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A Bayesian nonparametric approach for blind multiuser channel estimation

I. Valera ; F.J.R. Ruiz ; Lennart Svensson (Institutionen för signaler och system, Signalbehandling) ; F. Perez-Cruz
23rd European Signal Processing Conference (EUSIPCO) 2015, Nice, France, Aug. 31 - Sept. 4 2015 (2076-1465). p. 2766-2770. (2015)
[Konferensbidrag, refereegranskat]

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.

Nyckelord: Bayesian nonparametric; factorial HMM; multiuser communication; machine-to-machine

Denna post skapades 2016-01-22. Senast ändrad 2017-01-27.
CPL Pubid: 231147


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Institutionen för signaler och system, Signalbehandling (1900-2017)



Chalmers infrastruktur