Sum-product algorithm can be employed for obtaining the marginal probability
density functions from a given joint probability density function (p.d.f.). The sum-product
algorithm operates on a factor graph which represents the
dependencies of the random variables
whose joint p.d.f. is given.
The sum-product algorithm can not be operated on factor-graphs that contain
loops. For these factor graphs iterative sum-product algorithm is used.
A factor
graph which contains loops can be divided in to loop-free sub-graphs. Sum-product
algorithm can be operated in these loop-free sub-graphs and results of these sub-graphs can
be combined for obtaining the result of the whole factor graph in an iterative manner.
This method may increase the convergence rate of the algorithm significantly
while keeping the complexity
of an iteration and accuracy of the output constant.
A useful by-product of this research that is introduced in this thesis is a good
approximation to message calculation in factor nodes of the inter-symbol interference
(ISI) factor graphs. This approximation has a complexity that is linearly proportional with
the number of neighbors instead of being exponentially proportional. Using this
approximation and the sub-graph idea we have designed and simulated joint
decoding-equalization (turbo equalization) algorithm and obtained good results
besides the low complexity.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/3/12606550/index.pdf |
| Date | 01 September 2005 |
| Creators | Bayramoglu, Muhammet Fatih |
| Contributors | Baykal, Buyurman |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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