Optimal sensor density and placement in power-constrained Wireless Sensor Networks

Abstract

This paper presents algorithms that find the optimal number of sensor nodes and the optimal location of nodes to achieve more efficient estimation in a wireless sensor network under power constraints. The network consists of sensors that are optimally placed over an area. Sensors' observations are noisy measurements of an underlying field. Each sensor processes its observation prior to transmitting it to a fusion center, where a field parameter vector is estimated. The network has limited power for the observations transmission processes. Transmission channels between the sensors and the fusion center are assumed to be noisy parallel channels. The sensors' locations, the noise probability density function, and the field characteristic function are assumed to be known at the fusion center. Simulation results which support the derived algorithms are shown.