np-CECADA: Enhancing Ubiquitous Connectivity of LoRa Networks

Abstract

Long Range Wide Area Networks (LoRaWAN) offer ubiquitous communications for The Internet of Things (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), which is 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 heuristically inferred probability of capturing the channel. To achieve this, first, we carried out an 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. Packet Reception Ratio 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.

CANL LoRa: Collision Avoidance by Neighbor Listening for Dense LoRa Networks

“…They leverage Semtech's CAD mechanism [12] without considering the cases where the CAD fails to detect an ongoing transmission. But Semtech's CAD has reliability issues [13,14,24]. Experiments showed that CAD gets unreliable at distances less than 400 m in dense urban environments.…”

“…does not discard its use in np-CECADA [13]. The authors considered CAD ranges measured in good line-of-sight condition therefore got an optimistic performance evaluation.…”

“…Another promising technique consists in exploiting the fact that CE allows a packet to be successfully decoded even under the presence of interfering devices. Early works study and leverage CE and transmission power to increase the DER [13,[31][32][33]. However, if CE can present some benefit in small-scale deployment scenarios, when the traffic density starts to increase its benefit can be close to null as shown in [14].…”

“…• Listen-Before-Talk [2,4,11] using Channel Activity Detection (CAD) [12]: because transmissions are available below noise level for LoRa, CAD becomes unreliable at long range [13,14];…”