ABSTRACT With the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers.

中文翻译：

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用于精确 NanoCMOS 可变增益放大器性能的高效递归最小二乘参数估计算法

摘要 随着集成电路技术的大规模扩展，对于寻求解决某些纳米级 CMOS 参数挑战的设计人员来说，参数估计是一项关键任务。本文介绍了使用双平方权重 (BW) 方法和新的递归最小二乘法 (RLS) 参数估计算法对 16 nm 至 10 nm 工艺节点的 CMOS 晶体管的主要参数进行预测。所提出的 RLS 算法包括最小化与预测误差相关的二次准则，以获得所开发数学模型的最佳估计参数。由于提出的 RLS 算法获得的结果比使用 BW 方法获得的结果要好。将预测技术模型（PTM）数据与RLS算法估计的参数进行比较，以检验所提算法的有效性和一致性。这些预测的主要参数有助于估计和优化可变增益放大器 (VGA) 的性能，该放大器是一种基本电路元件，在即将推出的新接收器的设计中起着关键作用。