  LoRaWAN has emerged as an appealing technology to connect IoT devices but it
functions without explicit coordination among transmitters, which can lead to
many packet collisions as the network scales. State-of-the-art work proposes
various approaches to deal with these collisions, but most functions only in
high signal-to-interference ratio (SIR) conditions and thus does not scale to
many scenarios where weak receptions are easily buried by stronger receptions
from nearby transmitters. In this paper, we take a fresh look at LoRa's
physical layer, revealing that its underlying linear chirp modulation
fundamentally limits the capacity and scalability of concurrentLoRa
transmissions. We show that by replacing linear chirps with their non-linear
counterparts, we can boost the capacity of concurrent LoRa transmissions and
empower the LoRa receiver to successfully receive weak transmissions in the
presence of strong colliding signals. Such a non-linear chirp design further
enables the receiver to demodulate fully aligned collision symbols - a case
where none of the existing approaches can deal with. We implement these ideas
in a holistic LoRaWAN stack based on the USRP N210 software-defined radio
platform. Our head-to-head comparison with two state-of-the-art research
systems and a standard LoRaWAN baseline demonstrates that CurvingLoRa improves
the network throughput by 1.6-7.6x while simultaneously sacrificing neither
power efficiency nor noise resilience. An open-source dataset and code will be
made available before publication.
