LoRa network communication protocol based on location and time planning

LoRa is a low-power WAN technology designed for the Internet of Things. When large-scale nodes are deployed in a LoRa network channel conflicts increase and packet transmission collisions will lead to a significant reduction in the transmission efficiency of the network. It has been shown that the CSMA protocol based on the CAD mechanism of LoRa devices can be a good solution to such channel conflict problems, but less research has been done on the limitations of CAD itself. In this paper, we analyze in detail the listening range of LoRa network service area and CAD, get the relationship between ED location and the corresponding number of hidden EDs, and establish the communication model of LoRa network based on CSMA. The analysis shows that the CAD listening range of the nodes does not cover the whole LoRa network due to the limitation of the device performance, and the hidden nodes in their blind zones negatively affect the CSMA operation, and this effect is increasing as the number of deployed nodes increases and the network transmission efficiency keeps decreasing to p-ALOHA. To address this problem, this paper proposes a CSMA channel access scheme based on ED location and communication time planning (LT-CSMA), which plans the communication time of EDs at different locations in the LoRa network, aiming at the communication time of Eds within the CAD listening range of each ED to be adjacent to each other, while hidden nodes outside the listening range will be isolated from them in terms of communication time, thus avoiding the channel conflicts caused by hidden nodes. Simulation experiments prove that LT-CSMA can make full use of idle radio channels and has very good results for packet transmission in LoRa networks with small deployment size, and its packet success probability is much higher than that of channel access mechanisms such as CSMA, s-ALOHA, and p-ALOHA. And as the number of EDs deployed increases, LT-CSMA always outperforms CSMA, p-ALOHA in terms of data transmission efficiency, demonstrating good scalability.