MIGOU: A Low-Power Experimental Platform with Programmable Logic Resources and Software-Defined Radio Capabilities

被引:5
作者
Utrilla, Ramiro [1 ]
Rodriguez-Zurrunero, Roberto [1 ]
Martin, Jose [1 ]
Rozas, Alba [1 ]
Araujo, Alvaro [1 ]
机构
[1] Univ Politecn Madrid, ETSI Telecomunicac, B105 Elect Syst Lab, Av Complutense 30, E-28040 Madrid, Spain
关键词
platform; IoT; end-device; cognitive radio; edge computing; software-defined radio; WIRELESS;
D O I
10.3390/s19224983
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The increase in the number of mobile and Internet of Things (IoT) devices, along with the demands of new applications and services, represents an important challenge in terms of spectral coexistence. As a result, these devices are now expected to make an efficient and dynamic use of the spectrum, and to provide processed information instead of simple raw sensor measurements. These communication and processing requirements have direct implications on the architecture of the systems. In this work, we present MIGOU, a wireless experimental platform that has been designed to address these challenges from the perspective of resource-constrained devices, such as wireless sensor nodes or IoT end-devices. At the radio level, the platform can operate both as a software-defined radio and as a traditional highly integrated radio transceiver, which demands less node resources. For the processing tasks, it relies on a system-on-a-chip that integrates an ARM Cortex-M3 processor, and a flash-based FPGA fabric, where high-speed processing tasks can be offloaded. The power consumption of the platform has been measured in the different modes of operation. In addition, these hardware features and power measurements have been compared with those of other representative platforms. The results obtained confirm that a state-of-the-art tradeoff between hardware flexibility and energy efficiency has been achieved. These characteristics will allow for the development of appropriate solutions to current end-devices' challenges and to test them in real scenarios.
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页数:16
相关论文
共 23 条
  • [1] Fog and IoT: An Overview of Research Opportunities
    Chiang, Mung
    Zhang, Tao
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2016, 3 (06): : 854 - 864
  • [2] Cisco Systems Inc., 2019, CISC VIS NETW IND GL
  • [3] Dutta R, 2010, INT SYMP ADV NETW, P1, DOI 10.1109/ANTS.2010.5983509
  • [4] Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends
    Joshi, Gyanendra Prasad
    Nam, Seung Yeob
    Kim, Sung Won
    [J]. SENSORS, 2013, 13 (09) : 11196 - 11228
  • [5] Kuo YK, 2019, OPTICS, PHOTONICS AND LASERS (OPAL 2019), P6
  • [6] Revisiting Software Defined Radios in the IoT Era
    Narayanan, Revathy
    Kumar, Swarun
    [J]. HOTNETS-XVII: PROCEEDINGS OF THE 2018 ACM WORKSHOP ON HOT TOPICS IN NETWORKS, 2018, : 43 - 49
  • [7] Polastre J, 2005, 2005 Fourth International Symposium on Information Processing in Sensor Networks, P364
  • [8] Edge Computing for the Internet of Things: A Case Study
    Premsankar, Gopika
    Di Francesco, Mario
    Taleb, Tarik
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (02): : 1275 - 1284
  • [9] Electrosense: Open and Big Spectrum Data
    Rajendran, Sreeraj
    Calvo-Palomino, Roberto
    Fuchs, Markus
    Van den Bergh, Bertold
    Cordobes, Hector
    Giustiniano, Domenico
    Pollin, Sofie
    Lenders, Vincent
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2018, 56 (01) : 210 - 217
  • [10] A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices
    Ravi, Daniele
    Wong, Charence
    Lo, Benny
    Yang, Guang-Zhong
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2017, 21 (01) : 56 - 64