Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors

Zhang, Shan and Liu, Sijia and Sharma, Vinod and Varshney, Pramod K (2018) Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors. In: IEEE TRANSACTIONS ON SIGNAL PROCESSING, 66 (12). pp. 3339-3353.

PDF Ieee_Tra_Sig_Pro_66-12_3339_2018.pdf - Published Version Restricted to Registered users only Download (1MB) | Request a copy

Abstract

In this paper, we design an optimal sensor collaboration strategy among neighboring nodes while tracking a time-varying parameter using wireless sensor networks in the presence of imperfect communication channels. The sensor network is assumed to be self-powered, where sensors are equipped with energy harvesters that replenish energy from the environment. In order to minimize the mean square estimation error of parameter tracking, we propose an online sensor collaboration policy subject to real-time energy harvesting constraints. The proposed energy allocation strategy is computationally light and only relies on the second-order statistics of the system parameters. For this, we first consider an offline nonconvex optimization problem, which is solved exactly when using semidefinite programming. Based on the offline solution, we design an online power allocation policy that requires minimal online computation and satisfies the dynamics of energy flow at each sensor. We prove that the proposed online policy is asymptotically equivalent to the optimal offline solution and show its convergence rate and robustness. We empirically show that the estimation performance of the proposed online scheme is better than that of the online scheme when channel state information about the dynamical system is available in the low SNR regime. Numerical results demonstrate the effectiveness of our approach.

Item Type:	Journal Article
Publication:	IEEE TRANSACTIONS ON SIGNAL PROCESSING
Publisher:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Additional Information:	Copy right of this article belong to IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	12 Jun 2018 16:01
Last Modified:	12 Jun 2018 16:01
URI:	http://eprints.iisc.ac.in/id/eprint/59987

Actions (login required)

View Item