  Long Range (LoRa) has become a key enabler technology for low power wide area
networks. However, due to its ALOHA-based medium access scheme, LoRa has to
cope with collisions that limit the capacity and network scalability.
Collisions between randomly overlapped signals modulated with different
spreading factors (SFs) result in inter-SF interference, which increases the
packet loss likelihood when signal-to-interference ratio (SIR) is low. This
issue cannot be resolved by channel coding since the probability of error
distance is not concentrated around the adjacent symbol. In this paper, we
analytically model this interference, and propose an interference cancellation
method based on the idea of segmentation of the received signal. This scheme
has three steps. First, the SF of the interference signal is identified, then
the equivalent data symbol and complex amplitude of the interference are
estimated. Finally, the estimated interference signal is subtracted from the
received signal before demodulation. Unlike conventional serial interference
cancellation (SIC), this scheme can directly estimate and reconstruct the
non-aligned inter-SF interference without synchronization. Simulation results
show that the proposed method can significantly reduce the symbol error rate
(SER) under low SIR compared with the conventional demodulation. Moreover, it
also shows high robustness to fractional sample timing offset (STO) and carrier
frequency offset (CFO) of interference. The presented results clearly show the
effectiveness of the proposed method in terms of the SER performance.
