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https://hdl.handle.net/2142/72011
Description
Title
Coding and Equalization for Radio Channels
Author(s)
Frank, Colin David
Issue Date
1993
Doctoral Committee Chair(s)
Pursley, Michael B.
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
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.
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.
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