Performance Bounds for Remote Estimation under Energy Harvesting Constraints

TL;DR

This paper establishes bounds on the distortion in remote Gaussian field estimation using energy harvesting sensors with limited buffers, revealing how buffer size and energy process statistics influence performance.

Contribution

It provides the first performance bounds for online remote estimation with energy harvesting sensors, linking buffer sizes and energy statistics to achievable distortion.

Findings

Performance bounds depend on energy process mean, variance, and support.

Buffer size insensitivity for low-degree-of-freedom signals.

Potential for improved performance with larger buffers for complex signals.

Abstract

Remote estimation with an energy harvesting sensor with a limited data and energy buffer is considered. The sensor node observes an unknown Gaussian field and communicates its observations to a remote fusion center using the energy it harvested. The fusion center employs minimum mean-square error (MMSE) estimation to reconstruct the unknown field. The distortion minimization problem under the online scheme, where the sensor has access to only the statistical information for the future energy packets is considered. We provide performance bounds on the achievable distortion under a slotted block transmission scheme, where at each transmission time slot, the data and the energy buffer are completely emptied. Our bounds provide insights to the trade-offs between the buffer sizes, the statistical properties of the energy harvesting process and the achievable distortion. In particular, these trade-offs illustrate the insensitivity of the performance to the buffer sizes for signals with low degree of freedom and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom. Depending only on the mean, variance and finite support of the energy arrival process, these results provide practical insights for the battery and buffer sizes for deployment in future energy harvesting wireless sensing systems.