{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/75455"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/75455","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"A super-nyquist architecture for rateless underwater acoustic communication","abstract":"Oceans cover about 70 percent of Earth's surface. Despite the abundant resources they contain, much of them remain unexplored. Underwater communication plays a key role in the area of deep ocean exploration. It is also essential in the field of the oil and fishing industry, as well as for military use. Although research on communicating wirelessly in the underwater environment began decades ago, it remains a challenging problem due to the oceanic medium, in which dynamic movements of water and rich scattering are commonplace. In this thesis, we develop an architecture for reliably communicating over the underwater acoustic channel. A notable feature of this architecture is its rateless property: the receiver simply collects pieces of transmission until successful decoding is possible. With this, we aim to achieve capacity-approaching communication under a variety of a priori unknown channel conditions. This is done by using a super-Nyquist (SNQ) transmission scheme. Several other important technologies are also part of the design, among them dithered repetition coding, adaptive decision feedback equalization (DFE), and multiple-input multiple-output (MIMO) communication. We present a complete block diagram for the transmitter and receiver architecture for the SNQ scheme. We prove the sufficiency of the architecture for optimality, and we show through analysis and simulation that as the SNQ signaling rate increases, the SNQ scheme is indeed capacity-achieving. At the end, the performance of the proposed SNQ scheme and its transceiver design are tested in physical experiments, whose results show that the SNQ scheme achieves a significant gain in reliable communication rate over conventional (non-SNQ) schemes.","abstract_html":"Oceans cover about 70 percent of Earth&#x27;s surface. Despite the abundant resources they contain, much of them remain unexplored. Underwater communication plays a key role in the area of deep ocean exploration. It is also essential in the field of the oil and fishing industry, as well as for military use. Although research on communicating wirelessly in the underwater environment began decades ago, it remains a challenging problem due to the oceanic medium, in which dynamic movements of water and rich scattering are commonplace. In this thesis, we develop an architecture for reliably communicating over the underwater acoustic channel. A notable feature of this architecture is its rateless property: the receiver simply collects pieces of transmission until successful decoding is possible. With this, we aim to achieve capacity-approaching communication under a variety of a priori unknown channel conditions. This is done by using a super-Nyquist (SNQ) transmission scheme. Several other important technologies are also part of the design, among them dithered repetition coding, adaptive decision feedback equalization (DFE), and multiple-input multiple-output (MIMO) communication. We present a complete block diagram for the transmitter and receiver architecture for the SNQ scheme. We prove the sufficiency of the architecture for optimality, and we show through analysis and simulation that as the SNQ signaling rate increases, the SNQ scheme is indeed capacity-achieving. At the end, the performance of the proposed SNQ scheme and its transceiver design are tested in physical experiments, whose results show that the SNQ scheme achieves a significant gain in reliable communication rate over conventional (non-SNQ) schemes.","abstract_has_math":false,"creators":["He, Qing, Ph. D. Massachusetts Institute of Technology"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Uri Erez."],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-22T22:22:04Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. 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