Title :
Membership and inference rule generation for fuzzy-neural MIMO channel modeling
Author :
Sarma, Kandarpa Kumar ; Mitra, Abhijit
Author_Institution :
Dept. of Electron. & Electr. Eng., Indian Inst. of Technol. Guwahati, Guwahati, India
Abstract :
Membership and inference rule generation plays a critical role in performance enhancement of fuzzy-neural (FN) modeling of Multi-Input-Multi-Output (MIMO) wireless channels. This work proposes certain methods of the formation of multiple membership generation as well as some inference rule, that determine the performance of FN-MIMO modeling in terms of processing speed and precision. Experimental results establish the enhanced performance of the proposed system in comparison to statistical and other methods.
Keywords :
MIMO communication; inference mechanisms; wireless channels; fuzzy-neural MIMO channel modeling; inference rule generation; multi-input-multi-output wireless channels; multiple membership generation; processing speed; Adaptation models; Artificial neural networks; Channel estimation; Decision making; MIMO; Numerical models; Training; ANN; Estimation; Fuzzy; MIMO;
Conference_Titel :
Information and Communication Technologies (WICT), 2011 World Congress on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4673-0127-5
DOI :
10.1109/WICT.2011.6141268
