Skip to content
Open access

Energy Consumption Model for Full-Duplex LoRa Backscatter-Based Sensor Node

Aug 2026 · Computer Networks and Communications · 0 citations

TL;DR

This paper derives the energy model for single-node communication and extends it to multiple-sensor-node communication where several sensors concurrently transmit their information and derives an energy model for a battery-free sensor node that relies on the energy harvested from ambient sources to drive its operation.

Abstract

The integration of Wireless Sensor Networks (WSNs) into Internet of Things (IoT) brings new challenges in terms of range and energy consumption. Specifically, energy consumption is of great importance for future IoT sensors. Therefore, a thorough study must be performed to understand and evaluate the impact of different parameters that affect sensor node energy consumption. However, LoRa backscatter has been seen as a promising technology for long-range low-power IoT applications. Hence, this paper addresses the modeling of the energy consumption of a LoRa backscatter-based sensor node. We first derive the energy model for single-node communication and extend it to multiple-sensor-node communication where several sensors concurrently transmit their information. Furthermore, we derive an energy model for a battery-free sensor node that relies on the energy harvested from ambient sources to drive its operation. The simulation results show that both the LoRa parameters (such as payload size), the number of nodes in the network, and the number of retransmissions can impact the total energy consumption of the sensor node. Additionally, a single node powered by a battery with a capacity of 225 mAh and a transmission of 20 bytes every 5 minutes has a lifetime of about 14 years.

Read PDF

Similar papers

Open access Aug 2026

A Mechanism for Analyzing the Energy Consumption and Environmental Impact of LoRa Sensors Over Time

This transient analysis demonstrates that sustainability assessment in LoRa networks must consider the interactions among active consumption, reception overhead, residual idle drain, and information density throughout the device's operational cycle, providing a reliable basis for early scenario evaluation and energy‐aw...

Vandirleya Barbosa, Melissa Alves, I. Almeida et al. · 0 citations
#reinforcement learning Review Open access Sep 2026

A comprehensive survey on connectivity for IoT sensor networks

This paper presents various feature scopes used in wireless sensor networks (WSNs) and illustrates distinct approaches like relay node placement, efficient communication, machine-learning systems i.e. reinforcement learning, and heuristic techniques.

Ramesh Kumar, D. Sah, R. Bhan · 0 citations
Preprint Jul 2026

Outage Analysis of Backscatter-Based Ambient IoT Device Classes with Energy Buffering

An analytical framework for evaluating the outage probability of ambient Internet of Things device classes communicating directly with a base station is presented and it is highlighted that the optimal device choice depends critically on the operating regime and application demands.

Azzam Al-nahari, R. Jäntti, Yi Zhou et al. · 0 citations
Aug 2026

An Ambient RF Energy Powered Wireless Sensor Node for Environmental Monitoring

With the rapid proliferation of Internet of Things (IoT) devices and advancements in low‐power technologies, radio frequency (RF) energy harvesters present an economical and convenient power solution for low‐power wireless sensor nodes (WSNs). The limited utilization of ambient energy in current RF self‐powered WSNs is...

Tiancong Wang, Yu Cao, Xiaoqiang Liu et al. · 0 citations
Aug 2026

Signal Performance of LoRa‐Based Network for Efficient IoT Applications

A 5 dBi antenna has enhanced the signal strength up to −85.9 dBm in outdoor environments and −94.61 dBm in indoor environments, highlighting the significance of quantified antenna‐related information in design guidelines for optimizing LoRa network deployments in densely populated IoT environments.

Noor Hidayah Mohd Yunus, Syaza Syahirah Ismail, H. Basarudin et al. · 0 citations
#edge computing Aug 2026

Multi-mode energy harvesting–enabled edge computing architecture for industrial IoT environments

This work presents a multi-mode energy harvesting-assisted edge computing architecture, integrated with a joint optimization of energy consumption and communication behaviour, aimed at enhancing the sustainability, reliability and autonomy of operation in an industrial IoT context.

Dr. Deepa, M. Mehfooza, Padmavathy Thiruppathi Raj · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.