On-chip calibration of RF detectors by DC stimuli and artificial neural networks

R. Ramzan, J. Dabrowski
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引用次数: 9

Abstract

In the nanometer regime, especially the RF and analog circuits exhibit wide parameter variability, and consequently every chip produced needs to be tested. On-chip design for testability (DfT) features, which are meant to reduce test time and cost also suffer from parameter variability. Therefore, RF calibration of all on-chip test structures is mandatory. In this paper, artificial neural networks (ANN) are employed as multivariate regression technique to architect a general RF calibration scheme using DC- instead of RF stimuli. This relaxes the routing requirements on a chip for GHz test signals along with the reduction in test time and cost. The RF detector, a key element of a radio front-end DfT circuitry, designed in 65 nm CMOS is used to demonstrate the calibration scheme.
基于直流刺激和人工神经网络的射频探测器片上标定
在纳米范围内,特别是射频和模拟电路表现出广泛的参数可变性,因此每个芯片都需要进行测试。片上可测试性设计(DfT)特征旨在减少测试时间和成本,但也受到参数可变性的影响。因此,必须对所有片上测试结构进行射频校准。本文采用人工神经网络(ANN)作为多元回归技术,构建了一种通用的射频校准方案,该方案使用直流而不是射频刺激。这就降低了芯片对GHz测试信号的路由要求,同时减少了测试时间和成本。射频检测器是射频前端DfT电路的关键元件,采用65nm CMOS设计,用于演示校准方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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