LoRadar: An Efficient LoRa Channel Occupancy Acquirer Based on Cross-Channel Scanning

LoRa is widely deployed for various applications. Though the knowledge of the channel occupancy is the prerequisite of many aspects of network management, acquiring the channel occupancy for LoRa is challenging due to the large number of possible channels. In this paper, we propose ${\sf LoRadar}$LoRadar, a novel LoRa channel occupancy acquirer based on cross-channel scanning. Our in-depth study finds that Channel Activity Detection (CAD) in a narrow band can indicate the channel activities of wide bands because they have the same slope in the time-frequency domain. Based on this finding, we design a cross-channel scanning mechanism that infers the channel occupancy states of all the overlapping channels by the distribution of CAD results. We elaborately select and adjust the CAD settings to enhance the distribution features and design a pattern correction method to cope with distribution distortions. We also design a CAD scheduler to deal with the low duty-cycle LoRa operations. We implement ${\sf LoRadar}$LoRadar on commercial LoRa platforms and evaluate its performance in the indoor testbed and two outdoor deployed networks. The experimental results show that ${\sf LoRadar}$LoRadar can achieve a detection accuracy of 0.99 and reduce the acquisition overhead by up to 90%, compared to the traversal-based methods.