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Computational Analysis and Measurement for SDR-based Spectrum Sensing System Design on Single Board Computer

소프트웨어 정의 라디오 기반 스펙트럼 센싱 시스템 설계를 위한 단일 보드 컴퓨터 내 연산 분석 및 측정 연구

  • Received : 2019.09.28
  • Accepted : 2019.11.12
  • Published : 2019.12.31

Abstract

In recent years, IoT device and platform become widely popular and the computing performance and capabilities of IoT devices are also getting improved. However, the size and computing resources of IoT devices, especially small single board computer, are limited in a way that the design and implementation of the system should be carefully considered to operate on the devices. Recently, SDR technologies are adapting in IoT devices and can perform various radio systems. Thorough analysis and investigation of computer performances on small single board computer are necessary for its usage. In this paper, we present the results of computing resources measurement and analysis on small single-board computers. At first, we consider to design SDR based spectrum sensing for single board computer, investigate various key factors and propose a design procedure that can affect performance of the system with experiments.

최근 IoT 기기 및 플랫폼들의 발전 및 확장과 더불어 IoT 관련 기기 내 연산 성능도 지속해서 향상하고 있다. 그러나 기기 향상과는 별개로 IoT 기기, 특히 소형 단일 보드 컴퓨터의 제한적인 크기 및 연산 자원은 해당 기기 내 통신 시스템 구현 설계를 위한 중요 고려사항 중 하나이다. 현재 다양한 무선 통신 시스템을 활용할 수 있게끔 소프트웨어 정의 라디오 (SDR) 기술을 IoT 기기에 적용 시 소형 단일 보드 컴퓨터의 하드웨어 제한 사항으로 인한 열화 가능성으로 인하여 실제 시스템의 원활한 적용을 위해 해당 컴퓨터 성능에 대한 분석 및 조사가 필요하다. 본 논문에서는 소형 단일 보드 컴퓨터 내 SDR 적용 스펙트럼 센싱 시스템 디자인을 위한 시스템 연산 분석 및 실험을 진행한다. 먼저 단일 보드 컴퓨터를 위한 SDR 기반 스펙트럼 센싱 시스템을 설계하고 시스템 성능에 영향을 줄 수 있는 다양한 요소를 실험을 통해 조사하며. 이를 통한 중요 고려사항 및 디자인 가이드 절차를 도출한다.

Keywords

References

  1. F. Dahlqvist, M. Patel, A. Rajko, and J. Shulman, "Growing opportunities in the Internet of Things", McKinsey & Company, pp. 1-6, July 2019.
  2. S. Y. Oh, "[IFA 2019] Samsung's 5G and LG's Artificial Intelligence Ahead of Europe's Largest Consumer Electronics Event" [Internet] Available: http://m.elec4.co.kr/article/articleView.asp?idx=24002
  3. SmartThings Developer Documentation [Internet] Available: https://smartthings.developer.samsung.com
  4. J. R. Machado-Fernandez, . "Software defined radio: Basic principles and applications.", Facultad de Ingenieria, vol. 24, no. 38, pp.79-96., 2015 https://doi.org/10.19053/01211129.3160
  5. M. Mishra, A. Potnis, P. Dwivedy, S. K. Meena, "Software defined radio based receivers using RTLSDR: A review.", in 2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE). IEEE, 2017.
  6. S. E. Barrak, A. Lyhyaoui, A Puilafito, S. Serrano, "Implementation of a low cost SDR-Based Spectrum sensing Prototype Using USRP and Rasbperry Pi Board." in Proceedings of Engineering and Technology-PET 20, pp. 54-58, 2017
  7. E. G. Sierra, and G. A. R. Arroyave. "Low cost SDR spectrum analyzer and analog radio receiver using GNU radio, raspberry Pi2 and SDR-RTL dongle." in 2015 7th IEEE Latin-American Conference on Communications (LATINCOM). IEEE, 2015.
  8. S. Sabarinath, R. Shyam, C. Aneesh, R. Gandhraj, K. P. Soman, "Accelerated FFT computation for GNU radio using GPU of raspberry Pi." in Computational Intelligence in Data Mining-Volume 2., pp. 657-664, Springer, New Delhi, 2015.
  9. H. J. Park, G. M. Lee, S. H. Shin, B. H. Roh, J. M. Oh, "Implementation of Multi-Hop Cognitive Radio Testbed using Raspberry Pi and USRP." International Journal of Interdisciplinary Telecommunications and Networking (IJITN), vol. 9, no. 4, pp. 37-48, 2017 https://doi.org/10.4018/IJITN.2017100105
  10. S. Mohammed, K. A. Hatim, "Raspberry Pi and RTL-SDR for Spectrum Sensing based on FM Real Signals." in 2018 6th International Conference on Multimedia Computing and Systems (ICMCS). IEEE, 2018.
  11. J. Y. Kim, , A. C. Marcum, A. D. Balmos, A. W. Layton, S. G. Larew, J. V. Krogmeier, and D. J. Love. "Implementation and analysis of energy detection-based sensing using USRP/SBX platform." In 2014 IEEE Military Communications Conference, pp. 1504-1509. IEEE, 2014.
  12. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and Clifford Stein. Introduction to algorithms. MIT press, 2009
  13. M. T. Heath, Scientific computing: an introductory survey. Vol. 80. SIAM, 2018.
  14. BCM2835 - Raspberry Pi Documentation [Internet]. Available: https://www.raspberrypi.org/documentation/hardware/raspberrypi/bcm2835/README.md
  15. BCM2836 - Raspberry Pi Documentation [Internet]. Available: https://www.raspberrypi.org/documentation/hardware/raspberrypi/bcm2836/README.md
  16. BCM2837 - Raspberry Pi Documentation [Internet]. Available: https://www.raspberrypi.org/documentation/hardware/raspberrypi/bcm2837/README.md
  17. RTL-SDR Blog V3 Datasheet [Internet]. Available: https://www.electrokit.com/uploads/productfile/41015/RTL-SDR-Blog-V3-Datasheet.pdf
  18. H. T. Thien, R. Tendeng, H. Vu-Van, and I. Koo. "Implementation of Spectrum-Sensing for Cognitive Radio Using USRP with GNU Radio and a Cloud Server." Journal of information and communication convergence engineering, vol 16, no. 1, pp. 23-30, 2018 https://doi.org/10.6109/jicce.2018.16.1.23