Multiple Composite Hypothesis Testing: A Competitive Approach
Journal of VLSI Signal Processing Systems
Blind separation of digital signal sources in noise circumstance
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
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In this paper, we present a method for blind separation of co-channel BPSK signals arriving at an antenna array. This method consists of two parts: the maximum likelihood constellation estimation and assignment. We show that at high SNR, the maximum likelihood constellation estimation is well approximated by the smallest distance clustering algorithm, which we proposed earlier on heuristic grounds. We observe that both these methods for estimating the constellation vectors perform very well at high SNR and nearly attain Cramer-Rao bounds. Using this fact and noting that the assignment algorithm causes negligible error at high SNR, we derive upper bounds on the probability of bit error for the above method at high SNR. These upper bounds fall very rapidly with increasing SNR, showing that our constellation estimation-assignment approach is very efficient. Simulation results are given to demonstrate the usefulness of the bounds