Adaptive Power Allocation in Wireless Sensor Networks with Spatially Correlated Data and Analog Modulation: Perfect and Imperfect CSI
The authors address the problem of power allocation in a wireless sensor network where distributed sensors amplify and forward their partial and noisy observations of a Gaussian random source to a remote Fusion Center (FC). The FC reconstructs the source based on Linear Minimum Mean-Squared Error (LMMSE) estimation rule. Motivated by the availability of limited energy in the sensor networks, they undertake the design of power allocation based on minimization of the reconstruction distortion subject to a constraint on the network transmit power. The design is based on the following two cases: exact knowledge of the channel gains and the estimates of the channel gains. They show that the distortion can be represented as a convex function of the transmit powers of the sensors.