LoRa technology has become critical in numerous IoT applications, offering long-range connections with low energy consumption. However, their low-power nature makes them vulnerable to cross-technology interference (CTI) from other wireless technologies sharing the same unlicensed frequency bands. Existing solutions address this issue through signal analysis and coding techniques. Despite these efforts, the research on CTI mitigation needs to go one step further - to design a systematic framework for enhanced interference resilience. This article proposes SLoRa+, a systematic framework that integrates symbol recovery with soft decoding to achieve synergic interference resilience for LoRa. SLoRa+’s symbol recovery employs a two-stage analysis to recover corrupted LoRa symbols at a low cost. It also estimates the confidence of the recovered symbols by considering the characteristics of both LoRa and CTI. This confidence information is then utilized in soft decoding to improve error correction capabilities. Supported by theoretical analysis and real testbed evaluations, including commercial LoRa nodes and USRP B210, our experiments under different settings, i.e., various CTI sources and frequency bands, demonstrate SLoRa+’s effectiveness. Compared with state-of-the-art techniques, SLoRa+ enhances CTI protection capability by 1.6× with only 1% of the computation cost.