{"id":{"repo_id":"windsor","oai_identifier":"oai:uwindsor.scholaris.ca:20.500.14776/806"},"canonical_url":"https://search.dev.ndltd.org/etd/windsor/oai:uwindsor.scholaris.ca:20.500.14776/806","repository":{"repo_id":"windsor","name":"University of Windsor","base_url":"https://uwindsor.scholaris.ca/server/oai/request"},"display":{"title":"Adaptive Channel Estimation for Turbo Decoding","abstract":"A new adaptive filter is proposed for the turbo decoding on Rayleigh fading channels with noisy channel estimates. The extrinsic information generated from the turbo decoder has some priority information about the transmitted data bits, which can help us better understand the channel characters. By using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5&times10-4.","abstract_html":"A new adaptive filter is proposed for the turbo decoding on Rayleigh fading channels with noisy channel estimates. The extrinsic information generated from the turbo decoder has some priority information about the transmitted data bits, which can help us better understand the channel characters. By using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. 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The extrinsic information generated from the turbo decoder has some priority information about the transmitted data bits, which can help us better understand the channel characters. By using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5&times10-4."]},{"key":"dc:title","label":"Title","values":["Adaptive Channel Estimation for Turbo Decoding"]}]}],"canonical_facts":{"dc:contributor.advisor":["Shahrrava, Behnam (Electrical and Computer Engineering)"],"dc:creator":["GUO, YU QING"],"dc:date.accessioned":["2025-06-12 11:09"],"dc:date.available":["2012-10-26 7:16","2025-06-12T15:09:25Z"],"dc:date.issued":["2012-01-01"],"dc:description.abstract":["A new adaptive filter is proposed for the turbo decoding on Rayleigh fading channels with noisy channel estimates. The extrinsic information generated from the turbo decoder has some priority information about the transmitted data bits, which can help us better understand the channel characters. By using the soft extrinsic information after each iteration of decoding, we re-estimate the channel and the minimum mean square error (m.m.s.e.) and further update the channel reliability factor and decision variables at each iteration. Simulations show that signal to noise (SNR) gain is improved by up to about 1dB at bit error probability of 3.5&times10-4."],"dc:identifier.uri":["https://hdl.handle.net/20.500.14776/806"],"dc:language.iso":["en_CA"],"dc:rights":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:title":["Adaptive Channel Estimation for Turbo Decoding"],"dc:type":["text"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.A.Sc."],"thesis:institution_name":["University of Windsor"]},"updated_at":"2026-07-27T22:04:42Z"}