The Internet of Things (IoT) has been part of many automation and smart systems. Long Range Wide Area Networks (LoRaWAN) offer ubiquitous communications for IoT. However, there are many challenges in rolling out LoRaWAN - mainly scalability, energy efficiency, Packet Reception Ratio (PRR), and keeping the channel access as simple as unslotted ALOHA. To this end, we design non-persistent Capture Effect Channel Activity Detection Algorithm (np-CECADA), which is a novel, distributed protocol for the MAC layer of LoRaWAN. It utilizes Channel Activity Detection (CAD), a built-in, imperfect mechanism for channel sensing and minimal feedback from the gateways. In np- CECADA each device independently adapts backoff times based on the traffic in its vicinity and the transmission power based on the inferred chances of capturing the channel. To achieve this, first, we carried out extensive on-field evaluation to measure the effectiveness of CAD and capture effect in LoRa. Using them we designed np-CECADA and developed ns-3 modules. PRR of np-CECADA is 15.74× and 5.13× higher than vanilla LoRaWAN and p-CARMA, respectively. Channel utilization is 11.24× higher compared to LMAC. Further, on a testbed of 30 LoRa devices np-CECADA outperforms LoRaWAN up to 5 times.
Original language
English
Title of host publication
2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
