


    RSS-Based Indoor Localization System with Single Base Station

    Samir Salem Al-Bawri, Mohammad Tariqul Islam, Mandeep Jit Singh, Mohd Faizal Jamlos, Adam Narbudowicz, Max J. Ammann, Dominique M. M. P. Schreurs
    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5437-5452, 2022, DOI:10.32604/cmc.2022.020781
    (This article belongs to the Special Issue: Intelligent Computing Techniques for Communication Systems)
    Abstract The paper proposes an Indoor Localization System (ILS) which uses only one fixed Base Station (BS) with simple non-reconfigurable antennas. The proposed algorithm measures Received Signal Strength (RSS) and maps it to the location in the room by estimating signal strength of a direct line of sight (LOS) signal and signal of the first order reflection from the wall. The algorithm is evaluated through both simulations and empirical measurements in a furnished open space office, sampling 21 different locations in the room. It is demonstrated the system can identify user’s real-time location with a maximum More >

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