Turbo码解码超过100 Gb/s的先进硬件架构

Stefan Weithoffer, Oliver Griebel, Rami Klaimi, C. A. Nour, N. Wehn
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引用次数: 6

摘要

在本文中,我们提出了两种结合了功能并行、空间并行和迭代并行的Turbo Code译码硬件架构。我们的第一个架构是第一个支持多种帧大小的完全流水线迭代展开架构。这种帧灵活性是通过提供一组交织器来实现的,这些交织器旨在实现具有较少路由开销的硬件实现。第二种结构有效地利用了不同译码迭代错误率分布的动态特性,分为两个阶段。首先,一个完全流水线化的迭代展开解码器阶段适用于预先确定的迭代次数,第二阶段具有迭代加力-解码器,仅对第一阶段未成功解码的帧激活。我们给出了在最大帧大小为K = 128的情况下实现这两种架构的后置和路由结果,并演示了在2S nm FDSOI技术下的102.4 Gb/s吞吐量。面积效率分别为6.19和7.15 Gb/s/m$m^{2}$我们的实现明显优于目前的技术水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced Hardware Architectures for Turbo Code Decoding Beyond 100 Gb/s
In this paper, we present two new hardware architectures for Turbo Code decoding that combine functional, spatial and iteration parallelism. Our first architecture is the first fully pipelined iteration unrolled architecture that supports multiple frame sizes. This frame flexibility is achieved by providing a set of interleavers designed to achieve a hardware implementation with a reduced routing overhead. The second architecture efficiently utilizes the dynamics of the error rate distribution for different decoding iterations and is comprised of two stages. First, a fully pipelined iteration unrolled decoder stage applied for a pre-determined number of iterations and a second stage with an iterative afterburner-decoder activated only for frames not successfully decoded by the first stage. We give post place & route results for implementations of both architectures for a maximum frame size of K = 128 and demonstrate a throughput of 102.4 Gb/s in 2S nm FDSOI technology. With an area efficiency of 6.19 and 7.15 Gb/s/m$m^{2}$ our implementations clearly outperform state of the art.
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