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Blind particle filtering for detection in a time-varying frequency selective channel with non-Gaussian noise

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3 Author(s)
Derek Yee ; Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada ; Reilly, J.P. ; Kirubarajan, T.

In this paper, we present efficient particle filtering and smoothing algorithms to solve the problem of blind detection in a time-varying frequency selective channel with additive non-Gaussian noise. The proposed algorithms are efficiently implemented via a combination of the optimal importance distribution and the principle of Rao-Blackwellization. The proposed particle smoothing algorithms which results in significantly improved performance, employ the method of delayed sampling, delayed weights, or a combination of the former. Simulation results are provided to illustrate the effectiveness of the proposed algorithms.

Published in:

Signal Processing Advances in Wireless Communications, 2005 IEEE 6th Workshop on

Date of Conference:

5-8 June 2005