Decoder-Tailored Polar Code Design Using the Genetic Algorithm
Decoder-Tailored Polar Code Design Using the Genetic Algorithm
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DOI：
10.1109/tcomm.2019.2908870
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发表时间：
2019-07-01
影响因子：
8.3
通讯作者：
ten Brink, Stephan
中科院分区：
文献类型：
--
作者：
Elkelesh, Ahmed;Ebada, Moustafa;ten Brink, Stephan
我们提出了一种用于构造极化码的新框架（即，为任意信道选择冻结比特位置），适合于给定的解码算法，而不是假设（不一定是最佳的）连续消除（SC）解码。所提出的框架是基于遗传算法（GenAlg），其中种群（即，信息集的集合）基于它们各自的错误率性能经由进化变换而进化。这些群体收敛到一个信息集，适合解码行为和定义的通道。我们构造极化码，没有CRC辅助，适合于普通连续消除列表（SCL）解码，分别在AWGN信道和瑞利信道上实现与CRC辅助SCL解码相同的错误率性能。此外，建议的置信传播（BP）量身定制的建设接近SCL的错误率性能没有任何修改的解码算法本身。性能增益可以归因于低权重码字的数量的显着减少。我们表明，在需要时，GenAlg也可以设置找到代码，降低解码的复杂性。这样，SCL列表大小或BP迭代次数可以减少，同时保持相同的错误率性能。
We present a new framework for constructing polar codes (i.e., selecting the frozen bit positions) for arbitrary channels, tailored to a given decoding algorithm rather than assuming the (not necessarily optimal) successive cancellation (SC) decoding. The proposed framework is based on the genetic algorithm (GenAlg), where populations (i.e., collections) of information sets evolve via evolutionary transformations based on their individual error-rate performance. These populations converge toward an information set that fits both the decoding behavior and the defined channel. We construct polar codes, without the CRC-aid, tailored to plain successive cancellation list (SCL) decoding, achieving the same error-rate performance as the CRC-aided SCL decoding over both the AWGN channel and the Rayleigh channel, respectively. Furthermore, a proposed belief propagation (BP)-tailored construction approaches the SCL error-rate performance without any modifications in the decoding algorithm itself. The performance gains can be attributed to the significant reduction in the number of low-weight codewords. We show that, when required, the GenAlg can also be set up to find codes that reduce the decoding complexity. This way, the SCL list size or the number of BP iterations can be reduced while maintaining the same error-rate performance.