Title :
Gibbs sampling classification of QAM signals in frequency selective channels
Author :
Drumright, T.A. ; Ding, Z.
Author_Institution :
California Univ., Davis, CA, USA
Abstract :
In this paper, we present a method for QAM signal classification at the receiver, when signals are transmitted through frequency selective channels. Utilizing the Gibbs sampler, a classification of the constellation is achieved, along with joint estimation of all unknown system parameters including the data symbols. When the channel parameters are unknown, additional steps are taken for parameter estimation without altering the general approach. The method is shown to perform well on constellations with different cardinalities, resulting in an algorithm with a relatively low computational complexity and fast convergence.
Keywords :
channel estimation; computational complexity; maximum likelihood estimation; quadrature amplitude modulation; signal classification; signal sampling; Gibbs sampling classification; MLE; QAM signals; channel parameters; computational complexity; constellation classification; convergence; data symbols; frequency selective channels; joint estimation; maximum likelihood estimation; parameter estimation; quadrature amplitude modulation; receivers; system parameters; AWGN; Additive white noise; Constellation diagram; Convergence; Maximum likelihood estimation; Pattern classification; Quadrature amplitude modulation; Sampling methods; Signal to noise ratio; Testing;
Conference_Titel :
Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-7576-9
DOI :
10.1109/ACSSC.2002.1197295