Exploiting the Dynamically Architectural Configurability in Compressed Sensing

Project Description:

 Sensors or sensing systems are increasingly critical in a variety of applications including national security, surveillance monitoring and health care. Those systems should function with minimal hardware recourses, minimal communications and minimal computation overhead, and these efficiencies can dramatically improve the performance, reliability and usability, which can broaden the overall application scope of sensor systems. This project is to pursue preliminary results of dynamic configurability of architectural and circuit models in sensing systems, and the proposed research will have significant impacts on a range of sensing applications under the resource-constrained environment. For example, in large-scale sensor networks or implantable sensors, energy is tightly constrained. The ultimate goal of the research is to exploit the configurability and dynamics of sensing systems to improve the overall system efficiency. This project serves as an expedition to investigate the dynamically architectural sensing techniques and may open a new research direction of theory and practice in the signal acquisition. Upon the success of this project, a better performance-energy tradeoff in the sensing system will be obtained, which can further strengthen its advantage compared to other sampling techniques, and extend its application regime.


  • This Project is in part supported by the U.S. National Science Foundation ECCS-1462498.


    Wenyao Xu (PI)

    Aosen Wang (Ph.D. student)

    Chen Song (Ph.D. student)


    Dr. Zhanpeng Jin, University at Buffalo, USA

    Dr. Jian Xiao, Chang'an University, China

    Publications from the project:

  • [11] Chen Song, Aosen Wang, Feng Lin, Jian Xiao, Xinwei Yao, Wenyao Xu, "Selective CS: Energy-Efficient Sensing Architecture for Wireless Implantable Neural Decoding", to appear IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS)
  • [10] Chen Song, Aosen Wang, Feng Lin, Mohammadnabi Asmani, Ruogang Zhao, Zhanpeng Jin, Jian Xiao, Wenyao Xu, "Tempo-Spatial Compressed Sensing of Organ-on-a-chip for Pervasive Health", to appear IEEE Journal of Biomedical and Health Informatics (JBHI)
  • [9] Aosen Wang, Lizhong Chen, Wenyao Xu, "XPro: A Cross-End Processing Architecture for Data Analytics in Wearables", ACM/IEEE International Symposium on Computer Architecture (ISCA'17), Toronto, Canada, June 2017
  • [8] Chen Song, Aosen Wang, Feng Lin, Ruogang Zhao, Zhanpeng Jin, Wenyao Xu, "A Tempo-spatial Compressed Sensing Architecture for Efficient High-throughput Information Acquisition in Organs-on-a-chip", IEEE International Conference on Biomedical and Health Informatics (BHI'17), Orlando, Florida, February 2017
  • [7] Aosen Wang, Zhenpang Jin, Wenyao Xu, "A Programmable Analog-to-Information Converter for Agile Biosensing", IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED'16), San Francisco, California, August 2016
  • [6] Aosen Wang, Feng Lin, Zhanpeng Jin, Wenyao Xu, "Ultra-low Power Dynamic Knob in Adaptive Compressed Sensing towards Biosignal Dynamics", IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), Volume 10, Number 3, June 2016, Pages 579 - 592
  • [5] Aosen Wang, Feng Lin, Zhanpeng Jin, Wenyao Xu, "A Configurable Energy-Efficient Compressed Sensing Architecture with its Application on Body Sensor Networks", IEEE Transactions on Industrial Informatics (TII), Volume 12, Issue 1, January 2016, Pages 15 - 27
  • [4] Aosen Wang, Chen Song, Xiaowei Xu, Feng Lin, Zhanpeng Jin, Wenyao Xu, "Selective and Compressed Sensing for Energy-Efficient Implantable Neural Encoding", IEEE Conference on Biomedical Circuits and Systems (BioCAS'15), Atlanta, Georgia, October 2015
  • [3] Aosen Wang, Chen Song, Zhanpeng Jin, Wenyao Xu, "Adaptive Compressed Sensing Architecture in Wireless Brain Computer Interface", ACM/IEEE Design Automation Conference (DAC'15), San Francisco, California, June 2015
  • [2] Aosen Wang, Wenyao Xu, Zhanpeng Jin, Fang Gong, "Quantization Effects in an Analog-to-Information Front-end in EEG Tele-Monitoring", IEEE Transactions on Circuits and Systems II (TCAS-II), Volume 62, Issue 2, February 2015, Pages 104 - 108
  • [1] Aosen Wang, Chen Song, Wenyao Xu, "A Configurable Quantized Compressed Sensing Architecture for Low-Power Tele-Monitoring", International Green Computing Conference (IGCC'14), Dallas, Texas, November 2014