Adaptive NDF Classification for SF Allocation in Arbitrary Node Distribution in LoRaWAN
Conference proceedings article
Authors/Editors
Strategic Research Themes
Publication Details
Author list: Phanupong Tempiem and Rardchawadee Silapunt
Publication year: 2023
Start page: 1
End page: 5
Number of pages: 5
Languages: English-United States (EN-US)
Abstract
In this paper, we introduced the Adaptive NDF (Node Density Factor) classification method to enhance the performance of the original ADR (Adaptive Data Rate) scheme used in the LoRa (Long-Range) network in scenarios with arbitrary distributed nodes. The core concept of Adaptive NDF Classification is the NDF factor calculation, determined by the ratio of nodes in a specific section to the total number of nodes. The coverage area spanning from 2 to 10 kilometers was systematically observed for variations in NDF and DER values. The Adaptive NDF classification method boosted the DER to 78% in the area beyond 4 kilometers, around 18% over the original ADR. In other words, the Adaptive NDF classification method represents a valuable enhancement to the ADR scheme, offering improved performance when nodes are irregularly distributed.
Keywords
Adaptive Data Rate, Internet of Things, LoRaWAN