Improving the Capacity of a Mesh LoRa Network by Spreading-Factor-Based Network Clustering

Guibing Zhu, Chun Hao Liao*, Theerat Sakdejayont, I. Wei Lai, Yoshiaki Narusue, Hiroyuki Morikawa


研究成果: 雜誌貢獻期刊論文同行評審

73 引文 斯高帕斯(Scopus)


LoRa is a low-power long-range IoT standard that uses the chirp spread spectrum technique, and we have strived to further extend its coverage by utilizing the direct device-to-device (D2D) links to construct a multi-hop relay network. In LoRa, the spreading factor (SF) is an important parameter, which not only provides great flexibility between the data rate and sensitivity but also presents a new dimension for multiple accesses. Our approach to improving the capacity of a multihop LoRa network is to attempt to off-load the data traffic into several subnets by utilizing this multiple-access dimension. Each subnet rooted at a sink node is allocated a specific SF on the basis of network clustering. This enables packet transmission in parallel with multiple SFs to become feasible. To allow such parallel transmissions, our considerations are: 1) ensuring the connectivity of all subnets; 2) off-loading the traffic according to the number of nodes, data rates, and network topologies of each subnet; and 3) shortening the airtime of each subnet by reducing the hop count. Toward these objectives, we present a tree-based SF clustering algorithm (TSCA) to conduct SF allocation in a multihop LoRa network. The TSCA focuses on balancing the airtime between the subnets while ensuring connectivity. Furthermore, we use simulations to show that our approach can significantly increase the network performance compared with other approaches. We additionally deploy a real-chip experiment to evaluate the feasibility of parallel transmission in practice.

頁(從 - 到)21584-21596
期刊IEEE Access
出版狀態已發佈 - 2019

ASJC Scopus subject areas

  • 一般電腦科學
  • 一般材料科學
  • 一般工程


深入研究「Improving the Capacity of a Mesh LoRa Network by Spreading-Factor-Based Network Clustering」主題。共同形成了獨特的指紋。