文件名称:channel-aware-decsision-fusion
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Information fusion by utilizing multiple distributed sensors
is studied in this work. Extending the classical parallel fusion structure
by incorporating the fading channel layer that is omnipresent in wireless
sensor networks, we derive the likelihood ratio based fusion rule given fixed
local decision devices. This optimum fusion rule, however, requires perfect
knowledge of the local decision performance indices as well as the fading
channel. To address this issue, two alternative fusion schemes, namely, the
maximum ratio combining statistic and a two-stage approach using the
Chair–Varshney fusion rule, are proposed that alleviate these requirements
and are shown to be the low and high signal-to-noise ratio (SNR) equivalents
of the likelihood-based fusion rule
is studied in this work. Extending the classical parallel fusion structure
by incorporating the fading channel layer that is omnipresent in wireless
sensor networks, we derive the likelihood ratio based fusion rule given fixed
local decision devices. This optimum fusion rule, however, requires perfect
knowledge of the local decision performance indices as well as the fading
channel. To address this issue, two alternative fusion schemes, namely, the
maximum ratio combining statistic and a two-stage approach using the
Chair–Varshney fusion rule, are proposed that alleviate these requirements
and are shown to be the low and high signal-to-noise ratio (SNR) equivalents
of the likelihood-based fusion rule
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channel aware decsision fusion.pdf