RSSF: Towards Real-Time Decoding of LoRa Packets without Prior Knowledge of their Spreading Factor.

The selection of the spreading factor (SF) has important implications on the radio on-time, energy consumption, achievable data rate, and communication range of LoRa devices. In practical applications, LoRa packets can only be exchanged when the SF between transmitter and receiver matches. To ensure that this is the case, current approaches either statically hard-code the SF used to communicate between two devices, or negotiate which SF to use through handshaking mechanisms. Unfortunately, statically assigning the SF may lead to sub-optimal performance, and changing the assignment at runtime through a negotiation process incurs a significant overhead in terms of both latency and energy consumption. In this paper, we propose RSSF, a scheme that allows an off-the-shelf LoRa device to receive and decode a packet without prior knowledge of the SF used by the transmitter. RSSF leverages the observation that the SF with which a packet was sent can be inferred by analyzing the received signal strength (RSS) samples captured while receiving the first preamble symbols, and by characterizing their periodicity. In real-world systems, however, the waveform obtained by sampling the RSS during the reception of the first preamble symbols contains several spikes due to the receiver's DC offset cancellation, which makes it difficult to accurately identify periods. We show that this problem can be solved by letting an off-the-shelf LoRa receiver sample the RSS on a frequency that is shifted by half of the bandwidth from the original frequency at which the packet was transmitted. We then implement a lightweight algorithm that determines the SF by partitioning the RSS samples into sliding windows of different size (corresponding to each possible SF) and by measuring the zero-crossing intervals for each window size. We evaluate RSSF's performance experimentally using both software-defined radios and off-the-shelf LoRa nodes, showing that RSSF can accurately determine the SF within the first 5 preamble symbols.