Sorting-Based Soft-Demapping Algorithm for LoRa Systems

In low-complexity long-range (LoRa) systems, the prevailing decoding technique is based on hard-decision information due to the computationally intensive nature of the conventional maximum a posteriori probability in log-domain (Max-Log-MAP) soft demapper. In this letter, we propose a sorting-based soft-demapping (SSD) algorithm for LoRa systems. Our proposed algorithm reduces the complexity order of the soft-demapper from <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(M\log _{2} M)$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(M)$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$M=2^{\text {SF}}$ </tex-math></inline-formula> and SF represents the spreading factor, thus matching the complexity of hard decision. Importantly, this complexity reduction does not lead to any substantial performance degradation when compared to the Max-Log-MAP demapper. As a result, soft decoding can be employed in low-complexity LoRa systems to effectively enhance receiver sensitivity.