The problem of integrated cognition devices belongs to a multi-disciplinary area of advanced 5G and beyond networks. The multi-disciplinary focusing on cognitive models at Base Transceiver Stations (BTS) and Mobile Switching Networks (MSN), such as system architectures, Device Sensors, computing techniques, computation intelligence algorithms, mobile devices, Multiplexing devices, helps to reveal a broader and deeper understanding of system architecture and signal processing are part of everyday life and society. Over the past decades many cognitive architectures have been proposed and steadily developed, based on different approaches and computational intelligence methodologies for the network up-gradations, but still current cognitive architectures are far from the goal of covering the requirements for general intelligence in the area of Advanced networks like 5G and beyond wire/wireless Networks. Recent research in the area of evolutionary computational algorithms and genetic programming is used in this study as an inspiration for developing the new version of integrated cognitive architecture devices for advanced communication networks are the knowledge applied to the architecture as well for Industry 4.0 requirements.
A cognitive architecture models and computing algorithms specifies the underlying infrastructure for an intelligent communication networks. Briefly, architecture includes those aspects of developments in Latest BTS, MSN, computing algorithms and Computational intelligent techniques that are constant over time and across different application domains like Cognitive Radio Networks, Software Defined Networks and all wireless Adhoc Networks. The cognitive devices must be have the capacity typically include, the short-term and long-term memories that store content about the user’s information, nodes information, computational evolutionary algorithms, and knowledge about data transmission along with the speed of the Network transmissions. The advanced on chip boards, Artificial Intelligence, Deep Learning and Machine Learning models are expecting to give the solutions for the problems involved in the advanced wireless networks.
This special issue aims to address the various issues on cognitive architectures, computational intelligence algorithms like Hardware Description Languages, Signal processing, Communication devices, Artificial Intelligence (AI) algorithms, Machine Learning, Deep Learning on 5G and beyond Networks and the papers contributed high quality theoretical and practical works. The proposed submissions and presentations should be original and unpublished works.
Topics of interest include, but are not limited to:
- Cognitive Radio networks
- Ad Hoc and peer to peer network models
- Peer to Peer devices and routing algorithms
- Software Defined Radio Networks
- Analog/Digital Signal Processor Architectures for network devices
- Advanced Analog/Digital Circuit Architectures
- Advanced script languages programs for Network devices
- Advanced Device sensors architectures/computations
- Computing Algorithms for Networking
- Cognitive architectures in communication devices
- Machine Learning techniques for Cognitive Systems/Devices
- High speed computational algorithms for data transmission
- Cognitive architecture for high speed signal transmission
- Cognitive Adaptive Systems
- Quantum and Fuzzy Computing in cognitive systems
- Analog/Digital Signal Processing application algorithms
- Digital Filter techniques for advanced signal processing
Manuscript Submission Deadline: February 10, 2021
Notification for decision: April 10, 2021
Revision Due: May 30, 2021
Announcement of Acceptance by Guest Editor: June 30, 2021
Final Manuscript Due: July 30, 2021
Dr. Anil Kumar Budati,
Dept. of ECE, GRIET (Autonomous),
E-mail: firstname.lastname@example.org; email@example.com
Dr. George Ghinea
Department of Computer Science
Brunel University London
Dr. Dileep Kumar Yadav
Department of CSE,
Greater Noida, Uttar Pradesh, India.
Dr. R. Hafeez Basha
CEO, Basha Research Corporation
(CEO & Government Liaison) ,
Station-H Corporation (Non-Profit)
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