Implementation of Selected Spectrum Sensing Systems for Cognitive Radio Networks using FPGA Platform

• Autorzy: Abdullah H. N. , Abed H. S.

Identyfikatory

DOI

10.26636/jtit.2018.125018

• Języki publikacji: EN

Abstrakty

EN

The energy efficient spectrum sensing method is very important in cognitive radio (CR), since high power drain may limit its implementation in mobile applications. The spectrum sensing feature consumes more energy than other functional blocks, as it depends on continuous detection of the presence or absence of the primary user (PU). In this paper, we proposed two methods to reduce energy consumption of the spectrum sensing feature. The first is of a single stage variety with a reduced number of sensed samples. The other uses two stages. The first stage performs coarse sensing for many subchannels, and the best subchannel is forwarded for fine sensing in the second stage. The performance of the proposed methods is evaluated in AWGN channel and compared with the existing approach. The proposed methods are simulated using Matlab and ModelSim and are then hardware implemented using the Altera Cyclone II FPGA board. Simulation results show that the proposed methods offer an improvement in energy consumption with an acceptable reduction in the probability of detection. At Eb/N0 Eb/N0 Eb/N0 of 0 dB, the energy consumption is reduced by 50% and 72% in the first and second proposed method, respectively, compared to the traditional method (100% sensing).

Słowa kluczowe

EN

cognitive radio; energy consumption; energy detection; FPGA

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2018
• Tom: nr 4
• Strony: 81--87
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Abdullah H. N.

• College of Information Engineering, Al Nahrain University, Baghdad, Iraq

autor

Abed H. S.

• College of Information Engineering, Al Nahrain University, Baghdad, Iraq

Bibliografia

• [1] Y. H. Chye, E. Dutkiewicz, and R. Vesilo, “Adaptive Spectrum Sensing for Cognitive Radio Systems in a Fading Environment”, in Proc. 17th Int. Symp. on Wirel. Pers. Multim. Commun. WPMC 2015, Sydney, Australia, 2015, pp. 451–456 (doi: 10.1109/WPMC.2014.7014861).
• [2] M. Matinmikko et al., “Cognitive radio: An intelligent wireless communication system”, Research Rep. No. VTT-R-02219-08, Technical Research Center of Finland (VTT), 2008 [Online]. Available: https://www.vtt.fi/inf/julkaisut/muut/2008/ CHESS Research Report.pdf
• [3] S. Althunibat and F. Granelli, “On results’ reporting of cooperative spectrum sensing in cognitive radio networks”, J. of. Telecommun. Syst., vol. 62, no. 3, pp. 569–580, 2015 (doi: 10.007/s11235-015-0095-5).
• [4] S. J. Kim, G. Li, and G. B. Giannakis, “Minimum-delay spectrum sensing for multi-band cognitive radios”, in Proc. IEEE Global Telecommun. Conf. GLOBECOM 2010, Miami, FL, USA, 2010 (doi: 10.1109/GLOCOM.2010.5683914).
• [5] S. J. Kim and G. B. Giannakis, “Sequential and cooperative sensing for multi-channel cognitive radios”, IEEE Trans. on Sig. Process., vol. 58, no. 8, pp. 4239–4253, 2010 (doi: 10.1109/TSP.2010.2049106).
• [6] S. J. Kim and G. B. Giannakis, “Rate-optimal and reducedcomplexity sequential sensing algorithms for cognitive OFDM radios”, EURASIP J. on Adv. in Sig. Process., vol. 2009, no. 2, Article ID 421540, 2009 (doi: 10.1155/2009/421540).
• [7] Q. Zou, S. Zheng, and A. H. Sayed, “Cooperative sensing via sequential detection”, IEEE Trans. on Sig. Process., vol. 58, no. 12, pp. 6266–6283, 2010 (doi: 10.1109/TSP.2010.2070501).
• [8] S. Maleki and G. Leus, “Censored truncated sequential spectrum sensing for cognitive radio networks”, IEEE J. on Selec. Areas in Commun., vol. 31, no. 3, pp. 364–378, 2013 (doi: 10.1109/JSAC.2013.130304).
• [9] S. Srinu and S. L. Sabat, “FPGA implementation of spectrum sensing based on energy detection for cognitive radio”, in Proc. IEEE Int. Conf. on Commun. Control and Comput. Technol. ICCCCT 2010, Ramanathapuram, India, 2010 (doi: 10.1109/ICCCCT.2010.5670540).
• [10] H. N. Abdullah and H. S. Abed, “Improvement of energy consumption in cognitive radio networks using an efficient coarse-fine sensing method”, in Proc. Int. Conf. on Change, Innov., Inform. and Disruptive Technol. ICCIIDT’16, London, United Kingdom, 2016, pp. 218–230.
• [11] M. Emara et al., “Spectrum sensing optimization and performance enhancement of cognitive radio networks”, Wirel. Pers Commun., vol. 86, no. 2, pp. 925–941, 2015 (doi: 10.1007/s11277-015-2962-5).
• [12] H. N. Abdullah and H. S. Abed, “Improvement of energy consumption in cognitive radio by reducing the number of sensed samples”, in Proc. of IEEE Al-Sadiq Int. Conf. on Multidisc. in IT and Commun. Sci. and Technol. AIC-MITC 2016, Baghdad, Iraq, 2016, pp. 301–306 (doi: 10.1109/AIC-MITCSA.2016.7759954).
• [13] H. N. Abdullah and H. S. Abed,“Energy consumption control in cooperative and non-cooperative cognitive radio using variable spectrum sensing sampling”, J. of Telecommun., Electron. and Comp. Engin. (JTEC), vol. 8, no. 9, pp. 7–12, 2016.
• [14] S. Maleki, A. Pandharipande, and G. Leus, “Energy-efficient distributed spectrum sensing for cognitive sensor networks”, IEEE Sensor J., vol. 11, no. 3, pp. 565–573, 2011 (doi: 10.1109/JSEN.2010.2051327).
• [15] H. N. Abdullah and H. S. Abed, “Improvement of energy consumption in spectrum sensing cognitive radio networks using an efficient two stage sensing method”, Acta Polytechnica, vol. 47, no. 4, pp. 235–244, 2017 (doi: 10.14311/AP.2017.57.0235).
• [16] S. Atapattu, “Analysis of energy detection in cognitive radio networks”, Ph.D. Thesis, Department of Electrical and Computer Engineering, University of Alberta, 2013 (doi: 10.7939/R33X37).

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).