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Pinto, Andrea; Ashdown, Andrew; Bin Hassan, Tanzil; Cheng, Hai; Esposito, Flavio; Bonati, Leonardo; D'Oro, Salvatore; Melodia, Tommaso; Restuccia, Francesco (, ACM)
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Restuccia, Francesco; Blasch, Erik; Ashdown, Andrew; Ashdown, Jonathan; Turck, Kurt (, MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM))This position paper introduces a Dynamic Data Driven Open Radio Access Network System (3D-O-RAN). The key objective of 3D-O-RAN is to support congested, contested and contaminated tactical settings where multimedia sensors, application constraints and operating wireless conditions may frequently change over space, time and frequency. 3D-O-RAN is compliant with the O-RAN specification for beyond 5G cellular systems to reduce costs and guarantee interoperability among vendors. Moreover, 3D-O-RAN integrates computational, sensing, and cellular networking components in a highly-dynamic, feedback-based, data-driven control loop. Specifically, 3D-O-RAN is designed to incorporate heterogeneous data into the network control loop to achieve a system-wide optimal operating point. Moreover, 3D-O-RAN steers the multimedia sensor measurement process in real time according to the required application needs and current physical and/or environmental constraints. 3D-O-RAN uses (i) a semantic slicing engine, which takes into account the semantic of the application to optimally compress the multimedia stream without losing in classification accuracy; (ii) a dynamic data driven neural network certification system that translates mission-level constraints into technical-level constraints on neural network latency/accuracy, and occupation of hardware/software resources. Realistic use-case scenarios of 3D-O-RAN in a tactical context demonstrate system performance.more » « less
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