{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108581"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108581","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Application of particle swarm optimization in adaptive self-interference cancellation","abstract":"This thesis investigates the application of particle swarm optimization in self-interference cancellation. To achieve cancellation, the receiver has to differentiate between the transmit and receive signal. The transmit signal is already known at the transmitting side but it undergoes some distortion before it reaches the receiving end. An adaptive filter proves to be useful in estimating the distortion, but its weight remains an unknown factor. This thesis uses the particle swarm optimization algorithm to dynamically adjust the weights of the filter.","abstract_html":"This thesis investigates the application of particle swarm optimization in self-interference cancellation. To achieve cancellation, the receiver has to differentiate between the transmit and receive signal. The transmit signal is already known at the transmitting side but it undergoes some distortion before it reaches the receiving end. An adaptive filter proves to be useful in estimating the distortion, but its weight remains an unknown factor. 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To achieve cancellation, the receiver has to differentiate between the transmit and receive signal. The transmit signal is already known at the transmitting side but it undergoes some distortion before it reaches the receiving end. An adaptive filter proves to be useful in estimating the distortion, but its weight remains an unknown factor. This thesis uses the particle swarm optimization algorithm to dynamically adjust the weights of the filter.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-08-01","The student, Jingchao Zhou, accepted the attached license on 2020-07-07 at 14:08.","The student, Jingchao Zhou, submitted this Thesis for approval on 2020-07-07 at 14:14.","This Thesis was approved for publication on 2020-07-07 at 17:20.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15513 on 2020-10-02 at 15:31:36","Made available in DSpace on 2020-10-07T22:44:25Z (GMT). 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