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SUMMARY:Guillem Reus Muns' PhD Proposal Review
DESCRIPTION:Location: ISEC 332 \n“AI for communications and sensing in RF environments” \nAbstract: \nThe recent growth of Internet of Things (IoT)\, as well as other new revolutionary applications utilizing wireless spectrum are leading the way towards realization of next generation wireless systems that jointly utilize communications and sensing. However\, such systems offer many degrees of freedom\, and optimizing them for a specific task is difficult to accomplish with deterministic and classical approaches. For this reason\, data-driven and AI-based methods have been pursued actively by the research community\, as they are able to find solutions that often come close to or exceed the performance of the deterministic counterparts with a fractional execution complexity. This thesis presents\, through real systems and with experimental validation\, our progressive efforts in three broad areas\, where AI enables the operation of aerial and terrestrial systems that combine sensing and communications. This dissertation explores the following key use cases with distinct contributions made in each: \ni) Sensing-aided communications for air and ground systems. First\, we present a UAV communication method that defines constellation points in space that map to transmitter frequency bands and are detected at the Base Station using millimeter wave sensors. Second\, we explore alternative vehicle-to-infrastructure mmWave beamforming methods\, leveraging a) vehicle position and velocity estimation using in-band standard compliant 802.11ad radar and b) camera images and GPS location information.\nii) Signal classification using communication signals\, where we propose a) a UAV classification method using uniquely UAV-transmitted signals and b) an RF fingerprinting technique that improves class separation by combining triplet loss with regular classification techniques.\niii) ‘AirFC’\, an over-the-air computation method that implements fully connected neural networks inference leveraging multi-antenna systems. \nFinally\, the proposed work will address challenges in the CBRS band\, where a tiered structure is implemented to access the spectrum. Hence\, continuous sensing is needed to make sure that radar (tier 1) is not interfered by cellular systems (tier 2). Here\, we propose reusing the already existing cellular infrastructure to act as a radar detector\, which enhances their functionality to go beyond that of regular wireless communications. \nCommittee: \nProf. Kaushik Chowdhury (Advisor) \nProf. Hanumant Singh \nProf. Stratis Ioannidis
URL:https://ece.northeastern.edu/event/guillem-reus-muns-phd-proposal-review/
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