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June 2021

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Special Issue on Artificial Intelligence for Autonomous Vehicular Communication Networks - IEEE VT Magazine (Impact Factor: 7.921)
by Javier Manuel Gozalvez Sempere 23 Jun '21

23 Jun '21

********************************************************************************** Special Issue on Artificial Intelligence for Autonomous Vehicular Communication Networks - Call for Papers - IEEE VT Magazine (Impact Factor: 7.921) Manuscript Submission by: 29 July 2021 http://ieeevtc.org/vtmagazine/specisu--AI-AVCNet.php ********************************************************************************** With the advancement of sensing, communications and networking, autonomous vehicles and unmanned aerial vehicles (UAVs) are expected to play a vital role in a variety of areas, including healthcare, industry 4.0, smart farming and agriculture, logistics, transportation, and public safety. Together with the upcoming B5G/6G technologies, connected vehicular systems will become more ubiquitous and practical. Artificial intelligence (AI) and machine learning (ML) techniques can provide significant benefits towards automating the tasks of sensing, computing, and communicating in vehicular communication networks. To achieve real-time perception and autonomous control, computing and communications in AI-enabled vehicular communication networks will be more complex and heterogeneous than before. Security and privacy will be extremely challenging, due to certain characteristics of these complex systems (high mobility of nodes and unreliable link connectivity) combined with vulnerable end devices, limited resources, and heterogeneous networking. For example, data collected from sensors for AI-based approaches pose new security threats. ML models trained at edge devices may suffer from various malicious attacks, but distributed ML algorithms are essential in vehicular communication networks with multiple self-organizing vehicles for control that is both scalable and low-latency. The objective of this special issue is to bring together state-of-the-art innovations and research activities (from both academia and industry) to explore AI-based autonomous vehicular communication network technologies. Topics of interest include but are not limited to: - Edge learning in autonomous vehicular communication networks - Deep learning and distributed machine learning for vehicular communication networks - AI techniques for radio environment awareness in vehicular networks - Reinforcement learning for network decision making, network control, and management - Reinforcement learning for self-organized vehicular communication networks - Predictive QoS in autonomous vehicular communication networks - Privacy-preserving machine learning for autonomous vehicular communication networks - Blockchain-enabled autonomous vehicular communication networks - Joint design of AI-based communication and sensing in vehicular communication networks - AI-driven energy-efficient architectures/solutions for autonomous vehicular communication networks - Fault detection and self-healing in vehicular communication networks - New AI-based intelligent transportation systems and services in vehicular communication networks All manuscripts should contain state-of-the-art material presented in a tutorial or survey style, and must adhere to IEEE VTM guidelines at http://www.ieeevtc.org/vtmagazine/submission.php. Authors should submit a PDF version of their manuscript to (select Special Issue when submitting) http://mc.manuscriptcentral.com/vtm-ieee Important Dates * Manuscript Submission by: 29 July 2021 * First Round Reviews by: 28 October 2021 * Second Round Submissions by: 23 December 2021 * Second Round Reviews / Editorial Decision: 22 February 2022 * Final Articles by: 4 March 2022 * Publication: June 2022 Guest Editors * Li-Chun Wang, National Yang Ming Chiao Tung University, Taiwan * Haris Gaçanin, RWTH Aachen University, Germany * Dusit (Tao) Niyato, Nanyang Technological University, Singapore * Yu-Jia Chen, National Central University, Taiwan * Chun-Hung Liu, Mississippi State University, USA * Alagan Anpalagan, Ryerson University, Canada

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CFP - Special Issue on Backscatter and Reconfigurable Intelligent Surface Empowered Wireless Communications in 6G - IEEE VT Magazine (Impact Factor: 7.921)
by Javier Manuel Gozalvez Sempere 22 Jun '21

22 Jun '21

Call for Papers - Special Issue on Backscatter and Reconfigurable Intelligent Surface Empowered Wireless Communications in 6G - IEEE VT Magazine (Impact Factor: 7.921) Manuscript Submission by: 29 July 2021 Though the fifth generation (5G) mobile network system is rolled out worldwide, research attention in both academia and industry has shifted to the sixth generation (6G). Exciting new applications—such as multisensory XR applications, connected robotics and autonomous systems, and brain-computer interactions—will expect support from 6G communications. These cutting edge applications pose new challenges to the requirements of data rate, latency, connectivity density, and energy efficiency, which cannot not be tackled by current 5G technologies. The main principles of 5G technologies lie in increasing the number of antennas, migrating high frequency bands and deploying more access points. Although significant performance gains can be achieved in terms of spectrum efficiency, they have drawbacks such as high power and hardware cost, increased network maintenance cost, and excessive signal processing complexity. Hence, new transformative transmission technologies need to be developed to support these new applications and services. Due to recent advancements in micro-electro-mechanical systems (MEMS) and metamaterials, ambient backscatter communication (AmBC) and reconfigurable intelligent surface (RIS)-aided wireless communication have received extensive research attention. Unlike traditional wireless communication systems, AmBC does not need an active radio frequency (RF) component on the tag, and it can harvest energy from ambient RF sources in the radio environment. Therefore, AmBC requirements are low-cost and could be deployed ubiquitously. In addition, the RIS, which consists of a number of passive reflecting elements, can reconfigure the wireless propagation environment by carefully tuning the phase shifts of the reflecting elements, and thus can customize wireless channels based on design objectives. The RIS can be small and lightweight, enabling low-cost installation on indoor ceilings and walls, as well as street lamps. Due to these appealing advantages, AmBC and RIS have been recognized as some of the most promising techniques in 6G networks. Research on AmBC and RIS is still in its infancy. This special issue is soliciting recent contributions that address the major challenges in channel modeling, analysis, optimization, and implementation of AmBC and RIS empowered wireless communication systems. Topic of interest include but are not limited to: - Channel modelling for AmBC and/or RIS-aided wireless networks Communication-theoretic foundation and analysis of AmBC and/or RIS-aided wireless networks - Algorithms and protocol design for AmBC and/or RIS-aided wireless networks - Deployment optimization for AmBC and/or RIS-aided wireless networks - Integration of AmBC and/or RIS into emerging wireless communication applications such as wireless power transfer, mobile edge computing, physical layer security, unmanned aerial vehicle communications, etc. - Localization and sensing for AmBC and/or RIS-aided communications - Energy efficient design for AmBC and/or RIS-aided communications - Application of AmBC and/or RIS in high-frequency communications, such as mmWave/Terahertz communication and visible light communication - AI-empowered AmBC and/or RIS-aided communication systems - Testbeds, experimental measurements in AmBC and/or RIS-aided wireless communications All manuscripts should contain state-of-the-art material presented in a tutorial or survey style, and must adhere to IEEE VTM guidelines at http://www.ieeevtc.org/vtmagazine/submission.php. Authors should submit a PDF version of their manuscript to (select Special Issue when submitting) http://mc.manuscriptcentral.com/vtm-ieee Call for papers available at: http://www.ieeevtc.org/vtmagazine/specisu--6G-AmBC-RIS.php Important Dates Manuscript Submission by: 29 July 2021 First Round Reviews by: 28 October 2021 Second Round Submissions by: 23 December 2021 Second Round Reviews / Editorial Decision: 22 February 2021 Final Articles by: 4 March 2021 Publication: June 2022 Guest Editors Cunhua Pan (lead), Queen Mary University of London, UK Marco Di Renzo, Paris-Saclay University, France Chau Yuen, SUTD, Singapore Derrick Wing Kwan Ng, UNSW, Australia Ertugrul Basar, Ko University, Turkey

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