Distributed automatic modulation classification with multiple sensors

Document Type

Article

Publication Date

9-22-2010

Abstract

Automatic modulation classification (AMC) has been intensively studied to enhance the successful classification rate, particularly for overcoming the physical limit that deals with weak signals received in a noncooperative communication environment. A wireless sensor network (WSN) has multiple geometrically distributed sensors to work cooperatively. The distributed signal sensing and classification performed by collaborated sensors is proven to be beneficial to increasing the modulation classification reliability. In this paper, we apply the likelihood ratio-based distributed detection fusion technique to address the issues of general binary modulation classifications. The data fusion algorithm performed in the primary node is presented. Its numerical performance with simulation results is demonstrated. © 2010 IEEE.

Identifier

77956691189 (Scopus)

Publication Title

IEEE Sensors Journal

External Full Text Location

https://doi.org/10.1109/JSEN.2010.2049487

ISSN

1530437X

First Page

1779

Last Page

1785

Issue

11

Volume

10

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