<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Adaptive Underwater Video Transmission via Software-Defined MIMO Acoustic Modems</dc:title><dc:creator>Rahmati, Mehdi; Gurney, Adam; Pompili, Dario</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Video signal transmission enables a wide range of applications in the underwater environment; such as coastal and tactical multimedia surveillance, undersea/offshore exploration, oil pipe/bridge inspection, video monitoring of geologica/biological processes from the seafloor to the air-sea interface-that all require real-time multimedia acquisition and classification. Yet, it is a challenge to achieve an efficient and reliable video transmission, due to the spectrum limitations underwater and also the error prone nature of the acoustic channel. In this paper, we propose a pairwise scheme to manage the video distortion-rate tradeoff for underwater video transmission. The proposed Multi-input Multi-output (MIMO)-based Software-Defined Acoustic Radio (SDAR) system adapts itself to meet the needs of both video compression and underwater channel in a timely manner from one hand, and keeps the overall video distortion-caused by the coder/decoder and channel-under an acceptable threshold from the other hand. The scalability of Universal Software Radio Peripheral (USRP) with high processing capabilities is exploited in the proposed structure along with the temporal, spatial and quality scalability of Scalable Video Coding (SVC) H.264/MPEG-4 AVC compression standard. Experimental results at Sonny Werblin Recreation Center, Rutgers University, as well as simulations are presented, while more experiments are in-progress to evaluate the performance of our testbed in more challenging environments such as in the Raritan River, New Jersey.</dc:description><dc:publisher/><dc:date>2018-10-01</dc:date><dc:nsf_par_id>10112874</dc:nsf_par_id><dc:journal_name>OCEANS 2018 MTS/IEEE Charleston</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation>1 to 6</dc:page_range_or_elocation><dc:issn/><dc:isbn/><dc:doi>https://doi.org/10.1109/OCEANS.2018.8604782</dc:doi><dcq:identifierAwardId>1763709</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>