{"id":{"repo_id":"woods-hole","oai_identifier":"oai:darchive.mblwhoilibrary.org:1912/2751"},"canonical_url":"https://search.dev.ndltd.org/etd/woods-hole/oai:darchive.mblwhoilibrary.org:1912/2751","repository":{"repo_id":"woods-hole","name":"Woods Hole Oceanographic Institute","base_url":"https://darchive.mblwhoilibrary.org/server/oai/request"},"display":{"title":"A channel subspace post-filtering approach to adaptive equalization","abstract":"One of the major problems in wireless communications is compensating for the time-varying intersymbol interference (ISI) due to multipath. Underwater acoustic communications is one such type of wireless communications in which the channel is highly dynamic and the amount of ISI due to multipath is relatively large. In the underwater acoustic channel, associated with each of the deterministic propagation paths are macro-multipath fluctuations which depend on large scale environmental features and geometry, and micro-multipath fluctuations which are dependent on small scale environmental inhomogeneities. For arrivals which are unsaturated or partially saturated, the fluctuations in ISI are dominated by the macro-multipath fluctuations resulting in correlated fluctuations between different taps of the sampled channel impulse response. Traditional recursive least squares (RLS) algorithms used for adapting channel equalizers do not exploit this structure. A channel subspace post-filtering algorithm that treats the least squares channel estimate as a noisy time series and exploits the channel correlation structure to reduce the channel estimation error is presented. The improvement in performance of the algorithm with respect to traditional least squares algorithms is predicted theoretically, and demonstrated using both simulation and experimental data. An adaptive equalizer structure that explicitly uses this improved estimate of the channel impulse response is discussed. The improvement in performance of such an equalizer due to the use of the post-filtered estimate is also predicted theoretically, and demonstrated using both simulation and experimental data.","abstract_html":"One of the major problems in wireless communications is compensating for the time-varying intersymbol interference (ISI) due to multipath. Underwater acoustic communications is one such type of wireless communications in which the channel is highly dynamic and the amount of ISI due to multipath is relatively large. In the underwater acoustic channel, associated with each of the deterministic propagation paths are macro-multipath fluctuations which depend on large scale environmental features and geometry, and micro-multipath fluctuations which are dependent on small scale environmental inhomogeneities. For arrivals which are unsaturated or partially saturated, the fluctuations in ISI are dominated by the macro-multipath fluctuations resulting in correlated fluctuations between different taps of the sampled channel impulse response. Traditional recursive least squares (RLS) algorithms used for adapting channel equalizers do not exploit this structure. A channel subspace post-filtering algorithm that treats the least squares channel estimate as a noisy time series and exploits the channel correlation structure to reduce the channel estimation error is presented. The improvement in performance of the algorithm with respect to traditional least squares algorithms is predicted theoretically, and demonstrated using both simulation and experimental data. An adaptive equalizer structure that explicitly uses this improved estimate of the channel impulse response is discussed. The improvement in performance of such an equalizer due to the use of the post-filtered estimate is also predicted theoretically, and demonstrated using both simulation and experimental data.","abstract_has_math":false,"creators":["Nadakuditi, Rajesh Rao"],"institution":"Massachusetts Institute of Technology and Woods Hole Oceanographic Institution","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002-02","date_published":"2002-02","updated_at":"2026-07-27T22:05:12Z","subjects":["Underwater acoustics","Mathematical models"],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.1575/1912/2751"],"render_values":[{"text":"10.1575/1912/2751","href":"https://doi.org/10.1575/1912/2751","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/1912/2751","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Nadakuditi, Rajesh Rao"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2009-03-26T19:52:25Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2009-03-26T19:52:25Z"]},{"key":"dc:date.issued","label":"Date","values":["2002-02"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology and Woods Hole Oceanographic Institution"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Underwater acoustics","Mathematical models"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.1575/1912/2751"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1912/2751"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2002"]},{"key":"dc:description.abstract","label":"Abstract","values":["One of the major problems in wireless communications is compensating for the time-varying intersymbol interference (ISI) due to multipath. Underwater acoustic communications is one such type of wireless communications in which the channel is highly dynamic and the amount of ISI due to multipath is relatively large. In the underwater acoustic channel, associated with each of the deterministic propagation paths are macro-multipath fluctuations which depend on large scale environmental features and geometry, and micro-multipath fluctuations which are dependent on small scale environmental inhomogeneities. For arrivals which are unsaturated or partially saturated, the fluctuations in ISI are dominated by the macro-multipath fluctuations resulting in correlated fluctuations between different taps of the sampled channel impulse response. Traditional recursive least squares (RLS) algorithms used for adapting channel equalizers do not exploit this structure. A channel subspace post-filtering algorithm that treats the least squares channel estimate as a noisy time series and exploits the channel correlation structure to reduce the channel estimation error is presented. The improvement in performance of the algorithm with respect to traditional least squares algorithms is predicted theoretically, and demonstrated using both simulation and experimental data. An adaptive equalizer structure that explicitly uses this improved estimate of the channel impulse response is discussed. The improvement in performance of such an equalizer due to the use of the post-filtered estimate is also predicted theoretically, and demonstrated using both simulation and experimental data."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A channel subspace post-filtering approach to adaptive equalization"]}]}],"canonical_facts":{"dc:creator":["Nadakuditi, Rajesh Rao"],"dc:date.accessioned":["2009-03-26T19:52:25Z"],"dc:date.available":["2009-03-26T19:52:25Z"],"dc:date.issued":["2002-02"],"dc:description":["Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2002"],"dc:description.abstract":["One of the major problems in wireless communications is compensating for the time-varying intersymbol interference (ISI) due to multipath. Underwater acoustic communications is one such type of wireless communications in which the channel is highly dynamic and the amount of ISI due to multipath is relatively large. In the underwater acoustic channel, associated with each of the deterministic propagation paths are macro-multipath fluctuations which depend on large scale environmental features and geometry, and micro-multipath fluctuations which are dependent on small scale environmental inhomogeneities. For arrivals which are unsaturated or partially saturated, the fluctuations in ISI are dominated by the macro-multipath fluctuations resulting in correlated fluctuations between different taps of the sampled channel impulse response. Traditional recursive least squares (RLS) algorithms used for adapting channel equalizers do not exploit this structure. A channel subspace post-filtering algorithm that treats the least squares channel estimate as a noisy time series and exploits the channel correlation structure to reduce the channel estimation error is presented. The improvement in performance of the algorithm with respect to traditional least squares algorithms is predicted theoretically, and demonstrated using both simulation and experimental data. An adaptive equalizer structure that explicitly uses this improved estimate of the channel impulse response is discussed. The improvement in performance of such an equalizer due to the use of the post-filtered estimate is also predicted theoretically, and demonstrated using both simulation and experimental data."],"dc:format.mimetype":["application/pdf"],"dc:identifier.doi":["10.1575/1912/2751"],"dc:identifier.uri":["https://hdl.handle.net/1912/2751"],"dc:language.iso":["en_US"],"dc:publisher":["Massachusetts Institute of Technology and Woods Hole Oceanographic Institution"],"dc:subject":["Underwater acoustics","Mathematical models"],"dc:title":["A channel subspace post-filtering approach to adaptive equalization"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T22:05:12Z"}