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- W2116960956 abstract "Automatic modulation classification with a single receiver has been intensively studied for two decades. Enhancing the successful classification probability is a bottleneck in this research field especially with weak signals in a non-cooperative communication environment. A sensor network with distributed classification techniques is expected to achieve technology breakthrough in providing spatial diversity and increasing the classification reliability. In this paper, we developed a distributed likelihood function-based classification method and extend the automatic modulation classification to sensor or radio networks. The classification methods performed in the sensors and primary node associated with theoretical discussion and numerical results are presented." @default.
- W2116960956 created "2016-06-24" @default.
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- W2116960956 date "2010-04-01" @default.
- W2116960956 modified "2023-10-03" @default.
- W2116960956 title "Likelihood function-based modulation classification in bandwidth-constrained sensor networks" @default.
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- W2116960956 doi "https://doi.org/10.1109/icnsc.2010.5461606" @default.
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