论文标题
低分辨率水平和垂直分层的共同信息最大化LDPC解码
Low-Resolution Horizontal and Vertical Layered Mutual Information Maximizing LDPC Decoding
论文作者
论文摘要
我们研究了具有水平和垂直分层调度的准循环LDPC代码的迭代低分辨率通话算法。粗量化和分层调度与硬件实现非常相关，以减少消息的位宽度和解码迭代的数量。作为新颖性，本文将两种调度变体与相互信息结合使用，以最大化变量和检查节点的压缩操作进行比较。我们评估了各种配置的复杂性和错误率性能。常规准循环LDPC解码器的专用硬件体系结构以概念级别得出。硬件资源估计确认，大多数复杂性都在路由网络操作中。我们的模拟显示两个分层时间表的错误率性能相似，但水平解码器的平均迭代计数略低。
We investigate iterative low-resolution message-passing algorithms for quasi-cyclic LDPC codes with horizontal and vertical layered schedules. Coarse quantization and layered scheduling are highly relevant for hardware implementations to reduce the bit width of messages and the number of decoding iterations. As a novelty, this paper compares the two scheduling variants in combination with mutual information maximizing compression operations in variable and check nodes. We evaluate the complexity and error rate performance for various configurations. Dedicated hardware architectures for regular quasi-cyclic LDPC decoders are derived on a conceptual level. The hardware-resource estimates confirm that most of the complexity lies within the routing network operations. Our simulations reveal similar error rate performance for both layered schedules but a slightly lower average iteration count for the horizontal decoder.
