A New Paradigm of Radio Resource Management for Future Wireless Communication Networks Integrating Crowd Intelligence

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Wireless communications have been rapidly penetrating our daily life. It is expected that by 2020, the volume of mobile data will be 1000 times higher than today, and between 10 and 100 times more connected devices. To meet this ever-increasing demand on wireless services, it is critical to manage scarce radio resources in a more efficient way in order to maximize the overall network capacity. The emerging trend of wide deployment of smart devices, such as smart phones, provides opportunities for achieving this goal by facilitating network management through offering crowd intelligence, which includes devices' capabilities in communication, computation, and sensing. However, “How to make full use of such crowd intelligence through suitably designed resource allocation algorithms?” and “How to encourage the participation of selfish mobile devices in network management?” are two key questions we have to answer before we can successfully take advantage of this opportunity.******My research program plans to address the aforementioned questions through studying and developing novel radio resource management techniques for future device-centric and content-centric wireless networks through the integration of crowd intelligence. Together with my HQP, we plan to address two critical open questions, including the development of strategies for proactive scheduling (a new feature introduced by crowd intelligence) based on predicted future information, and incentive mechanism design to encourage the participation of selfish smart devices in network management while at the same time preventing strategic behaviors, such as untruthfulness, from them. Research emphases will be put on addressing challenges raised from practical applications, including potential prediction errors, hierarchy resource management involving multiple entities, multi-dimensional resource allocation, limitation on resource availability, dynamic network environments, and computational complexity. The key tasks in this research involve: 1) development of novel radio resource management algorithms/protocols; 2) mathematical modeling and analyses; and 3) performance evaluation by analysis and simulation.******The proposed research will achieve breakthroughs in wireless communication network technology, is significant to foster a vital competitive edge for Canadian Information and Communication Technology industry in the international market place, and will result in significant benefits to Canadian users, including new wireless services and improved quality of experience.