Ultra-low power electronics with Si/Ge tunnel FET

Trivedi, Amit Ranjan; Amir, Mohammad Faisal; Mukhopadhyay, Saibal

doi:10.7873/date.2014.244

Cited by 20 publications

(9 citation statements)

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“…As pointed out in [13][14][15], established design methodologies and tools as well as compact equations representing the device response in all the biasing design space are often required by analog IC designers as a guide for performing optimal circuit design. Here we discuss the gm/Id method and a compact device-model as some of such tools enabling TFET-based analog circuit design.…”

Section: The / Integrated Circuit Design Methods Applied To Tfetsmentioning

confidence: 99%

“…At a given bias current, the DC gain, bandwidth, noise performance and offset improve by increasing the transconductance of the input transistors. Work by Trivedi et al [13] shows that TFETs can reduce the power of analog amplifiers since the same transconductance as in a MOSFET based designs is achieved at lower powers through a higher gm/Id. In the present work a two-stage OTA with Miller effect compensation is designed by using the gm/Id method.…”

Section: Shown Inmentioning

confidence: 95%

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TFET-Based Circuit Design Using the Transconductance Generation Efficiency <inline-formula> <tex-math notation="LaTeX">$ {g}_{m}/ {I}_{d}$ </tex-math></inline-formula> Method

Barboni

Siniscalchi

Sensale‐Rodriguez

2015

IEEE J. Electron Devices Soc.

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Tunnel field effect transistors (TFETs) have emerged as one of the most promising post-CMOS transistor technologies. In this work we: (i) review the perspectives of such devices for low-power high-frequency analog IC applications (e.g. GHz operation with sub-0.1 mW power consumption), (ii) discuss and employ a compact TFET device model in the context of the gm/Id integrated analog circuit design methodology, and (iii) compare several proposed TFET technologies for such applications. The advantages of TFETs arise since these devices can operate in the sub-threshold region with larger transconductance-to-current ratio than traditional FETs, which is due to the current turn-on mechanism being inter-band tunneling rather than thermionic emission. Starting from TCAD and/or analytical models for Si-FinFETs, graphene nano-ribbon (GNR) TFETs, and InAs/GaSb TFETs at the 15-nm gate-length node, as well as InAs double-gate (DG) TFETs at the 20-nm gatelength node, we conclude that GNR TFETs might promise larger bandwidths at low voltage drives due to their high current densities in the sub-threshold region. Based on this analysis and on theoretically predicted properties, GNR TFETs are identified as one of the most attractive field effect transistor technologies proposed-to-date for ultra-low power analog applications.Index Terms-Si-FinFETs, Tunnel-FET, ultra low power design, gm/Id method, one-stage common-source amplifier, twostage OTA with Miller effect compensation.

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Section: The / Integrated Circuit Design Methods Applied To Tfetsmentioning

confidence: 99%

Section: Shown Inmentioning

confidence: 95%

TFET-Based Circuit Design Using the Transconductance Generation Efficiency <inline-formula> <tex-math notation="LaTeX">$ {g}_{m}/ {I}_{d}$ </tex-math></inline-formula> Method

Barboni

Siniscalchi

Sensale‐Rodriguez

2015

IEEE J. Electron Devices Soc.

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“…Energy efficiency represents one of the primary challenges in the development of WBSNs. 30,31 Since communication is the most power-consuming operation for sensor nodes, many current energy-efficient protocols are based on TPC and duty-cycling mechanisms. However, most of these solutions are expensive from both the computational and the memory resources' point of view, and therefore, they result in being hardly implementable on resources constrained devices, such as sensor nodes.…”

Section: Energy Efficiency With Cross-layer Approach In Wbsnsmentioning

confidence: 99%

“…However, most of these solutions are expensive from both the computational and the memory resources' point of view, and therefore, they result in being hardly implementable on resources constrained devices, such as sensor nodes. 31 The PHY layer plays a very important role in WBSN due to the dynamic nature of wireless channel. The power consumption of sensor nodes heavily depends on the PHY layer.…”

Section: Energy Efficiency With Cross-layer Approach In Wbsnsmentioning

confidence: 99%

“…Data uncertainty in WBSN can be foreseen, for example, to event-driven sensor nodes, which generates data only under some particular conditions, so that their data rate is not constant and even not exactly known earlier. 30,31,37 When any sensor node transmits data, it consumes energy, and a main focus is to develop the energy-efficient communication system to extend the battery lifetime of WBSNs. Figure 4 shows the power consumption in three different states: sleep state, idle state, and active state.…”

Section: Energy Efficiency With Cross-layer Approach In Wbsnsmentioning

confidence: 99%

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Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Sodhro

Chen

Sekhari

et al. 2018

International Journal of Distributed Sensor Networks

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This article presents comparison between data rate or rate control, that is, video transmission rate control algorithm and transmission power control algorithms for two different cases. First, energy consumption due to high peak variable data rates in video transmission. Second, energy depletion due to high transmission power consumption and dynamic nature of wireless on-body channel. The former one focuses on constant (fixed) transmission power level and variable data rate (''severe'' conditions), for example, medical monitoring of the emergency patients. The latter considers variable transmission power level and constant (fixed) data rate (''less severe'' conditions), for example, electrocardiography measurement for patients in wireless body sensor networks. Besides, energy efficiency comparison analysis of battery-driven or video transmission rate control algorithm and transmission power control-driven or power control algorithm is presented. Finally, proposed algorithms are analyzed and categorized as energy-efficient and battery-friendly for medical applications in wireless body sensor networks.

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Architectures for Self-Powered Edge Intelligence

Trivedi

Kung

2022

Handbook of Computer Architecture

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Ultra-low power electronics with Si/Ge tunnel FET

Cited by 20 publications

References 0 publications

TFET-Based Circuit Design Using the Transconductance Generation Efficiency <inline-formula> <tex-math notation="LaTeX">$ {g}_{m}/ {I}_{d}$ </tex-math></inline-formula> Method

TFET-Based Circuit Design Using the Transconductance Generation Efficiency <inline-formula> <tex-math notation="LaTeX">$ {g}_{m}/ {I}_{d}$ </tex-math></inline-formula> Method

Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Architectures for Self-Powered Edge Intelligence

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