Distributed spectrum sensing in rem based cognitive radio networks

Document Type : Power Article

Authors

1 university staff

2 electrical, electronic engineering department of Amirkabir university of technology

Abstract

Ever increasing development of wireless devices and wireless networks have increased the value of spectral space‎. ‎Many efforts have been conducted to increase spectral utilization‎. The radio environment mapping opens new gates for developing low cost wireless devices. ‎In this paper‎, ‎a new method is proposed for increasing spectral utilization in distributed networks‎. ‎In this method‎ ‎distributed Kalman filter, which is modified to increase estimation accuracy, is used to estimate position‎, ‎velocity and power of primary transmitters‎. ‎These data are used to select spectrum holes optimally and increase spectral utilization compared to centralized methods‎. Obtained r‎esults are evaluated through practical implementations and simulations‎. ‎Innovations of this research include introducing and employing a linear model for estimating position of a transmitter using received power in line of sight (LoS) and non-line of sight (NLS) conditions, ‎‎‎modifying extended kalman filter and‎ ‎implementation of distributed spectrum sensing; advantages of this method are illustrated compared to centralized methods.‎‎

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References

[1] M.T. Masonta, M. Mzyece, and N. Ntlatlapa, "Spectrum decision in cognitive radio networks: A survey", IEEE Communications Surveys and Tutorials, Vol. 15, No. 3, 2013, pp. 1088 – 1107.
[2] M. Pesko, T. Javornik, A. Kosir, M. Štular, and M. Mohorcic, "Radio environment maps: The survey of construction methods", KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, Vol. 8, No. 11, 2014, pp. 3789 – 3809.
[3] D. Denkovski, V. Atanasovski, L. Gavrilovska, J. Riihijärvi, and P. Mähönen, "Reliability of a radio environment map: Case of spatial interpolation techniques", in 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Stockholm, Sweden, 2012.
[4] S. Ulaganathan, D. Deschrijver, M. Pakparvar, I. Couckuyt, W. Liu, D. Plets, W. Joseph, T. Dhaene, L. Martens, I. Moerman, "Building accurate radio environment maps from multi-fidelity spectrum sensing data", Wireless Networks, Vol. 22, No. 8, 2016, pp. 2551 – 2562.
[5] J.A. Bazerque and G.B. Giannakis, "Distributed spectrum sensing for cognitive radio networks by exploiting sparsity", IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol. 58, No. 3, 2015, pp. 1847 – 1863.
[6] M. Pesko, T. Javornik, L. Vidmar, A. Košir, M. Štular & M. Mohorčič, "The indirect self-tuning method for constructing radio environment map using omnidirectional or directional transmitter antenna", Eurasip Journal on Wireless Communications and Networking, Vol. 2015, No. 1, 2015, pp. 1 – 12.
[7] Z.Y. Xiufang Shi, Guoqiang Mao and J. Chen, "Localization algorithm design and performance analysis in probabilistic los/nlos environment", in IEEE Wireless Communications Symposium (ICC 2016), Kuala Lumpur, Malaysia, 2016.
[8] H.M. Paul Zarchan, Fundamentals of Kalman Filtering: A Practical Approach, American Institute of Aeronautics and Astronautics Incorporated, 2000.
[9] L. Li, J.A. Chambers, C.G. Lopes and A.H. Sayed, "Distributed estimation over an adaptive incremental network based on the affine projection algorithm", IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol. 58, No. 1, 2010, pp. 151 – 164.
[10] F.S. Cattivelli and A.H. Sayed, "Diffusion lms strategies for distributed estimation", IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol. 58, No. 3, 2010, pp. 1035– 1048.
[11] L. Xiao, T. Chen, J. Liu, and H. Dai, "Anti-jamming transmission stackelberg game with observation errors", IEEE Communications Letters, Vol. 19, No. 6, 2015, pp. 949– 952.
[12] S.-Y. Tu and A.H. Sayed, "Diffusion strategies outperform consensus strategies for distributed estimation over adaptive networks", IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol. 60, No. 12, 2012, pp. 6217– 6234.
[13] S.-Y. Tu and A.H. Sayed, "Diffusion strategies outperform consensus strategies for distributed estimation over adaptive networks unknown primary signal arrival time", IEEE TRANSACTIONS ON COMMUNICATIONS, Vol. 59, No. 7, 2011, pp. 1779– 1785.[14] L. Lu, X. Zhou, U. Onunkwo and G.Y. Li, "Ten years of research in spectrum sensing and sharing in cognitive radio", Eurasip Journal on Wireless Communications and Networking, Vol. 2012, No. 28, 2012, pp. 1– 16.
[ 14 [ ه. مختاری، م. بهادری، ج. غلام نژاد، "برآورد ارزش اقتصادی بلوک استخراجی برای طراحی پیشرویها در معادن روباز، با در نظر گرفتن عدم قطعیت عیار، نمونۀ مطالعاتی: معدن سنگ آهن چادرملو"، مجله مدلسازی در مهندسی، دوره 14 ، شماره 47 ، 1395 ، صفحه 229-241 .
[ 15 [ ا. حسین بیگ، ج. سلیمان میگونی، "استفاده از حل معادلات انتگرالی در تحلیل یک آنتن پهن باند مایکرواستریپی"، مجله مدلسازی در مهندسی، دوره 14 ، شماره 46 ، 1395 ، صفحه 160 - 151 .
[ 16 [ ب. حسنی و ا. گنجعلی، "مکان یابی نقاط بهینه تنش در تحلیل ایزوژئومتریک"، مجله مدلسازی در مهندسی، دوره 13 ، شماره 40 ، 1394 ، صفحه 167 - 151 .
[17] Y.-Ch. Liang, K.-Ch. Chen, G.Y. Li, and P. Mahonen, "Cognitive radio networking and communications: An overview", IEEE Transactions on Vehicular Technology, Vol. 60, No. 7, 2011, pp. 3386– 3407.
[18] H. Sun, A. Nallanathan, Ch.-X. Wang and Y. Chen, "Wideband spectrum sensing for cognitive radio networks: A survey", IEEE Wireless Communications, Vol. 20, No. 2, 2013, pp. 74– 81.
[19] R. Bouraoui and H. Besbes, "Cooperative spectrum sensing for cognitive radio networks: Fusion rules performance analysis", in 2016 International Wireless Communications and Mobile Computing Conference (IWCMC), 2016.
[20] J.A. Bazerque and G.B. Giannakis, "Distributed spectrum sensing for cognitive radio networks by exploiting sparsity", IEEE Transactions on Signal Processing, Vol. 58, No. 3, 2010, pp. 1847– 1862.
[21] S. Gronroos, K. Nybom, J. Björkqvist, J. Hallio, J. Auranen, and R. Ekman, "Distributed spectrum sensing using low cost hardware", Journal of Signal Processing Systems, Vol. 83, No. 1, 2016, pp. 5– 17.
[22] H.B. Yilmaz and T. Tugcu, "Location estimation-based radio environment map construction in fading channels", WIRELESS COMMUNICATIONS AND MOBILE COMPUTING, Vol. 15, No. 3, 2015, pp. 561– 570.
[23] N. Ezzati, H. Taheri and T. Tugcu, "Optimised sensor network for transmitter localization and radio environment mapping", IET COMMUNICATIONS, Vol. 10, No. 16, 2016, pp. 2170– 2178.
Journal of Modeling in Engineering
Volume 17, Issue 56
April 2019
Pages 223-233

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History

  • Receive Date: 22 December 2017
  • Revise Date: 30 March 2018
  • Accept Date: 12 May 2018

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