{"id":{"repo_id":"soton","oai_identifier":"oai:eprints.soton.ac.uk:206015"},"canonical_url":"https://search.dev.ndltd.org/etd/soton/oai:eprints.soton.ac.uk:206015","repository":{"repo_id":"soton","name":"University of Southampton","base_url":"https://eprints.soton.ac.uk/cgi/oai2"},"display":{"title":"Reduced-complexity near-optimal Ant-Colony-aided multi-user detection for CDMA systems","abstract":"Reduced-complexity near-maximum-likelihood Ant-Colony Optimization (ACO) assisted Multi-User Detectors (MUDs) are proposed and investigated. The exhaustive search complexity of the optimal detection algorithm may be deemed excessive for practical applications. For example, a Space-Time Block Coded (STBC) two transmit assisted K = 32-user system has to search through the candidate-space for finding the final detection output during 264 times per symbol duration by invoking the Euclidean-distance-calculation of a 64-element complex-valued vector. Hence, a nearoptimal or near-ML MUDs are required in order to provide a near-optimal BER performance at a significantly reduced complexity.<br/><br/>Specifically, the ACO assisted MUD algorithms proposed are investigated in the context of a Multi-Carrier DS-CDMA (MC DS-CDMA) system, in a Multi-Functional Antenna Array (MFAA) assisted MC DS-CDMA system and in a STBC aided DS-CDMA system. The ACO assisted MUD algorithm is shown to allow a fully loaded MU system to achieve a near-single user performance, which is similar to that of the classic Minimum Mean Square Error (MMSE) detection algorithm. More quantitatively, when the STBC assisted system support K = 32 users, the complexity imposed by the ACO based MUD algorithm is a fraction of 1 × 10?18 of that of the full search-based optimum MUD.<br/><br/>In addition to the hard decision based ACO aided MUD a soft-output MUD was also developed,which was investigated in the context of an STBC assisted DS-CDMA system using a three-stage concatenated, iterative detection aided system. It was demonstrated that the soft-output system is capable of achieving the optimal performance of the Bayesian detection algorithm.","abstract_html":"Reduced-complexity near-maximum-likelihood Ant-Colony Optimization (ACO) assisted Multi-User Detectors (MUDs) are proposed and investigated. The exhaustive search complexity of the optimal detection algorithm may be deemed excessive for practical applications. For example, a Space-Time Block Coded (STBC) two transmit assisted K = 32-user system has to search through the candidate-space for finding the final detection output during 264 times per symbol duration by invoking the Euclidean-distance-calculation of a 64-element complex-valued vector. Hence, a nearoptimal or near-ML MUDs are required in order to provide a near-optimal BER performance at a significantly reduced complexity.&lt;br/&gt;&lt;br/&gt;Specifically, the ACO assisted MUD algorithms proposed are investigated in the context of a Multi-Carrier DS-CDMA (MC DS-CDMA) system, in a Multi-Functional Antenna Array (MFAA) assisted MC DS-CDMA system and in a STBC aided DS-CDMA system. The ACO assisted MUD algorithm is shown to allow a fully loaded MU system to achieve a near-single user performance, which is similar to that of the classic Minimum Mean Square Error (MMSE) detection algorithm. More quantitatively, when the STBC assisted system support K = 32 users, the complexity imposed by the ACO based MUD algorithm is a fraction of 1 × 10?18 of that of the full search-based optimum MUD.&lt;br/&gt;&lt;br/&gt;In addition to the hard decision based ACO aided MUD a soft-output MUD was also developed,which was investigated in the context of an STBC assisted DS-CDMA system using a three-stage concatenated, iterative detection aided system. It was demonstrated that the soft-output system is capable of achieving the optimal performance of the Bayesian detection algorithm.","abstract_has_math":false,"creators":["Xu, Chong"],"institution":"University of Southampton","degree_name":"Ph.D.","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Hanzo, Lajos"],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-06","date_published":"2009-06","updated_at":"2026-07-24T04:36:36Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hanzo, Lajos"]},{"key":"dc:creator","label":"Author","values":["Xu, Chong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009-06"]},{"key":"dc:date.issued","label":"Date","values":["2009-06"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Southampton Wireless Group (pre 2018 reorg)","Faculty of Physical and Applied Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Southampton"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://eprints.soton.ac.uk/206015/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Ph.D."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://eprints.soton.ac.uk/206015/1/report-thesis_xu.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Reduced-complexity near-maximum-likelihood Ant-Colony Optimization (ACO) assisted Multi-User Detectors (MUDs) are proposed and investigated. The exhaustive search complexity of the optimal detection algorithm may be deemed excessive for practical applications. For example, a Space-Time Block Coded (STBC) two transmit assisted K = 32-user system has to search through the candidate-space for finding the final detection output during 264 times per symbol duration by invoking the Euclidean-distance-calculation of a 64-element complex-valued vector. Hence, a nearoptimal or near-ML MUDs are required in order to provide a near-optimal BER performance at a significantly reduced complexity.<br/><br/>Specifically, the ACO assisted MUD algorithms proposed are investigated in the context of a Multi-Carrier DS-CDMA (MC DS-CDMA) system, in a Multi-Functional Antenna Array (MFAA) assisted MC DS-CDMA system and in a STBC aided DS-CDMA system. The ACO assisted MUD algorithm is shown to allow a fully loaded MU system to achieve a near-single user performance, which is similar to that of the classic Minimum Mean Square Error (MMSE) detection algorithm. More quantitatively, when the STBC assisted system support K = 32 users, the complexity imposed by the ACO based MUD algorithm is a fraction of 1 × 10?18 of that of the full search-based optimum MUD.<br/><br/>In addition to the hard decision based ACO aided MUD a soft-output MUD was also developed,which was investigated in the context of an STBC assisted DS-CDMA system using a three-stage concatenated, iterative detection aided system. It was demonstrated that the soft-output system is capable of achieving the optimal performance of the Bayesian detection algorithm."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Reduced-complexity near-optimal Ant-Colony-aided multi-user detection for CDMA systems"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hanzo, Lajos"],"dc:creator":["Xu, Chong"],"dc:date":["2009-06"],"dc:date.issued":["2009-06"],"dc:description.abstract":["Reduced-complexity near-maximum-likelihood Ant-Colony Optimization (ACO) assisted Multi-User Detectors (MUDs) are proposed and investigated. The exhaustive search complexity of the optimal detection algorithm may be deemed excessive for practical applications. For example, a Space-Time Block Coded (STBC) two transmit assisted K = 32-user system has to search through the candidate-space for finding the final detection output during 264 times per symbol duration by invoking the Euclidean-distance-calculation of a 64-element complex-valued vector. Hence, a nearoptimal or near-ML MUDs are required in order to provide a near-optimal BER performance at a significantly reduced complexity.<br/><br/>Specifically, the ACO assisted MUD algorithms proposed are investigated in the context of a Multi-Carrier DS-CDMA (MC DS-CDMA) system, in a Multi-Functional Antenna Array (MFAA) assisted MC DS-CDMA system and in a STBC aided DS-CDMA system. The ACO assisted MUD algorithm is shown to allow a fully loaded MU system to achieve a near-single user performance, which is similar to that of the classic Minimum Mean Square Error (MMSE) detection algorithm. More quantitatively, when the STBC assisted system support K = 32 users, the complexity imposed by the ACO based MUD algorithm is a fraction of 1 × 10?18 of that of the full search-based optimum MUD.<br/><br/>In addition to the hard decision based ACO aided MUD a soft-output MUD was also developed,which was investigated in the context of an STBC assisted DS-CDMA system using a three-stage concatenated, iterative detection aided system. It was demonstrated that the soft-output system is capable of achieving the optimal performance of the Bayesian detection algorithm."],"dc:format":["text"],"dc:identifier.uri":["https://eprints.soton.ac.uk/206015/1/report-thesis_xu.pdf"],"dc:publisher.department":["Southampton Wireless Group (pre 2018 reorg)","Faculty of Physical and Applied Sciences"],"dc:publisher.institution":["University of Southampton"],"dc:relation.isreferencedby":["https://eprints.soton.ac.uk/206015/"],"dc:title":["Reduced-complexity near-optimal Ant-Colony-aided multi-user detection for CDMA systems"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["Ph.D."]},"updated_at":"2026-07-24T04:36:36Z"}