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Non-Uniform Quantization of Successive Cancellation List Decoder for Polar Codes

机译:极性码的连续消除列表解码器的非均匀量化

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A good quantization scheme plays a tremendously important role in the hardware implementation of the decoder for polar codes. In this paper, a non-uniform quantization scheme for cyclic redundancy check aided successive-cancellation list (CA-SCL) decoder of polar codes is proposed to save memory resources. In the proposed non-uniform quantization scheme, we introduce a simple compression function to decrease the truncation threshold so that the soft information can be quantized with fewer quantization bits. The scaling factor in the compression function is a negative integer power of two, which can be efficiently implemented by shift operations. Then a compressed-domain CA-SCL decoder is derived, alleviating the need to decompress samples one-by-one. Simulation results show that on the condition of approaching floating-point performance, the internal log-likelihood ratio (LLR) memory resource consumption can be saved by 20% compared with uniform quantization.
机译:良好的量化方案在极性码解码器的硬件实现中起着极其重要的作用。为了节省存储资源,提出了一种非均匀量化的极性码循环冗余校验辅助连续消除列表(CA-SCL)解码器。在提出的非均匀量化方案中,我们引入了一个简单的压缩函数来降低截断阈值,从而可以用更少的量化位来量化软信息。压缩函数中的比例因子是2的负整数幂,可以通过移位操作有效地实现。然后,导出一个压缩域CA-SCL解码器,从而减少了对样本进行一次解压缩的需要。仿真结果表明,在达到浮点性能的条件下,与统一量化相比,内部对数似然比(LLR)内存资源消耗可以节省20%。

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