Scope and Objectives

In the last two decades, cognitive radios have emerged as an efficient way to improve spectrum utilization and provide more flexibility in networking. A significant change in cognitive radio networks (CRNs) recently is putting social behaviour in the loop. Many social behaviours can be sensed and even predicted by the machine learning and artificial intelligence (AI) based smart applications. In this context, the social behaviour is a new driven force for better performance in CRNs. In addition, emerging smart applications can strongly affect social behaviour, which will be a new driven force for proposing new applications in CRNs as well. In this social behaviour driven CRNs, critical technical problems should be solved to realize the potential benefits, e.g., how to efficiently formulate and utilize human-device interactions to boost communication performance since the device holder are supposed to be mobile regularly, and how to facilitate the benefits of considering social behaviours and application characteristics from utilizing the devices’ capability of caching and computing. Another major challenge is how to sense and understand social behaviours and application characteristics. In this SIG group, we provide a platform on the development of social behaviour driven CRNs to exploit and explore new dimensions.


Dr. Li Wang, BUPT, China


Dr. Giuseppe Araniti, University Mediterranea of Reggio Calabria, Italy
Dr. Bo Bai, Huawei Technologies Co., Ltd., HongKong
Dr. Trung Q. Duong, Queen’s Uni. Belfast, UK
Dr. Yongpeng Wu, Shanghai Jiaotong University, China

Founding Members

Tommy Svensson, Chalmers University of Technology
Maurizio Murroni, University of Cagliari, Italy
Lei Chen, Georgia Southern University, USA
Alessandro Raschellà, Liverpool John Moores University, Italy
Qingzhong Liu, Sam Houston State University, USA
Antonino Orsino, Ericsson Research, Finland
Guoru Ding, Southeast University, China
Xiaojun Ruan, California State University, USA
Qing Yang, University of North Texas, USA
Massimo Condoluci, King’s College London, UK
Zhonghong Ou, Beijing University of Posts and Telecommunications, China
Kamel Tourki, Huawei, France
Chau Yuen, Singapore University of Technology and Design (SUTD), Singapore
Jakob Hoydis,Nokia-Bell-Labs,France
Symeon Chatzinotas, University of Luxembourg, Luxembourg
Miaomiao Dong, City University of Hong Kong
Tianyang Bai, Qualcomm Corporate R&D, USA
Yan Zhang, University of Oslo, Norway
Qihui Wu, Nanjing University of Aeronautics and Astronautics, China
A. Nallanathan, Queen’s Mary University of London, UK
Octavia Dobre, Memorial University, Canada
Daniel Benevides da Costa, Federal University of Ceará, Brazil
Marco Di Renzo, CNRS – CentraleSupelec – Univ Paris-Sud, France
Himal A. Suraweera, University of Peradeniya, Sri Lanka
Nghi H. Tran, University of Akron, USA
Phee Lep Yeoh, University of Sydney, Australia
Jinhong Yuan, University of New South Wales, Australia
David López-Pérez, Bell Labs Alcatel-Lucent, Ireland
George C. Alexandropoulos, Huawei Technologies France
Kyeongjin Kim, Mitsubishi Electric Research Laboratories, USA
George K. Karagiannidis, Aristotle University of Thessaloniki, Greece
Le-Nam Tran, University College Dublin, Ireland

Full Proposal