LoRa Fine Synchronization with Two-Pass Time and Frequency Offset Estimation

LoRa is currently one of the most widely used low-power wide-area network (LPWAN) technologies. The physical layer leverages a chirp spread spectrum modulation to achieve long-range communication with low power consumption. Synchronization at long distances is a challenging task as the spread signal can lie multiple orders of magnitude below the thermal noise floor. Multiple research works have proposed synchronization algorithms for $L$oR$a$ under different hardware impairments. However, the impact of sampling frequency offset (SFO) has mostly either been ignored or tracked only during the data phase, but it often harms synchronization. In this work, we extend existing synchronization algorithms for $L$oR$a$ to estimate and compensate SFO already in the preamble and show that this early compensation has a critical impact on the estimation of other impairments such as carrier frequency offset and sampling time offset. Therefore it is critical to recover long-range signals.