2021 Fiscal Year Annual Research Report
Toward Ubiquitous Connectivity via Unlicensed LPWANs
| Project/Area Number |
21F21074
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| Research Institution | Kyushu University |
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Principal Investigator |
牟田 修 九州大学, 日本エジプト科学技術連携センター, 准教授 (80336065)
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| Co-Investigator(Kenkyū-buntansha) |
SHAO CHENGLONG 九州大学, 日本エジプト科学技術連携センター, 外国人特別研究員
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| Project Period (FY) |
2021-04-28 – 2023-03-31
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| Keywords | Internet of Things / LoRaWAN / Physical layer / Close physical contact / Collision resolution / Wireless power transfer / Mobile charging |
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| Outline of Annual Research Achievements |
This research aims to design LRNet, a one-size-fits-all networking engine for LoRaWAN systems, to provide ubiquitous Internet-of-Things (IoT) connectivity. Specifically, LRNet is expected to enable better device coexistence and higher link capacity. In the first year, this is achieved mainly via the design of novel algorithms for resilient signal reception. To this end, we have built an indoor LoRaWAN prototype with two USRP N210 software-defined radios as LoRaWAN gateways and twelve Dragino LoRa Shields as LoRaWAN end devices. We have confirmed packet exchanges and signal collision problems based on this prototype. For the sake of resilient signal reception, we have devised several solutions and used the prototype to show their feasibility in practical LoRaWAN. We have published a related paper to provide a comprehensive overview of up-to-date physical-layer solutions for LoRaWAN signal collision resolution. The potential insights of physical-layer design to resolve LoRaWAN signal collisions are deeply discussed. Furthermore, we have also conducted several preliminary experiments to study the medium access control (MAC)-layer issues in LoRaWAN. Particularly, we have used our prototype to figure out that the standard Channel Activity Detection (CAD) technique in the MAC layer of LoRaWAN is not reliable for LoRaWAN carrier sensing. Besides, we have designed a close physical contact (CPC) detection technique to recognize if two LoRaWAN end devices are close to each other. We have also studied mobile charger-based wireless power transfer issues in IoT systems.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Our research plans in the first year are: (1) building an indoor LoRaWAN prototype where packet exchanges between LoRaWAN gateways and end devices can be observed; (2) devising a resilient signal reception algorithm to resolve LoRaWAN signal collisions; (3) studying LoRaWAN medium access control (MAC)-layer issues for harmonious signal transmissions at LoRaWAN end devices. Regarding the plan (1), we have used two USRP N210 software-defined radios and twelve commodity Dragino LoRa Shields as LoRaWAN gateways and end devices, respectively. By applying customized programs for signal transmission and reception in the gateways and the end devices, we have successfully built a laboratory-scale LoRaWAN and confirmed packet exchanges. Regarding the plan (2), we have devised several possible solutions and published a related paper by additionally providing a comprehensive overview of existing physical-layer techniques designed for LoRaWAN signal collision resolution. Regarding the plan (3), we have conducted several related experiments in real-world environments by using commodity Dragino LoRa Shields. Particularly, we have obtained the important result that the standard Channel Activity Detection (CAD) technique in the MAC layer of LoRaWAN is not reliable for LoRaWAN carrier sensing.
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| Strategy for Future Research Activity |
In the second year, our research will be based on an outdoor environment with a larger LoRaWAN size. Particularly, in addition to using more LoRaWAN end devices, we plan to deploy commodity LoRaWAN gateways instead of software-defined radios. Based on this LoRaWAN prototype, we will design a full-fledged medium access control (MAC)-layer protocol to enable harmonious signal transmissions at LoRaWAN end devices. Specifically, we will develop a more reliable carrier-sensing technique based on the Channel Activity Detection (CAD) function in the MAC layer of LoRaWAN. This technique will then be used to make each LoRaWAN end device able to detect the transmissions of others for the purpose of signal collision avoidance. Furthermore, we will study the issues in LoRaWAN optimization by designing an algorithm for adaptive network resource allocation. We will take into consideration the most important network parameters including spreading factor, coding rate, bandwidth, signal transmission power, and channel frequency. Our object function in this optimization problem will be related to the energy fairness among LoRaWAN end devices. Besides, we will consider integrating all the proposed techniques through this research into a single software module for system upgrade ease. We plan to adopt a star software integration method to enable fast communication among sub-systems. We will test this module on different Internet-of-Things operating systems that are used in current LoRaWAN infrastructure.
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Research Products
(5 results)
