Energy Efficient Estimation in Wireless Sensor Network With Unmanned Aerial Vehicle

Abstract

Distributed estimation is a typical application of wireless sensor network (WSN), where a set of sensor nodes (SNs) collaboratively estimate some parameters of interest from noisy measurements. Recently, unmanned aerial vehicle (UAV) enabled WSN has attracted significant interest since the UAV can collect data energy-efficiently due to its high mobility. In this paper, we consider the joint optimization of UAV trajectory design and SNs' transmission bits allocation for estimating an unknown parameter in UAV-enabled WSN, and the objective is to minimize the total energy consumption of all SNs under the constraint that the mean square error (MSE) of estimation is below a target threshold. The joint optimization problem is formulated with mixed-integer non-convex programming, which is difficult to solve in general. As such, an efficient iterative algorithm is proposed to solve it by applying the block coordinate descent and successive convex optimization techniques. A low-complexity and systematic initialization scheme is also proposed for the trajectory design and transmission bits allocation based on the trade-off structure on the number of visited SNs for estimation. The extensive simulation results are provided to demonstrate the significant performance gains in terms of total energy consumption of all SNs as compared with other benchmark schemes.