Sym-FEC: Enhancing Error Correction in LoRa PHY with a Symbol-Level FEC Decoder

LoRa, a leading wireless technology for Low Power Wide Area Networks (LPWAN), is well-known for its long transmission range and low power consumption. The extended range is primarily attributed to the Chirp Spread Spectrum technique. However, the LoRa physical layer (LoRa PHY) contributes only marginally to this advantage, as it employs an inefficient Forward Error Correction (FEC) strategy for error recovery. In this paper, we introduce Sym-FEC, a symbol-level FEC decoder designed to link the received signals' spectrum with the coding correlations inherent in LoRa PHY, thereby enhancing error recovery. The key enabler of Sym-FEC is signal copy retrieval. We begin by facilitating signal copy conversion between two symbols and extend this to the general case, where signal copy conversions can be performed between any symbols in a coding block. Approaches are also introduced to assess the validity of the block-wide decoding results. Extensive hardware evaluations demonstrate that Sym-FEC provides Signal-to-Noise-Ratio (SNR) improvement of 2.3dB to 3dB compared to the traditional decoder in LoRa PHY. Sym-FEC requires no modifications at the transmitter while incurs low storage and computational complexity at the gateway, thus can be easily integrated into gateway nodes.