DOI QR코드

DOI QR Code

Real-time implementation of distributed beamforming for simultaneous wireless information and power transfer in interference channels

  • Hong, Yong-Gi (Department of Electronic Engineering, Pukyong National University) ;
  • Hwang, SeongJun (Department of Electronic Engineering, Pukyong National University) ;
  • Seo, Jiho (Department of Electronic Engineering, Pukyong National University) ;
  • Lee, Jonghyeok (Department of Electronic Engineering, Pukyong National University) ;
  • Park, Jaehyun (Department of Electronic Engineering, Pukyong National University)
  • Received : 2020.02.13
  • Accepted : 2020.07.30
  • Published : 2021.06.01

Abstract

In this paper, we propose one-bit feedback-based distributed beamforming (DBF) techniques for simultaneous wireless information and power transfer in interference channels where the information transfer and power transfer networks coexist in the same frequency spectrum band. In a power transfer network, multiple distributed energy transmission nodes transmit their energy signals to a single energy receiving node capable of harvesting wireless radio frequency energy. Here, by considering the Internet-of-Things sensor network, the energy harvesting/information decoding receivers (ERx/IRx) can report their status (which may include the received signal strength, interference, and channel state information) through one-bit feedback channels. To maximize the amount of energy transferred to the ERx and simultaneously minimize the interference to the IRx, we developed a DBF technique based on one-bit feedback from the ERx/IRx without sharing the information among distributed transmit nodes. Finally, the proposed DBF algorithm in the interference channel is verified through the simulations and also implemented in real time by using GNU radio and universal software radio peripheral.

Keywords

Acknowledgement

This work is supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (2018R1D1A1B07043786).

References

  1. S. C. Lee et al., Design and implementation of wireless sensor based-monitoring system for smart factory, in Proc. Int. Conf. Comput. Sci. Applicat. (Kuala Lumpur, Malaysia), 2007, pp. 584-592.
  2. B. Holfeld et al., Wireless communication for factory automation: an opportunity for LET and 5G systems, IEEE Commun. Mag. 54 (2016), 36-43. https://doi.org/10.1109/MCOM.2016.7497764
  3. A. Gonga, O. Landsiedel, and M. Johansson, MobiSense: Power-efficient micro-mobility in wireless sensor networks, in Proc. IEEE Int. Conf. Distrib. Comput. Sens. Syst. (Barcelona, Spain), June 2011, pp. 1-8.
  4. J. Ren et al., RF energy harvesting and transfer in cognitive radio sensor networks: Opportunities and challenges, IEEE Commun. Mag. 56 (2018), 104-110.
  5. H. Ju, Y. Lee, and T.-J. Kim, Full-duplex operations in wireless powered communication networks, ETRI J. 39 (2017), 794-802. https://doi.org/10.4218/etrij.17.0117.0217
  6. S. Lee, R. Zhang, and K. Huang, Opportunistic wireless energy harvesting in cognitive radio networks, IEEE Trans. Wirel. Commun. 12 (2013), 4788-4799. https://doi.org/10.1109/TWC.2013.072613.130323
  7. J. Park and B. Clerckx, Joint wireless information and energy transfer in a K-user MIMO interference channel, IEEE Trans. Wireless Commun. 13 (2014), 5781-5796. https://doi.org/10.1109/TWC.2014.2341233
  8. J. Park and B. Clerckx, Joint wireless information and energy transfer with reduced feedback in MIMO interference channels, IEEE J. Selected Areas Commun. 33 (2015), 1563-1577. https://doi.org/10.1109/JSAC.2015.2391684
  9. J. Park et al., An analysis of the optimum node density for simultaneous wireless information and power transfer in Ad Hoc networks, IEEE Trans. Veh. Technol. 67 (2018), 2713-2726. https://doi.org/10.1109/tvt.2017.2773270
  10. R. Mudumbai et al., Distributed transmit beamforming: Challenges and recent progress, IEEE Commun. Mag. 47 (2009), 102-110. https://doi.org/10.1109/MCOM.2009.4785387
  11. R. Mudumbai et al., Distributed transmit beamforming using feedback control, IEEE Trans. Inf. Theory 56 (2010), 411-426. https://doi.org/10.1109/TIT.2009.2034786
  12. S. Song et al., Improving the one-bit feedback algorithm for distributed beamforming, in Proc. IEEE Wireless Commun. Netw. Conf. (Sydney, Australia), Apr. 2010, doi: 10.1109/WCNC.2010.5506562.
  13. F. Quitin et al., Demonstrating distributed transmit beamforming with software-defined radios, in Proc. IEEE Int. Symp. World Wireless, Mobile Multimedia Netw. (San Francisco, CA, USA), June 2012, doi: 10.1109/WoWMoM.2012.6263729.
  14. M. M. Rahman et al., Fully wireless implementation of distributed beamforming on a software-defined radio platform, in ACM/IEEE Int. Conf. Inf. Process. Sensor Netw. (Beijing, China), Apr. 2012, 10.1109/IPSN.2012.6920945.
  15. E. Blossom, GNU radio: Tools for exploring the radio frequency spectrum, Linux Journal 122 (2004), 2004.
  16. Reserch, Ettus, USRP N200/N210 networked series, Moun-tain Viewi CA: Ettus Research, 2012.
  17. Datasheet, Product, P2110-915MHz RF powerharvester receiver, Powercast Corporation, Available at www.powercastco.com/PDF/P2110-datasheet.pdf.
  18. M. Chowdhury and A. Goldsmith, Capacity of block Rayleigh fading channels without CSI, in Proc. IEEE Int. Symp. Inf. Theory (Barcelona, Spain), July 2016, pp. 1884-1888.
  19. Y. Zhu and D. Guo, The degrees of freedom of isotropic MIMO interference channels without state information at the transmitters, IEEE Trans. Inf. Theory 58 (2012), 341-352. https://doi.org/10.1109/TIT.2011.2167314
  20. D. Tse and P. Viswanath, Fundamentals of wireless communication, Cambridge University Press, USA, 2005.
  21. Guided Tutorial GRC, https://wiki.gnuradio.org/index.php/Guided_Tutorial_PSK_Demodulation