Power macromodeling for high level power estimation
DAC '97 Proceedings of the 34th annual Design Automation Conference
Synthesis of power-optimized and area-optimized circuits from hierarchical behavioral descriptions
DAC '98 Proceedings of the 35th annual Design Automation Conference
A power macromodeling technique based on power sensitivity
DAC '98 Proceedings of the 35th annual Design Automation Conference
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An automated, reconfigurable, low-power RFID tag
Proceedings of the 43rd annual Design Automation Conference
Reducing power while increasing performance with supercisc
ACM Transactions on Embedded Computing Systems (TECS)
A Field Programmable RFID Tag and Associated Design Flow
FCCM '06 Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
An automated, FPGA-based reconfigurable, low-power RFID tag
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EURASIP Journal on Applied Signal Processing
Radio frequency identification prototyping
ACM Transactions on Design Automation of Electronic Systems (TODAES)
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IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on the 2002 international symposium on low-power electronics and design (ISLPED)
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EUC'06 Proceedings of the 2006 international conference on Embedded and Ubiquitous Computing
A Markov chain sequence generator for power macromodeling
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Optimizing power using transformations
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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While RFID has become a ubiquitous technology, there is still a need for RFID systems with different capabilities, protocols, and features depending on the application. This article describes a design automation flow and power estimation technique for fast implementation and design feedback of new RFID systems. Physical layer features are described using waveform features, which are used to automatically generate physical layer encoding and decoding hardware blocks. RFID primitives to be supported by the tag are enumerated with RFID macros and the behavior of each primitive is specified using ANSI-C within the template to automatically generate the tag controller. Case studies implementing widely used standards such as ISO 18000 Part 7 and ISO 18000 Part 6C using this automation technique are presented. The power macromodeling flow demonstrated here is shown to be within 5% to 10% accuracy, while providing results 100 times faster than traditional methods. When eliminating the need for certain features of ISO 18000 Part 6C, the design flow shows that the power required by the implementation is reduced by nearly 50%.