Cross-layer framework and optimization for efficient use of the energy budget of IoT Nodes

TL;DR

This paper presents a cross-layer assessment framework for IoT devices in LPWANs, demonstrating significant energy efficiency improvements and throughput gains through joint physical and MAC-layer optimization, specifically evaluated on LoRaWAN networks.

Contribution

It introduces an open-source assessment framework for LPWANs and demonstrates the benefits of a cross-layer approach on LoRaWAN energy and throughput performance.

Findings

Cross-layer optimization improves energy efficiency and throughput.

Larger payloads can reduce energy consumption in static channels.

Dynamic conditions may negate energy savings from larger payloads.

Abstract

Both physical and MAC-layer need to be jointly optimized to maximize the autonomy of IoT devices. Therefore, a cross-layer design is imperative to effectively realize Low Power Wide Area networks (LPWANs). In the present paper, a cross-layer assessment framework including power modeling is proposed. Through this simulation framework, the energy consumption of IoT devices, currently deployed in LoRaWAN networks, is evaluated. We demonstrate that a cross-layer approach significantly improves energy efficiency and overall throughput. Two major contributions are made. First, an open-source LPWAN assessment framework has been conceived. It allows testing and evaluating hypotheses and schemes. Secondly, as a representative case, the LoRaWAN protocol is assessed. The findings indicate how a cross-layer approach can optimize LPWANs in terms of energy efficiency and throughput. For instance, it is shown that the use of larger payloads can reduce up to three times the energy consumption on quasi-static channels yet may bring an energy penalty under adverse dynamic conditions.