Open Access Paper
2 October 1998 Blind channel identification and extraction of more sources than sensors
Pierre Comon
Author Affiliations +
Abstract
It is often admitted that a static with more inputs than outputs cannot be blindly identified, that is, identified only from the observation of its outputs, and without any a priori knowledge on the source statistics but their independence.By resorting to high-order statistics, it turns out that static MIMO systems with fewer outputs than inputs can be identified, as demonstrated in the present paper. The principle, already described in a recent theoretical paper, had not yet been applied to a concrete blind identification problem. Here, in order to demonstrate its feasibility, the procedure is detailed in the case of a 2-sensor 3-source mixture; a numerical algorithm is devised, that blindly identifies a 3-input 2-output mixture. Computer results show its behavior as a function of the data length when sources are QPSK-modulated signals, widely used in digital communications. Then another algorithm is proposed to extract the 3 sources from the 2 observations, once the mixture has been identified. Contrary to the first algorithm, this one assumes that the sources have a known discrete distribution. Computer experiments are run in the case of three BPSK sources in presence of Gaussian noise.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pierre Comon "Blind channel identification and extraction of more sources than sensors", Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); https://doi.org/10.1117/12.325670
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CITATIONS
Cited by 56 scholarly publications and 1 patent.
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KEYWORDS
Sensors

Signal to noise ratio

Matrices

Data communications

Error analysis

Independent component analysis

Vector spaces

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