Soft Decoders for Various Ambient IoT Receivers in FEC-Miller Concatenated Coding System

As a potential IoT technology for future networks, Ambient IoT (A-IoT) has entered the standardization process in Third Generation Partnership Project (3GPP). In A-IoT, Forward Error Correction (FEC)-Miller concatenated coding is emerging as a promising coding mechanism due to its advantages in link performance and time synchronization. This concatenated mechanism necessitates the use of Miller soft decoding before FEC decoding. However, it is difficult to design a unified Miller soft decoding approach in A-IoT. The reason is that, the soft decoding approach is closely associated with the receiver detection approaches, such as envelope detectors or amplitude/phase detectors. Owing to the diversity of A-IoT devices/readers, hardware complexities of different receivers vary significantly, thereby resulting in disparate signal detecting and decoding capabilities. To address this challenge, this paper considers three typical A-IoT receivers with different hardware complexities, proposes Miller soft decoding algorithms in Miller-FEC concatenated decoding for each receiver respectively, and derives closed-form expressions of Log-Likelihood Ratio (LLR). Finally, link-level simulations are conducted to validate the effectiveness of the proposed algorithms across different receivers.