NeTS: Small: Spatial Spectrum Sensing-Based Device-to-Device (D2D) Networks

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The continuing growth of mobile data applications is expected to trigger a large increase in mobile traffic over the next decade. Direct device-to-device (D2D) communications between user devices that offload cellular network traffic has a great potential to be an integral part of the solution to address this mobile data challenge. In this project, the researchers will introduce a novel spectrum access model, called sensing-based D2D communication, to significantly improve the overall network spectral-efficiency of a mobile broadband network. In sensing-based D2D, users utilize spatial spectrum sensing to explore temporal and spatial spectrum transmission opportunities within the underlying cellular network bands. Equipped with spatial spectrum sensing, these users can efficiently utilize the available non-occupied cellular spectrum while providing enough protection to legacy base-station-to-device users. This project will result in a new enabling technology for future mobile broadband networks and will also effectively enrich educational materials by providing software and hardware-based implementation and experimental activities.The research project has three interconnected thrusts. In the first thrust, a comprehensive framework for both theoretical analysis and practical design of sensing-based D2D that connects the user-driven spatial spectrum sensing to the overall network performance will be developed, using detection theory and stochastic geometry. In the second thrust, optimal system design and resource allocation of sensing-based D2D will be identified. Existing techniques, such as distributed caching and millimeter wave communications, will be integrated into sensing-based D2D. In the third thrust, the performance of the developed schemes will be evaluated using both software and hardware test-beds to obtain ideas on real-world performance. The key aspect of the proposed research is that the success of the project will lead to a big shift from currently popular design methodologies used for wireless networks and can provide a comprehensive response to mobile data growth challenge under realistic system assumptions.