Millimeter Wave Energy Harvesting

TL;DR

This paper analyzes the potential of millimeter wave (mmWave) signals for wireless energy harvesting in 5G networks, deriving analytical models and proposing design optimizations to improve energy and information transfer efficiency.

Contribution

It provides the first analytical framework for mmWave energy harvesting, including expressions for coverage and power, and proposes a low-power multi-antenna receiver architecture.

Findings

mmWave energy harvesting can outperform lower frequency solutions.

Optimizing antenna beamwidth enhances network-wide energy coverage.

Multi-antenna arrays and signal splitting improve device-level performance.

Abstract

The millimeter wave (mmWave) band, which is a prime candidate for 5G cellular networks, seems attractive for wireless energy harvesting. This is because it will feature large antenna arrays as well as extremely dense base station (BS) deployments. The viability of mmWave for energy harvesting though is unclear, due to the differences in propagation characteristics such as extreme sensitivity to building blockages. This paper considers a scenario where low-power devices extract energy and/or information from the mmWave signals. Using stochastic geometry, analytical expressions are derived for the energy coverage probability, the average harvested power, and the overall (energy-and-information) coverage probability at a typical wireless-powered device in terms of the BS density, the antenna geometry parameters, and the channel parameters. Numerical results reveal several network and device level design insights. At the BSs, optimizing the antenna geometry parameters such as beamwidth can maximize the network-wide energy coverage for a given user population. At the device level, the performance can be substantially improved by optimally splitting the received signal for energy and information extraction, and by deploying multi-antenna arrays. For the latter, an efficient low-power multi-antenna mmWave receiver architecture is proposed for simultaneous energy and information transfer. Overall, simulation results suggest that mmWave energy harvesting generally outperforms lower frequency solutions.