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Particle filtering algorithms for single-channel blind separation of convolutionally coded signals

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3 Author(s)
Canhui Liao ; State Key Lab on Microwave and Digital Communications, Tsinghua University, Beijing 100084 China ; Shilong Tu ; Shidong Zhou

In this paper, we propose a particle filtering based algorithm for single-channel blind separation (SCBS) of two convolutionally coded signals. We utilize the convolution code to enhance the performance of separation. By modifying the generalized state-space representation of the SCBS model, we obtain an approach for joint separation and decoding of two source signals. Two conventional algorithms, which execute decoding after signal separation, are then discussed and compared with the proposed algorithm. Computer simulations show that the proposed algorithm makes a significant improvement in symbol error rate (SER) performance over the two conventional algorithms.

Published in:

Intelligent Signal Processing and Communication Systems, 2009. ISPACS 2009. International Symposium on

Date of Conference:

7-9 Jan. 2009