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A High Throughput Hardware Architecture for Parallel Recursive Systematic Convolutional Encoders

机译:并行递归系统卷积编码器的高吞吐量硬件体系结构

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During the last years, recursive systematic convolutional (RSC) encoders have found application in modern telecommunication systems to reduce the bit error rate (BER). In view of the necessity of increasing the throughput of such applications, several approaches using hardware implementations of RSC encoders were explored. In this paper, we propose a hardware intellectual property (IP) for high throughput RSC encoders. The IP core exploits a methodology based on the ABCD matrices model which permits to increase the number of inputs bits processed in parallel. Through an analysis of the proposed network topology and by exploiting data relative to the implementation on Zynq 7000 xc7z010clg400-1 field programmable gate array (FPGA), an estimation of the dependency of the input data rate and of the source occupation on the parallelism degree is performed. Such analysis, together with the BER curves, provides a description of the principal merit parameters of a RSC encoder.
机译:在过去的几年中,递归系统卷积(RSC)编码器已在现代电信系统中得到应用,以降低误码率(BER)。考虑到增加此类应用的吞吐量的必要性,探索了使用RSC编码器的硬件实现的几种方法。在本文中,我们提出了一种用于高吞吐量RSC编码器的硬件知识产权(IP)。 IP内核采用了基于ABCD矩阵模型的方法,该方法允许增加并行处理的输入位数。通过对所建议的网络拓扑进行分析,并通过利用与Zynq 7000 xc7z010clg400-1现场可编程门阵列(FPGA)上的实现相关的数据,估计输入数据速率和源占用对并行度的依赖性为:执行。这种分析与BER曲线一起提供了RSC编码器的主要性能参数的描述。

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