Title: Analysis and circuit sizing performance of a differential amplifier using HPSO algorithm

Authors: Chabungbam Lison Singh; Ashim Jyoti Gogoi; Chabungbam Anandini; Krishna Lal Baishnab; Loukrakpam Merin

Addresses: VLSI Laboratory, ECE Department, National Institute of Technology, Silchar, Assam, 788010, India ' VLSI Laboratory, ECE Department, National Institute of Technology, Silchar, Assam, 788010, India ' VLSI Laboratory, ECE Department, National Institute of Technology, Silchar, Assam, 788010, India ' VLSI Laboratory, ECE Department, National Institute of Technology, Silchar, Assam, 788010, India ' VLSI Laboratory, ECE Department, National Institute of Technology, Silchar, Assam, 788010, India

Abstract: This paper presents an analysis of thermal noise of differential amplifier and automated sizing procedure with thermal noise incorporation, in addition to various design specifications, as constraints in the design process. Human behaviour-based particle swarm optimisation (HPSO), a swarm intelligence (SI)-based optimisation algorithm is used to perform the sizing task to obtain optimal value of design variables value subject to a satisfying set of constraints, with the main objective of designing a low-noise amplifier with minimum circuit area. The presented design procedure gives an option of considering both width and length of MOS transistor as design variables, which in turn can tune trade-off circuit performance parameters. The computational analysis is performed in MATLAB and CADENCE tool with UMC 180 nm parameters technology is used to validate the presented design procedure. Further, the performance of the purposed automated design methodology is compared with previous design methodology to check its efficiency in terms of speed, time and robustness.

Keywords: human behaviour-based particle swarm optimisation; HPSO; differential amplifier; thermal noise; area optimisation; circuit sizing.

DOI: 10.1504/IJNP.2019.099187

International Journal of Nanoparticles, 2019 Vol.11 No.2, pp.167 - 180

Received: 21 Dec 2017
Accepted: 06 Oct 2018
Published online: 19 Apr 2019 *

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