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Virginia Tech

Advances in Iterative Probabilistic Processing for Communication Receivers

Abstract

dc:description.abstract

As wireless communication systems continue to push the limits of energy and spectral efficiency, increased demands are placed on the capabilities of the receiver. At the same time, the computational resources available for processing received signals will continue to grow. This opens the door for iterative algorithms to play an increasing role in the next generation of communication receivers. In the context of receivers, the goal of iterative probabilistic processing is to approximate maximum a posteriori (MAP) symbol-by-symbol detection of the information bits and estimation of the unknown channel or signal parameters. The sum-product algorithm is capable of efficiently approximating the marginal posterior probabilities desired for MAP detection and provides a unifying framework for the development of iterative receiver algorithms. However, in some applications the sum-product algorithm is computationally infeasible. Specifically, this is the case when both continuous and discrete parameters are present within the model. Also, the complexity of the sum-product algorithm is exponential in the number of variables connected to a particular factor node and can be prohibitive in multi-user and multi-antenna applications. In this dissertation we identify three key problems which can benefit from iterative probabilistic processing, but for which the sum-product algorithm is too complex. They are (1) joint synchronization and detection in multipath channels with emphasis on frame timing, (2) detection in co-channel interference and non-Gaussian noise, and (3) joint channel estimation and multi-signal detection. This dissertation presents the advances we have made in iterative probabilistic processing in order to tackle these problems. The motivation behind the work is to (a) compromise as little as possible on the performance that is achieved while limiting the computational complexity and (b) maintain good theoretical justification to the algorithms that are developed.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Electrical Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Jakubisin, Daniel Joseph
Chair dc:contributor.committeechair
  • Buehrer, R. Michael
Committee members dc:contributor.committeemember
  • McGwier, Robert W.
  • Batra, Dhruv
  • Kim, Inyoung
  • da Silva, Claudio R. C. M.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:7719
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/71640

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Jakubisin, Daniel Joseph. Advances in Iterative Probabilistic Processing for Communication Receivers. doctoral thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71640