{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/72011"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/72011","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Coding and Equalization for Radio Channels","abstract":"Many communications channels are appropriately modeled as frequency-selective and linear, and such channels introduce intersymbol interference. Equalization can be employed for such channels if the time variation is slow. In this thesis, three equalization methods which are compatible with trellis codes are considered: maximum-likelihood sequence estimation (MLSE), reduced-state sequence estimation (RSSE), and combined minimum-mean-square error decision-feedback equalization (MMSE-DFE) and Viterbi decoding.","abstract_html":"Many communications channels are appropriately modeled as frequency-selective and linear, and such channels introduce intersymbol interference. Equalization can be employed for such channels if the time variation is slow. In this thesis, three equalization methods which are compatible with trellis codes are considered: maximum-likelihood sequence estimation (MLSE), reduced-state sequence estimation (RSSE), and combined minimum-mean-square error decision-feedback equalization (MMSE-DFE) and Viterbi decoding.","abstract_has_math":false,"creators":["Frank, Colin David"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["Pursley, Michael B."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-16T22:23:17Z","date_published":"2014-12-16T22:23:17Z","updated_at":"2026-07-22T22:26:06Z","subjects":["Engineering, Electronics and Electrical"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI9411628"],"render_values":[{"text":"(UMI)AAI9411628","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/72011","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Pursley, Michael B."]},{"key":"dc:creator","label":"Author","values":["Frank, Colin David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-16T22:23:17Z","10000-01-01","1993"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Electronics and Electrical"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/72011","(UMI)AAI9411628"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Many communications channels are appropriately modeled as frequency-selective and linear, and such channels introduce intersymbol interference. Equalization can be employed for such channels if the time variation is slow. In this thesis, three equalization methods which are compatible with trellis codes are considered: maximum-likelihood sequence estimation (MLSE), reduced-state sequence estimation (RSSE), and combined minimum-mean-square error decision-feedback equalization (MMSE-DFE) and Viterbi decoding.","It is well-known that the union bound on the probability of error for maximum-likelihood decoding can be formulated as the solution of a system of linear equations. For many channels and codes of interest, this system of equations is too large to solve directly. An iterative method is presented for computing an upper bound on the union bound for the probability of error. Reduced-state sequence estimation is an attractive reduced-complexity alternative to MLSE. An approximation to the union bound for RSSE is also formulated as the solution of a system of linear equations, and the iterative method employed for MLSE can be applied.","Combined MMSE-DFE and Viterbi decoding is also a reduced-complexity decoding algorithm. Previous investigations of this algorithm have focused on trellis codes with one symbol per branch. We consider implementations of the algorithm compatible with trellis codes having multiple symbols per branch. Approximations for the union bound on the probability of error are presented. Simulation results indicate that MMSE-DFE with Viterbi decoding can yield better performance than a reduced-state decoder having the same number of states.","Made available in DSpace on 2014-12-16T22:23:17Z (GMT). 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In this thesis, three equalization methods which are compatible with trellis codes are considered: maximum-likelihood sequence estimation (MLSE), reduced-state sequence estimation (RSSE), and combined minimum-mean-square error decision-feedback equalization (MMSE-DFE) and Viterbi decoding.","It is well-known that the union bound on the probability of error for maximum-likelihood decoding can be formulated as the solution of a system of linear equations. For many channels and codes of interest, this system of equations is too large to solve directly. An iterative method is presented for computing an upper bound on the union bound for the probability of error. Reduced-state sequence estimation is an attractive reduced-complexity alternative to MLSE. An approximation to the union bound for RSSE is also formulated as the solution of a system of linear equations, and the iterative method employed for MLSE can be applied.","Combined MMSE-DFE and Viterbi decoding is also a reduced-complexity decoding algorithm. Previous investigations of this algorithm have focused on trellis codes with one symbol per branch. We consider implementations of the algorithm compatible with trellis codes having multiple symbols per branch. Approximations for the union bound on the probability of error are presented. Simulation results indicate that MMSE-DFE with Viterbi decoding can yield better performance than a reduced-state decoder having the same number of states.","Made available in DSpace on 2014-12-16T22:23:17Z (GMT). No. of bitstreams: 1 9411628.pdf: 2831545 bytes, checksum: 22f209a520bf3bb8fe5ec61a0c720bce (MD5) Previous issue date: 1993","Embargo set by: Seth Robbins for item 72177 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","82 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1993."],"dc:identifier":["http://hdl.handle.net/2142/72011","(UMI)AAI9411628"],"dc:subject":["Engineering, Electronics and Electrical"],"dc:title":["Coding and Equalization for Radio Channels"],"dc:type":["text"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:06Z"}