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A sensor network is used for distributed SNR estimation. Sensors observe a signal embedded in noise. These observations are phase modulated using a constant-modulus scheme and transmitted over a Gaussian multiple-access channel to a fusion center. At the fusion center, the location parameter and scale parameter are estimated using a minimum-variance estimator as well as computationally simple alternatives...
We consider a distributed detection problem over fading multiple-access channels. Sensors observe a phenomenon and transmit their observations to a fusion center using the amplify-and-forward scheme. The fusion center has multiple antennas and uses the transmissions from the sensors to run a detection algorithm. The channels are Ricean fading, and the sensors have no channel information. The performance...
We consider a distributed estimation problem where sensors transmit their observations over fading channels to a fusion center (FC), where the parameter is estimated. We calculate the variance of the estimate when we have full, partial and no channel information at the sensors. We compare these with a benchmark obtained when the channels are AWGN. We show that while having no CSI at the sensors leads...
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