自适应阵列应用中LMS和N-LMS处理器的FPGA实现

Hirokazu Oba, Minseok Kim, Hiroyuki Arai
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引用次数: 12

摘要

提出了一种LMS(最小均方)和N-LMS(归一化LMS)处理器的定点实现方法。在N-LMS中,本文提出了一种用简单的移位运算代替除法的有效方法。通过在同一硬件平台上使用单个大规模现场可编程门阵列(FPGA)实现LMS、N-LMS和RLS(递归最小二乘)自适应阵列天线的收敛性能进行比较。它是通过考虑操作时钟速度而不是权重更新次数的实际处理时间来评估的。在某些特定情况下,与RLS相比,采用优化字长的定点操作和位移位操作代替除法,有望为LMS系列提供更快的实际FPGA处理时间
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FPGA Implementation of LMS and N-LMS Processor for Adaptive Array Applications
This paper proposed a fixed-point implementation method of LMS (least mean square) and N-LMS (normalized-LMS) processor. In N-LMS, this paper proposes an efficient method using simple bit-shift operation instead of division. The convergence performance in LMS, N-LMS and RLS (recursive least square) adaptive array antenna is compared by implementation with single large scale FPGA (field programmable gate array) on the same developed hardware platform. It was evaluated by using the actual processing time considering the operation clock speed instead of the number of weight updates. The fixed-point operation with optimized word length and bit-shift operation instead of division are expected to provide faster actual FPGA processing time for LMS families compared with RLS in some specific cases
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