Abstract:To extend the applications of polar codes within next-generation wireless communication systems, it is essential to incorporate support for Incremental Redundancy (IR) Hybrid Automatic Repeat Request (HARQ) schemes. The baseline IR-HARQ scheme's reliance on set-based operations leads to irregular memory access patterns, posing significant challenges for efficient hardware implementation. Furthermore, the introduction of new bit types increases the number of fast nodes that are decoded without traversing the sub-tree, resulting in a substantial area overhead when implemented in hardware. To address these issues and improve hardware compatibility, we propose transforming the set-based operations within the polar IR-HARQ scheme into binary vector operations. Additionally, we introduce a new fast node integration approach that avoids increasing the number of fast nodes, thereby minimizing the associated area overhead. Our proposed scheme results in a memory overhead of 25-27% compared to successive cancellation list (SCL) decoding without IR-HARQ support.
Abstract:GRAND features both soft-input and hard-input variants that are well suited to efficient hardware implementations that can be characterized with achievable average and worst-case decoding latency. This paper introduces step-GRAND, a soft-input variant of GRAND that, in addition to achieving appealing average decoding latency, also reduces the worst-case decoding latency of the corresponding hardware implementation. The hardware implementation results demonstrate that the proposed step-GRAND can decode CA-polar code $(128,105+11)$ with an average information throughput of $47.7$ Gbps at the target FER of $\leq10^{-7}$. Furthermore, the proposed step-GRAND hardware is $10\times$ more area efficient than the previous soft-input ORBGRAND hardware implementation, and its worst-case latency is $\frac{1}{6.8}\times$ that of the previous ORBGRAND hardware.