Iteratif topla-çarp algoritmasında alt ağ yaklaşımı


Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2005

Tezin Dili: İngilizce

Öğrenci: Muhammet Fatih Bayramoğlu

Danışman: BUYURMAN BAYKAL

Özet:

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.