The URLLC scenario in the upcoming 6G standard requires low latency and ultra reliable transmission, i.e., error correction towards ML performance. Achieving near-ML performance is very challenging especially for short block lengths. Polar codes are a promising candidate and already part of the 5G standard. The Successive Cancellation List (SCL) decoding algorithm provides very good error correction performance but at the cost of high computational decoding complexity resulting in large latency and low area and energy efficiency. Recently, Automorphism Ensemble Decoding (AED) gained a lot of attention to improve the error correction capability. In contrast to SCL, AED performs several low-complexity (e.g., SC) decoding in parallel. However, it is an open question whether AED can compete with sophisticated SCL decoders, especially from an implementation perspective in state of the art silicon technologies. In this paper we present an elaborated AED architecture that uses an advanced path metric based candidate selection to reduce the implementation complexity and compare it to state of the art SCL decoders in a 12nm FinFET technology. Our AED implementation outperform state of the art SCL decoders by up to 4.4x in latency, 8.9x in area efficiency and 4.6x in energy efficiency, while providing the same or even better error correction performance.
翻译:即将推出的 6G 标准中的 URLLC 情景要求低潜值和超可靠的传输, 即对 ML 性能的错误校正。 实现接近ML 性能非常困难, 特别是对于短块长度而言。 极地代码是一个很有希望的候选人, 已经是 5G 标准的一部分 。 连续取消列表解码算法提供了非常好的错误校正性能, 但代价是计算解码复杂性高, 导致大延度和低面积以及能源效率。 最近, 自动脱色( AED) 获得了很多关注, 以提高错误校正能力。 与 SCL 相比, AED 运行了一些低兼容性( 例如 SC ), 并平行解码。 然而, 连续取消列表解码算法的算法能否与精密的 SCL 解码功能进行竞争, 特别是从艺术硅技术的状态的执行角度来看, 我们展示了一个精心的AED结构结构, 使用高级路径选择候选人来降低执行复杂性, 将它与 SCL decoduders est of the SCL decodistrations in 12nal develevations in rest the rest in squal deflistration.</s>