DocumentCode :
3716336
Title :
A Bayesian nonparametric approach for blind multiuser channel estimation
Author :
Isabel Valera;Francisco J. R. Ruiz;Lennart Svensson;Fernando Perez-Cruz
Author_Institution :
Max Planck Institute for Software Systems, Kaiserslautern, Germany
fYear :
2015
Firstpage :
2766
Lastpage :
2770
Abstract :
In many modern multiuser communication systems, users are allowed to enter and leave the system at any given time. Thus, the number of active users is an unknown and time-varying parameter, and the performance of the system depends on how accurately this parameter is estimated over time. We address the problem of blind joint channel parameter and data estimation in a multiuser communication channel in which the number of transmitters is not known. For that purpose, we develop a Bayesian nonparametric model based on the Markov Indian buffet process and an inference algorithm that makes use of slice sampling and particle Gibbs with ancestor sampling. Our experimental results show that the proposed approach can effectively recover the data-generating process for a wide range of scenarios.
Keywords :
"Transmitters","Hidden Markov models","Receiving antennas","Signal to noise ratio","Bayes methods","Communication systems"
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2015 23rd European
Electronic_ISBN :
2076-1465
Type :
conf
DOI :
10.1109/EUSIPCO.2015.7362888
Filename :
7362888
Link To Document :
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