Heuristic and Statistical Power Estimation Model for FPGA Based Wireless Systems

Gaurav Verma, Tarun Singhal, Rahul Kumar, Shivam Chauhan, Sushant Shekhar, Bishwajeet Pandey, Dil muhammed Akbar Hussain

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Resumé

As the technology is advancing day by day, the need of high performance devices is also increasing. High performance is achieved at the expense of high power dissipation. Nowadays, field programmable gate arrays (FPGAs) are widely used in wireless communication systems due to their low non-recurring cost and high operating speed. There are many high performance applications (i.e., image processing, digital signal processing, wireless transceivers etc.) in which FPGAs are widely used. However, their complex architectures lead to high power consumption. Estimation of power in the early stage of the design flow would help designers to design the systems as per specified power budget. Therefore, two different approaches for power estimation are proposed in this paper. First is the heuristic approach based on back propagation neural network and second is the regression based statistical approach. It is observed that heuristic approach is better as compared regression in terms of power estimation of most of the digital circuits considered in this work.
OriginalsprogEngelsk
TidsskriftWireless Personal Communications
Vol/bind106
Udgave nummer4
Sider (fra-til)2087–2098
Antal sider12
ISSN0929-6212
DOI
StatusUdgivet - 2019

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Field programmable gate arrays (FPGA)
Digital circuits
Digital signal processing
Backpropagation
Transceivers
Energy dissipation
Communication systems
Image processing
Electric power utilization
Neural networks
Costs

Citer dette

Verma, Gaurav ; Singhal, Tarun ; Kumar, Rahul ; Chauhan, Shivam ; Shekhar, Sushant ; Pandey, Bishwajeet ; Hussain, Dil muhammed Akbar. / Heuristic and Statistical Power Estimation Model for FPGA Based Wireless Systems. I: Wireless Personal Communications. 2019 ; Bind 106, Nr. 4. s. 2087–2098.
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title = "Heuristic and Statistical Power Estimation Model for FPGA Based Wireless Systems",
abstract = "As the technology is advancing day by day, the need of high performance devices is also increasing. High performance is achieved at the expense of high power dissipation. Nowadays, field programmable gate arrays (FPGAs) are widely used in wireless communication systems due to their low non-recurring cost and high operating speed. There are many high performance applications (i.e., image processing, digital signal processing, wireless transceivers etc.) in which FPGAs are widely used. However, their complex architectures lead to high power consumption. Estimation of power in the early stage of the design flow would help designers to design the systems as per specified power budget. Therefore, two different approaches for power estimation are proposed in this paper. First is the heuristic approach based on back propagation neural network and second is the regression based statistical approach. It is observed that heuristic approach is better as compared regression in terms of power estimation of most of the digital circuits considered in this work.",
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author = "Gaurav Verma and Tarun Singhal and Rahul Kumar and Shivam Chauhan and Sushant Shekhar and Bishwajeet Pandey and Hussain, {Dil muhammed Akbar}",
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Heuristic and Statistical Power Estimation Model for FPGA Based Wireless Systems. / Verma, Gaurav; Singhal, Tarun; Kumar, Rahul; Chauhan, Shivam; Shekhar, Sushant; Pandey, Bishwajeet; Hussain, Dil muhammed Akbar.

I: Wireless Personal Communications, Bind 106, Nr. 4, 2019, s. 2087–2098.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

TY - GEN

T1 - Heuristic and Statistical Power Estimation Model for FPGA Based Wireless Systems

AU - Verma, Gaurav

AU - Singhal, Tarun

AU - Kumar, Rahul

AU - Chauhan, Shivam

AU - Shekhar, Sushant

AU - Pandey, Bishwajeet

AU - Hussain, Dil muhammed Akbar

PY - 2019

Y1 - 2019

N2 - As the technology is advancing day by day, the need of high performance devices is also increasing. High performance is achieved at the expense of high power dissipation. Nowadays, field programmable gate arrays (FPGAs) are widely used in wireless communication systems due to their low non-recurring cost and high operating speed. There are many high performance applications (i.e., image processing, digital signal processing, wireless transceivers etc.) in which FPGAs are widely used. However, their complex architectures lead to high power consumption. Estimation of power in the early stage of the design flow would help designers to design the systems as per specified power budget. Therefore, two different approaches for power estimation are proposed in this paper. First is the heuristic approach based on back propagation neural network and second is the regression based statistical approach. It is observed that heuristic approach is better as compared regression in terms of power estimation of most of the digital circuits considered in this work.

AB - As the technology is advancing day by day, the need of high performance devices is also increasing. High performance is achieved at the expense of high power dissipation. Nowadays, field programmable gate arrays (FPGAs) are widely used in wireless communication systems due to their low non-recurring cost and high operating speed. There are many high performance applications (i.e., image processing, digital signal processing, wireless transceivers etc.) in which FPGAs are widely used. However, their complex architectures lead to high power consumption. Estimation of power in the early stage of the design flow would help designers to design the systems as per specified power budget. Therefore, two different approaches for power estimation are proposed in this paper. First is the heuristic approach based on back propagation neural network and second is the regression based statistical approach. It is observed that heuristic approach is better as compared regression in terms of power estimation of most of the digital circuits considered in this work.

KW - Regression

KW - VHDL

KW - MATLAB

KW - Xpower analyser (XPA)

KW - Heuristic

U2 - 10.1007/s11277-018-5927-7

DO - 10.1007/s11277-018-5927-7

M3 - Conference article in Journal

VL - 106

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JO - Wireless Personal Communications

JF - Wireless Personal Communications

SN - 0929-6212

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