Journal of Communications and Information Networks

Call for Papers

To satisfy typical scenarios and applications for the intelligent information society, a large-dimensional and autonomous network architecture that integrates space, air, ground, and underwater networks is anticipated to provide ubiquitous and unlimited wireless connectivity.

The integration of terrestrial and non-terrestrial networks within the 5G/6G is under standardization and can lead to manifold advantages, such as coverage extension and additional communication link to reinforce service reliability and scalability. Through the provision of efficient multicast/broadcast resources for data delivery, non-terrestrial networks can upgrade the performance of terrestrial networks and increase service availability everywhere.

With the development of enhanced mobile broadband, multi-Gbit/s peak rate, ultra-low latency, and massive machine-type communications, massive wireless devices with continual emergence of novel technologies are fueling a great demand for access to the radio frequency (RF) spectrum. To provide ubiquitous wireless connectivity with heterogeneous quality of experience (QoE), there is a significant spectrum crunch faced by the commercial mobile broadband users with the compelling need to get additional spectrum for the wireless broadband services. Managing this increasing demand while resolving a seemingly looming scarcity of RF spectrum imposes great challenges to develop improved spectrum usage strategies for achieving efficient use of the spectrum.

Traditional approach isolates wireless systems by dividing the spectrum into exclusively licensed bands for the guarantee of interference-free communication. However, many licensed frequency bands are underutilized while other bands are overwhelmed in practice either over time or geography, thus encouraging dynamic spectrum usage to mitigate the spectrum supply-demand gap. Spectrum collaboration is a promising strategy to autonomously collaborate and reason about how to share the RF spectrum for overcoming the low spectrum utilization. There have been some rapid advances towards the development of dynamic spectrum access through approaches such as geolocation database, cognitive communication network, software-defined radios, sub-Nyquist RF front-end, etc. Moreover, as artificial intelligence (AI) can provide human-like intelligence through learning and big data training, applying these techniques to wireless networks can promote the evolution to autonomous systems that can monitor network in real-time and quickly adjust network parameters.

Therefore, AI provides a new way to design cognitive communication networks and will be an innovate technology leading to superior performance.

The objective of this special issue is to provide a forum across academia and industry to explore recent advances, research opportunities, and technical challenges in spectrum collaboration for terrestrial and non-terrestrial networks. This special issue will bring together leading researchers to present their research in this area including novel ideas, models, methodologies, system designs and architectures, experiments and benchmarks, as well as research surveys. Authors are invited to submit original manuscripts on topics including, but not limited to:

1) Sensing and communication information theory

2) Advanced spectrum sensing and learning techniques for spectrum and energy efficiency

3) Collaborative spectrum sharing and learning technology

4) Distributed spectrum sharing, sensing and learning

5) Energy-efficient dynamic spectrum access and sharing

6) MAC and routing protocols for dynamic spectrum access

7) Security and privacy issues in spectrum access and collaboration

8) Application of AI in spectrum access and sharing

9) Geolocation databases for dynamic spectrum access and sharing

10) Spectrum management for the Internet of Things (IoT)

11) Emerging technology on machine learning for communications

12) Data-driven dynamic spectrum sharing

13) Spectrum collaboration hardware architectures and implementation

14) Experimental prototypes and results from spectrum measurement trials

Important Dates

Submission Deadline: Sept. 1, 2020

Initial Decision: Sept. 20, 2020

Revised Manuscript: Oct. 10, 2020

Final Decision: Oct. 20, 2020

Final Upload: Oct. 30, 2020

Guest Editors

Yuan Ma, Shenzhen University, China

Email: mayuan@szu.edu.cn

Zhiyong Feng, Beijing University of Posts and Telecommunications, China

Email: fengzy@bupt.edu.cn

Qihui Wu, Nanjing University of Aeronautics and Astronautics, China

Email: wuqihui2014@sina.com

Yue Gao, University of Surrey, UK

Email: yue.gao@surrey.ac.uk

Submission Guideline

All original manuscripts to JCIN should be submitted electronically through the Manuscript Central https://mc.manuscriptcentral.com/jcin

About the Guest Editors

Yuan Ma (S’15-M’17) received the B.Sc. degree (First Class Hons.) in telecommunications engineering from Beijing University of Posts and Telecommunications, Beijing, China, in 2013, and the Ph.D. degree in electronic engineering from Queen Mary University of London, London, U.K., in 2017. She is currently an Assistant Professor with the College of Information Engineering, Shenzhen University. Her research interests include cognitive and cooperative wireless networking, compressive sensing, data-driven signal processing, and spectrum analysis, detection and sharing.

Zhiyong Feng (M’08-SM’15) received her B.E., M.E., and Ph.D. degrees from Beijing University of Posts and Telecommunications (BUPT), Beijing, China. She is a professor at BUPT, and the director of the Key Laboratory of the Universal Wireless Communications, Ministry of Education, P.R.China. She is a senior member of IEEE, vice chair of the Information and Communication Test Committee of the Chinese Institute of Communications (CIC). Currently, she is serving as Associate Editors-in-Chief for China Communications, and she is a technological advisor for international forum on NGMN. Her main research interests include wireless network architecture design and radio resource management in mobile networks, spectrum sensing and dynamic spectrum management in cognitive wireless networks, and universal signal detection and identication.

Qihui Wu (SM’13) received the B.S. degree in communications engineering and the M.S. and Ph.D. degrees in communications and information systems from the Institute of Communications Engineering, Nanjing, China, in 1994, 1997, and 2000, respectively. From 2003 to 2005, he was a Post-Doctoral Research Associate with Southeast University, Nanjing. From 2005 to 2007, he was an Associate Professor with the College of Communications Engineering, PLA University of Science and Technology, Nanjing, where he was a Full Professor from 2008 to 2016. Since May 2016, he has been a Full Professor with the College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing. From March 2011 to September 2011, he was an Advanced Visiting Scholar with the Stevens Institute of Technology, Hoboken, NJ, USA. His current research interests include wireless communications and statistical signal processing, with emphasis on system design of software defined radio, cognitive radio, and smart radio.

Yue Gao (S’03–M’07–SM’13) is a Professor of Wireless Communications at Institute for Communication Systems, University of Surrey, United Kingdom. He received the Ph.D. degree from the Queen Mary University of London (QMUL), U.K., in 2007. Prof. Gao was a Lecturer, Senior Lecturer and Reader in Antennas and Signal Processing with QMUL. He currently leads a team developing fundamental research into practice in the interdisciplinary area of smart antennas, signal processing, spectrum sharing, millimetre-wave and Internet of Things technologies in mobile and satellite systems. He has published over 180 peer-reviewed journal and conference papers, 3 patents, 1 book and 5 book chapters, 3 best paper awards and Google H-index 27. He is an Engineering and Physical Sciences Research Council Fellow from 2018 to 2023. He was a co-recipient of the EU Horizon Prize Award on Collaborative Spectrum Sharing in 2016, and shortlisted for the Newton Prize on IoT systems for smart farming in 2019. He served as the Signal Processing for Communications Symposium Co-Chair for IEEE ICCC 2016, the Publicity Co-Chair for the IEEE GLOBECOM 2016, the Cognitive Radio Symposium Co-Chair for the IEEE GLOBECOM 2017, and the General Chair of the IEEE WoWMoM and iWEM 2017. He is the Chair of the IEEE Technical Committee on Cognitive Networks, the Secretary of the IEEE ComSoc Technical Committee Wireless Communication and the IEEE Distinguished Lecturer of the Vehicular Technology Society. He is an Editor for the IEEE INTERNET OF THINGS JOURNAL, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY and IEEE TRANSACTIONS ON COGNITIVE NETWORKS.