论文标题
管道式架构,用于RM代码的软性迭代迭代投影聚合解码
Pipelined Architecture for Soft-decision Iterative Projection Aggregation Decoding for RM Codes
论文作者
论文摘要
最近提出的递归投影聚集(RPA)解码算法用于Reed-Muller代码,因此受到了极大的关注,因为它在短代码方面提供了近ML的解码性能。但是,其复杂的结构使其不适合硬件实现。迭代投影 - 聚集(IPA)解码是RPA解码的修改版本,简化了硬件实现。在这项工作中,我们为IPA解码器提供了一种灵活的硬件体系结构,可以从完全序列到完全平行的情况下配置,从而适合具有不同约束和资源预算的广泛应用程序。我们的仿真和实施结果表明,IPA解码器的面积消耗量降低了41%,延迟降低了44%,吞吐量提高了4倍,但目前,与具有比较解码功能的可比解码功能相比,块长度为128且信息长度为29的代码相比,块长度为128且信息长度为29的代码的功耗七倍。
The recently proposed recursive projection-aggregation (RPA) decoding algorithm for Reed-Muller codes has received significant attention as it provides near-ML decoding performance at reasonable complexity for short codes. However, its complicated structure makes it unsuitable for hardware implementation. Iterative projection-aggregation (IPA) decoding is a modified version of RPA decoding that simplifies the hardware implementation. In this work, we present a flexible hardware architecture for the IPA decoder that can be configured from fully-sequential to fully-parallel, thus making it suitable for a wide range of applications with different constraints and resource budgets. Our simulation and implementation results show that the IPA decoder has 41% lower area consumption, 44% lower latency, four times higher throughput, but currently seven times higher power consumption for a code with block length of 128 and information length of 29 compared to a state-of-the-art polar successive cancellation list (SCL) decoder with comparable decoding performance.