  The booming of Internet-of-Things (IoT) is expected to provide more
intelligent and reliable communication services for higher network coverage,
massive connectivity, and low-cost solutions for 6G services. However, frequent
charging and battery replacement of these massive IoT devices brings a series
of challenges. Zero energy devices, which rely on energy-harvesting
technologies and can operate without battery replacement or charging, play a
pivotal role in facilitating the massive use of IoT devices. In order to enable
reliable communications of such low-power devices, Manchester-coded on-off
keying (OOK) modulation and non-coherent detections are attractive techniques
due to their energy efficiency, robustness in noisy environments, and
simplicity in receiver design. Moreover, to extend their communication range,
employing channel coding along with enhanced detection schemes is crucial. In
this paper, a novel soft-decision decoder is designed for OOK-based low-power
receivers to enhance their detection performance. In addition, exact
closed-form expressions and two simplified approximations are derived for the
log-likelihood ratio (LLR), an essential metric for soft decoding. Numerical
results demonstrate the significant coverage gain achieved through soft
decoding for convolutional code.
