ELLR-BP: An Enhanced LLR-BP Algorithm Based on LDPC Coding for LoRa Physical Layer

Wireless communication is highly susceptible to various forms of noise and interference, leading to potential errors in received data. Consequently, this study proposes a novel anti-interference LoRa physical layer communication model to reduce the Bit Error Rate (BER) under extremely low Signal-to-Noise Ratio (SNR) conditions in LoRa communication. The model incorporates Low-Density Parity-Check (LDPC) codes as the channel coding scheme and integrates soft Chirp Spread Spectrum (CSS) demodulation with the Log-Likelihood Ratios Belief Propagation (LLR-BP) decoding algorithm. A key component of the model is the Enhanced LLR-BP (ELLR-BP) algorithm, which dynamically adjusts LLR values during iterative decoding based on variations in SNR and Spreading Factor (SF), enabling enhanced BER performance in challenging environments. Additionally, the model introduces realistic channel effects, including fading and Co-SF interference, into the simulation framework. MATLAB simulations demonstrate the model’s effectiveness: LDPC coding improves the SNR threshold by approximately 1 dB and reduces the BER by more than 3% compared to traditional Hamming coding. When BER <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${=} \,\, 10{^{-}4 }$ </tex-math></inline-formula>, the proposed ELLR-BP algorithm achieves a gain of 0.4097 dB and reduces the BER by 0.54% to 0.81% compared with the LLR-BP algorithm. Similarly, the proposed anti-interference model significantly improves performance under Rayleigh channels and provides better resistance to Co-SF interference than standard LoRa.