NeTS: Small: Smart Interference Management for Wireless Internet of Things

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Wireless Internet of Things (W-IoT) consists of billions of wireless devices, whose number is increasing at half a billion each year. These wireless devices have strong wireless communications and networking capabilities and have brought in huge amounts of data traffic over the airwaves. When multiple different devices are transmitting at the same time, there will be interference at the receivers, which could severely distort received signals and make them undecodable. To mitigate interference, many of the existing standards focus on interference avoidance, i.e., restricting to only one device transmitting at a time. This avoidance approach has poor throughput performance when wireless traffic volume in W-IoT becomes heavy. This project proposes a new approach to mitigate interference by exploiting advanced interference management (IM) techniques and programmability of new radio hardware. This approach has the potential to offer much higher throughput than existing methods. The success of this project will offer a revolutionary approach for IM in the W-IoT and offer new knowledge and methodology for future research on IM in W-IoT. New education materials will be developed and special programs to broaden participation by female and underrepresented students are planned through Wireless@VT summer symposium. A fundamental problem to ensure that data can be smoothly transported in the W-IoT is how to manage interference effectively. Recent advances in IM have introduced a number of new techniques to exploit interference rather than avoiding it. On a separate front, advances in field-programmable hardware and software-defined radios allow many physical and link layer algorithms to be programmable on the fly. Capitalizing on these two trends, this project investigates the feasibility of making IM techniques programmable at a mobile device so that an optimal IM algorithm can be chosen and programmed in real time based on the underlying communications scenarios. This project aims to take concrete steps to realize this vision by focusing on the following research topics: (1) gain fundamental understanding of programmable IM algorithms, (2) design innovative new IM algorithms with much improved capabilities and fewer limitations, (3) provide a roadmap for optimal deployment of programmable IM in the W-IoT. System building and experimentation are embedded into each component of this project. An array of advanced IM algorithms will be implemented on the WARP platform and Virginia Tech CORNET testbed.