2026-09-20T08:49:01Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/80935 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Andrew Singer Nelson, Jill Karen 2015-09-25T20:08:54Z 2015-09-25T20:08:54Z 10000-01-01 2005 2005 In addition to asymptotic analysis of receivers for ISI channels, we also propose a joint maximum likelihood detection and decoding scheme for use when the channel is unknown to the receiver. Rather than employing training data to generate an estimate of the channel, the proposed receiver views the channel taps as stochastic quantities drawn from a known prior distribution and uses Bayesian techniques to compute estimates of the transmitted symbols. To implement the proposed receiver, we employ a stacklike algorithm, which estimates the transmitted bits by navigating the tree generated by the combined code and channel. We describe the derivation of the Bayesian metric and explore the performance loss incurred as a result of the lack of channel knowledge. In addition, we empirically characterize the robustness of the Bayesian detector to variations in the parameters of the prior distribution. Made available in DSpace on 2015-09-25T20:08:54Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3199099.pdf: 3629320 bytes, checksum: 4e9a99a90d40692e5d177ca389db2d2d (MD5) Previous issue date: 2005 Embargo set by: Seth Robbins for item 82217 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 138 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005. http://hdl.handle.net/2142/80935 (MiAaPQ)AAI3199099 eng Engineering, Electronics and Electrical Mitigating the Effects of Intersymbol Interference: Algorithms and Analysis text Electrical Engineering Electrical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.