Adaptive channel equalization for satellite communications with multipath based on unsupervised learning algorithm

Author

Li, Jiang ; Qilian Liang ; Manry, Michael T.

Author_Institution

Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA

Volume

1

fYear

2003

fDate

7-10 Sept. 2003

Firstpage

730

Abstract

Channel equalization has been revealed to be a classification problem by some recent applications of clustering and neural network techniques. In this paper, a new unsupervised learning (clustering) algorithm, adaptive nearest neighbor classifier (ANNC) is presented for channel equalization. ANNC can mine more channel characteristics that the recently proposed nearest neighbor (NNC) classifier. The proposed method is applied to a time-division-multiple-access (TDMA) satellite communication system with burst digital transmission. The improvement of the proposed algorithm over the recently reported NNC approach is clearly demonstrated.

Keywords

adaptive equalisers; classification; fading channels; multipath channels; satellite communication; statistical analysis; telecommunication computing; time division multiple access; unsupervised learning; adaptive channel equalization; adaptive nearest neighbor classifier; burst digital transmission; classification problem; clustering techniques; multipath fading; neural network techniques; satellite communications; time-division-multiple-access; unsupervised learning algorithm; Adaptive equalizers; Channel estimation; Clustering algorithms; GSM; Intersymbol interference; Maximum likelihood estimation; Nearest neighbor searches; Satellite communication; Time division multiple access; Unsupervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003. 14th IEEE Proceedings on

Print_ISBN

0-7803-7822-9

Type

conf

DOI

10.1109/PIMRC.2003.1264370

Filename

1264370