Reconfigurable analog signal processing for wireless sensor networks

Kelly, Brandon M.; Rumberg, Brandon; Graham, David; Kulathumani, Vinod

doi:10.1109/mwscas.2013.6674625

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…Alternative triggering schemes can be made from analog front-ends designed for different signal-conditioning and classification schemes. For example, one could imagine an ADC triggered upon the detection of a certain frequency within a signal [11] or upon the detection of vocal characteristics of a signal [12]. Indeed, many energy-efficient analog front-ends [13] could provide a trigger for an asynchronous data converter.…”

Section: Asynchronous Quantizationmentioning

confidence: 99%

Reconfigurable Analog Preprocessing for Efficient Asynchronous Analog-to-Digital Conversion

Kelly

DiLello

Graham

2019

JLPEA

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Wearable medical devices, wireless sensor networks, and other energy-constrained sensing devices are often concerned with finding specific data within more-complex signals while maintaining low power consumption. Traditional analog-to-digital converters (ADCs) can capture the sensor information at a high resolution to enable a subsequent digital system to process for the desired data. However, traditional ADCs can be inefficient for applications that only require specific points of data. This work offers an alternative path to lower the energy expenditure in the quantization stage-asynchronous content-dependent sampling. This asynchronous sampling scheme is achieved by pairing a flexible analog front-end with an asynchronous successive-approximation ADC and a time-to-digital converter. The versatility and reprogrammability of this system allows a multitude of event-driven, asynchronous, or even purely data-driven quantization methods to be implemented for a variety of different applications. The system, fabricated in standard 0.5 µm and 0.35 µm processes, is demonstrated along with example applications with voice, EMG, and ECG signals.

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Section: Asynchronous Quantizationmentioning

confidence: 99%

Reconfigurable Analog Preprocessing for Efficient Asynchronous Analog-to-Digital Conversion

Kelly

DiLello

Graham

2019

JLPEA

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“…Since the primary energy cost is wireless reception of the configuration, we developed an entropy-coding algorithm to compress the configuration file [8]. For typical FPAA configurations, we achieve a compression factor of >4.…”

Section: System-level Implications Of Reconfigurationmentioning

confidence: 99%

Reconfiguration costs in analog sensor interfaces for wireless sensing applications

Rumberg

Graham

2013

2013 IEEE 56th International Midwest Symposium on Circuits and Systems (MWSCAS)

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Analog sensor interfaces are used in wireless sensor nodes to perform sensor conditioning, event detection, and data reduction. The use of reconfigurable interfaces will enable applications developers to customize these sensor interfaces and to reconfigure them in the field. In this paper, we examine the energy cost of reconfiguring analog circuitry and how the requirements of wireless sensor nodes impact the design of reconfigurable analog systems.

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“…The work in this Chapter has been presented in a conference paper and a conference demonstration. Our first FPAA was published in the Proceedings of the International Midwest Symposium on Circuits and Systems [192]. Our first FPAA was also shown in the demonstration session at the International Conference on Information Processing in Sensor Networks [193].…”

Section: Chapter 10mentioning

confidence: 99%

“…Since then, FPAAs have grown in size and programmability. We have surveyed approximately 30 FPAA designs (including [192,195,196,198,199,201,202,[209][210][211][212][213][214][215][216][217][218][219][220][221][222][223][224][225][226] as well as our two Netamorph designs in this Chapter) for the following illustrations of FPAA trends.…”

Section: Fpaa Trendsmentioning

confidence: 99%

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Rumberg¹

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Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device's analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits. iii Dedication To faculty and peers who have been so helpful, To family who won't try to read beyond this pageand more so to those who will, And to anyone who may benefit from this work. Contents Dedication iii List of Figures ix List of Tables xii Symbols and Acronyms xiii 12 Conclusions and Future Work 160 References 162 A Background on Sub-Threshold Analog Circuits 181 A.

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Reconfigurable analog signal processing for wireless sensor networks

Cited by 9 publications

References 9 publications

Reconfigurable Analog Preprocessing for Efficient Asynchronous Analog-to-Digital Conversion

Reconfigurable Analog Preprocessing for Efficient Asynchronous Analog-to-Digital Conversion

Reconfiguration costs in analog sensor interfaces for wireless sensing applications

Low-Power and Programmable Analog Circuitry for Wireless Sensors

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