On the number of samples needed to identify a mixture of finite alphabet constant modulus signals

A. Leshem, A. J. van der Veen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Constant modulus algorithms try to separate linear mixtures of sources with modulus 1. We study the identifiability of this problem: the number of samples needed to ensure that in the noiseless case we have a unique solution. For finite alphabet (L-PSK) sources, finite sample identifiability can hold only with a probability close to but not equal to 1. In a previous paper (Leshem, A. et al., Proc. IEEE Workshop on Sensor Array and Multichannel Signal Processing, 2002), we provided a subexponentially decaying upper bound on the probability of non-identifiability. Here, we provide an improved exponentially decaying upper bound, based on Chernoff bounds. We show that, under practical assumptions, this upper bound is much tighter than previously known bounds.
Original languageAmerican English
Title of host publicationAcoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
PublisherIEEE
StatePublished - 2003

Bibliographical note

Place of conference:Hong-Kong, China

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