Periodic Reporting for period 1 - NEWSENs (eNergy nEutral Wireless SEnsor Networks)
Reporting period: 2019-05-01 to 2021-04-30
European directives have set targets for increasing the share of renewable energy use and to limit greenhouse emissions and promote cleaner transport. At the same time, with the emergence of the Internet of Things (IoT) and the billions of connected devices aimed at improving our quality of life and automating industrial processes, the ICT carbon footprint (currently at 3% of the total generated by humans, or 25% of all car emissions) is bound to rise. It is therefore important to research and develop novel energy-neutral IoT solutions.
Collectively, the main objectives of this project are therefore to mathematically study and experimentally demonstrate eNergy nEutral Wireless SEnsor Networks (NEWSENs) that can enable new wireless sensor network technologies and deployment strategies for Smart City and IoT applications. Since many of these applications rely heavily on wireless communications for sensing and control purposes, they are often limited by the short product life cycles of battery-powered wireless sensors and actuator devices. Thus, this interdisciplinary project specifically looked at both the engineering of reliable and scalable wireless communications systems and their efficient functioning through renewable energy sources.
Collectively, the main objectives of this project are therefore to mathematically study and experimentally demonstrate eNergy nEutral Wireless SEnsor Networks (NEWSENs) that can enable new wireless sensor network technologies and deployment strategies for Smart City and IoT applications. Since many of these applications rely heavily on wireless communications for sensing and control purposes, they are often limited by the short product life cycles of battery-powered wireless sensors and actuator devices. Thus, this interdisciplinary project specifically looked at both the engineering of reliable and scalable wireless communications systems and their efficient functioning through renewable energy sources.
A major theme of this fellowship project was to investigate wireless technologies for low power transmission over a long-range thus facilitating the operation of efficient wireless sensor networks. In collaboration with the host institution, the University of Cyprus (UCY), the Marie Curie fellow has led the investigation obtaining several significant results in this area that have been openly disseminated and published in flagship engineering conferences and journals.
On the brink of the IoT revolution, different low-power wide area network technologies are already competing for market share and scalability. LoRa networks is one such technology that has been deployed all over the world and is a major enabler for massive connectivity applications such as smart metering, agriculture, supply chain, and logistics due to the long-range, low cost, and low power features of LoRa. Thus, much of the work carried out in the project has used the LoRa network architecture as a starting point and use case.
The first main result of the project leveraged stochastic geometry tools to better understand how one should model the uplink wireless coverage in a multi-cell LoRa network while taking under consideration both the effects of co-spreading factor interference and the spatial diversity afforded by the LoRa network server. To that end, a tractable model that captures these two system peculiarities was proposed and later used to mathematically show that gateway densification has an overall positive effect on network coverage thus supporting the scalability of LoRa networks.
Building on this first result, more realistic non-uniform LoRa network deployments were also considered and mathematically investigated than what is usually the case in the state-of-the-art literature. Specifically, the question of how non-uniform deployments affect network coverage was studied analytically for the first time. To that end, the fellow and his UCY collaborators suggested optimal deployment strategies and uplink random access transmission schemes to improve network performance. It was found that concave deployments of LoRa end-devices with a sub-linear spread of random-access inter-transmission times provided a more optimal network coverage performance.
Energy harvesting technologies that extract energy from ambient sources have enabled the battery-less operation of many small wireless sensors. Therefore, the final main result of this project merged LoRa wireless communication systems with ambient energy harvesting sources and mathematically modeled device and network performance using tools from stochastic geometry and Markov analysis. To that end, the steady-state distributions of the capacitor voltage were derived, and the outage probability due to co-spreading factor interference at the LoRa gateway was calculated. This level of engineering insight enabled the fellow to propose efficient operating modes such as adaptive charging time schemes that can mitigate energy outage events and extend indefinitely the operation of the network while also maximizing the quality of service.
In addition to low power wireless communications, the project also investigated wireless localization challenges in collaboration with colleagues at the University of California Davis (USA), the University of Bristol (UK), the University of Nottingham (UK), the Paris-Saclay University (France), and Toshiba Corporation (Japan). Finally, in collaboration with researchers in the UK, the project also investigated and demonstrated wireless power transfer using ultrasound to remotely power all sorts of low-power devices, particularly in the context of human-computer interaction.
On the brink of the IoT revolution, different low-power wide area network technologies are already competing for market share and scalability. LoRa networks is one such technology that has been deployed all over the world and is a major enabler for massive connectivity applications such as smart metering, agriculture, supply chain, and logistics due to the long-range, low cost, and low power features of LoRa. Thus, much of the work carried out in the project has used the LoRa network architecture as a starting point and use case.
The first main result of the project leveraged stochastic geometry tools to better understand how one should model the uplink wireless coverage in a multi-cell LoRa network while taking under consideration both the effects of co-spreading factor interference and the spatial diversity afforded by the LoRa network server. To that end, a tractable model that captures these two system peculiarities was proposed and later used to mathematically show that gateway densification has an overall positive effect on network coverage thus supporting the scalability of LoRa networks.
Building on this first result, more realistic non-uniform LoRa network deployments were also considered and mathematically investigated than what is usually the case in the state-of-the-art literature. Specifically, the question of how non-uniform deployments affect network coverage was studied analytically for the first time. To that end, the fellow and his UCY collaborators suggested optimal deployment strategies and uplink random access transmission schemes to improve network performance. It was found that concave deployments of LoRa end-devices with a sub-linear spread of random-access inter-transmission times provided a more optimal network coverage performance.
Energy harvesting technologies that extract energy from ambient sources have enabled the battery-less operation of many small wireless sensors. Therefore, the final main result of this project merged LoRa wireless communication systems with ambient energy harvesting sources and mathematically modeled device and network performance using tools from stochastic geometry and Markov analysis. To that end, the steady-state distributions of the capacitor voltage were derived, and the outage probability due to co-spreading factor interference at the LoRa gateway was calculated. This level of engineering insight enabled the fellow to propose efficient operating modes such as adaptive charging time schemes that can mitigate energy outage events and extend indefinitely the operation of the network while also maximizing the quality of service.
In addition to low power wireless communications, the project also investigated wireless localization challenges in collaboration with colleagues at the University of California Davis (USA), the University of Bristol (UK), the University of Nottingham (UK), the Paris-Saclay University (France), and Toshiba Corporation (Japan). Finally, in collaboration with researchers in the UK, the project also investigated and demonstrated wireless power transfer using ultrasound to remotely power all sorts of low-power devices, particularly in the context of human-computer interaction.
Enabling the efficient operation of a network of sensors across a region has many benefits. For example, environmental or industrial indicators can more easily enable analysis, detection, and mitigation of issues before they become crises while also facilitating new business opportunities and the reduction of greenhouse emissions. Results from the project concerning the improved functioning and potential perpetual operation of wireless sensor networks using ambient energy harvesting sources resonate with such objectives. The results of the project have gone beyond the state of the art both in terms of mathematical analysis providing deep engineering insights for optimization, but also experimentally demonstrating new system prototypes and capabilities for battery-less sensors and actuators. The project results have been shared openly with the public at several science fairs and with the scientific community at conferences and journal publications.