Energy Harvesting Wireless Node Scheduling via Battery Level Prediction

Solution Overview

Problem

Energy harvesting wireless devices often face unavailability due to insufficient energy levels, leading to excessive unnecessary signaling and increased energy consumption, as the network cannot predict when the device can perform energy harvesting.

Innovation Solution

A method performed in a network node to predict the energy level of an energy harvesting wireless device by receiving information and parameters from the device, including energy harvesting properties and current use parameters, to enable accurate energy level prediction and intelligent scheduling of communication.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the device signals every time energy level drops below a certain level, then the network can be informed of low energy status, but energy consumption increases and communication efficiency decreases

Engineering Contradiction:

Improvenetwork awareness of device energy statusVSAvoiddevice energy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The network node performs preliminary prediction of the device's energy level using received parameters and algorithms before the device actually experiences energy depletion. This allows the network to proactively schedule communications during periods when energy will be sufficient, avoiding the need for reactive signaling when energy runs low.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The device provides feedback parameters to the network node about its energy harvesting properties and current usage patterns. The network uses this feedback to continuously refine its prediction model and adjust communication scheduling to match the device's energy availability, creating a closed-loop system that optimizes both reliability and energy efficiency.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If the device communicates frequently to report energy status, then the network can adapt communication scheduling, but device unavailability increases due to energy depletion

Engineering Contradiction:

Improvecommunication scheduling flexibilityVSAvoiddevice unavailability time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The network node performs preliminary prediction of the device's energy level using received parameters and algorithms before the device actually experiences energy depletion. This allows the network to proactively schedule communications during periods when energy will be sufficient, avoiding the need for reactive signaling when energy runs low.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The communication scheduling is made dynamic by continuously updating the prediction algorithm with new parameters from the device. The network adapts the communication schedule in real-time based on changing energy harvesting conditions and usage patterns, optimizing the balance between communication needs and energy availability.

Inventive Principle:

Principle #15Dynamics

3Device complexity

If the network schedules communication without energy prediction, then communication simplicity is maintained, but excessive unnecessary signaling occurs increasing overhead

Engineering Contradiction:

Improvecommunication scheduling simplicityVSAvoidenergy wasted in unnecessary signaling

Core Design Contradiction:

Device complexityVSLoss of energy

Solution Approach 1:

The network node performs preliminary prediction of the device's energy level using received parameters and algorithms before the device actually experiences energy depletion. This allows the network to proactively schedule communications during periods when energy will be sufficient, avoiding the need for reactive signaling when energy runs low.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The device autonomously monitors its own energy harvesting properties and usage patterns, and selectively reports only the necessary parameters to the network. This self-service approach reduces the signaling overhead compared to continuous status reporting, while still providing sufficient information for accurate energy prediction and optimized scheduling.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250132600A1Methods for predicting energy level for an energy harvesting wireless device, a related network node and a related wireless device

Publication Date: 2025.04.24 SONY GROUP CORP

AI summary

A method is disclosed, performed in a network node, for enabling a prediction of an energy level of an energy harvesting wireless device, WD. The method comprises receiving, from the WD, information assisting the network node to obtain an algorithm for predicting the energy level of the WD. The method comprises receiving, from the WD, parameters for use by the algorithm in predicting the energy level of the WD. the parameters comprise energy harvesting properties and parameters associated with current use of the WD, whereby prediction of the energy level of the WD is enabled.