High inductance fractal inductors for wireless applications

Padavala, Akhendra Kumar; Nistala, Bheema Rao

doi:10.3906/elk-1607-190

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…Type/model Average run time (s) Lower order fractal inductor EM Simulation 1800 Higher order fractal inductor EM Simulation 6000 Fractal loop inductor [3] EM Simulation 2200 Series stacked fractal inductor [4] EM Simulation 8900 Proposed work FNNPSOGSA 44…”

Section: Inductor Typementioning

confidence: 99%

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Design of an on-chip Hilbert fractal inductor using an improved feed forward neural network for Si RFICs

Padavala¹,

Nistala²

2018

Turk J Elec Eng & Comp Sci

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This paper presents an efficient modeling of Hilbert fractal inductors by improved feed forward neural network trained hybrid particle swarm optimization and gravitational search algorithm (FNNPSOGSA). The proposed model computes the effective inductance value (L) and quality factor (Q) of Hilbert fractal inductors with metal trace width, effective fractal length, frequency, and oxide thickness as input parameters. In contrast to the traditional feed forward neural network, the proposed FNNPSOGSA has been designed with fewer hidden neurons with much-enhanced learning and generalization capabilities. As a consequence, the proposed model achieves better speed and is as accurate as electromagnetic simulations. From the simulation results, it is proved that the proposed model is a good alternative for complex fractal inductor design.

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Section: Inductor Typementioning

confidence: 99%

“…An exhaustive study of conventional fractal inductors was carried out in [1,2]. The modified fractal inductors are proposed in single and multilayer processes to achieve higher L and Q values [3,4]. These fractal inductors are designed using an EM simulator, which gives accurate results but is time-consuming.…”

Section: Introductionmentioning

confidence: 99%

Design of an on-chip Hilbert fractal inductor using an improved feed forward neural network for Si RFICs

Padavala¹,

Nistala²

2018

Turk J Elec Eng & Comp Sci

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“…Despite high performance, the spiral inductors are unable to achieve higher inductance for the miniaturized on-chip area (Kuhn and Ibrahim, 2001). This problem is solved using fractal curves in the implementation of the inductor (Lazarus et al , 2014; Padavala and Nistala, 2017; Maric et al , 2008). The space-filling property of the fractal curves results in longer conductive segments that leads to high inductance density while occupying the equal on-chip area (Sagan, 2012).…”

Section: Introductionmentioning

confidence: 99%

High-quality factor multipath differential fractal inductor for wireless applications

Tumma

Nistala

2021

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Purpose The purpose of this study is to develop a high-quality factor fractal inductor for wireless applications such as satellite, WLAN, Bluetooth, microwave, radar and cellular phone. Design/methodology/approach The Hilbert fractal curve is used in the implementation of the proposed inductor. In the proposed inductor, the metal width has split into multiple paths based on the skin depth of the metal. The simulations of the proposed inductor are performed in 180 nm CMOS technology using the Advanced Design System EM simulator. Findings The multipath technique reduces the skin effects and proximity effects, which, in turn, decreases the series resistance of the inductor and attains high-quality factor over conventional fractal inductor for the equal on-chip area. Research limitations/implications The width of the path has chosen higher than the skin depth of the metal for a required operating frequency. Due to cost constraints, the manufacturing of the proposed fractal inductor is limited to a single layer. Practical implications The proposed inductor will be useful for the implementation of critical building blocks of radio frequency integrated circuits and monolithic microwave integrated circuits such as low-noise amplifiers, voltage-controlled oscillators, mixers, filters and power amplifiers. Originality/value This paper presents for the first time the use of a multipath technique for the fractal inductors to enhance the quality factor.

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“…In contrast, conventional planar inductors require a large on-chip area to achieve high inductance values. Fractal geometry-based inductors act as a feasible solution to achieve higher inductance due to longer trace lengths [2][3][4]. The conventional series stacked fractal inductor (CSSFI) improves the inductance and self-resonance frequency ( f SR ) and reduces the quality factor (Q) [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Design of a high performance narrowband low noise amplifier using an on-chip orthogonal series stacked differential fractal inductor for 5G applications

Tumma¹,

Nistala²

2020

Turk J Elec Eng & Comp Sci

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Inductors play a crucial role in the design of radio frequency integrated circuits (RFICs) and they typically consume a considerably large area and have a low-quality factor at high frequencies.The employment of fractal structure in on-chip inductors helps in improving the quality factor and also reduces the overall area besides improving the inductance value. In this paper, an orthogonal series stacked differential fractal inductor is proposed and the same is used to design a low noise amplifier (LNA) for 5G band (27-30 GHz) applications. The proposed inductor is fabricated on a multilayer printed circuit board and the measurement results demonstrate twice the enhancement in inductance, 56% improvement in quality factor, and 33% reduction in series resistance when compared to the conventional series stacked fractal inductor for the equivalent on-chip area. The LNA using cascode topology with inductive source degeneration is designed and simulated at a center frequency of 28 GHz in 90 nm CMOS technology using the tool Advanced Design System. The inductors in the LNA are replaced with the proposed on-chip inductor for different layers, which contributes to high gain, better input matching, and low noise figure compared to the state-of-the-art LNAs.

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High inductance fractal inductors for wireless applications

Cited by 6 publications

References 12 publications

Design of an on-chip Hilbert fractal inductor using an improved feed forward neural network for Si RFICs

Design of an on-chip Hilbert fractal inductor using an improved feed forward neural network for Si RFICs

High-quality factor multipath differential fractal inductor for wireless applications

Design of a high performance narrowband low noise amplifier using an on-chip orthogonal series stacked differential fractal inductor for 5G applications

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