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Linear MMSE-Optimal Turbo Equalization Using Context Trees
[article]
2012
arXiv
pre-print
Formulations of the turbo equalization approach to iterative equalization and decoding vary greatly when channel knowledge is either partially or completely unknown. Maximum aposteriori probability (MAP) and minimum mean square error (MMSE) approaches leverage channel knowledge to make explicit use of soft information (priors over the transmitted data bits) in a manner that is distinctly nonlinear, appearing either in a trellis formulation (MAP) or inside an inverted matrix (MMSE). To date,
arXiv:1203.4168v1
fatcat:7uhv5v4hpvarxdjzr4udjx44vi