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A Step Towards Enhancing Spectrum Utilization by Implementing a Spectrum Sensing Cognitive Radio Using an RTL-SDR


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DOI: https://doi.org/10.15866/irecap.v8i5.13954

Abstract


In this paper, a spectrum sensing cognitive radio using the RTL-SDR interfaced with Simulink in MATLAB was developed. It performed spectrum sensing and signal prediction between the ranges of 25MHz to 1.5GHz, the tuner range of the RTL-SDR. The RF spectrum occupancy was explored by choosing specific centre frequencies between 25MHz to 1.5GHz in real time using the RTL-SDR. Tests were carried out in real time to ascertain the workability and efficiency of the RTL-SDR cognitive radio. The efficiency of the cognitive radio reduced as the false alarm probability increased. The cognitive radio’s efficiency also reduced in high noise signal floors.
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Keywords


Software Defined Radio; Spectrum Sensing; Cognitive Radio; Primary User; Secondary User; False Alarm Probability (Pfa); Probability of Detection (Pd); Probability of Miss Detection (Pmd)

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References


National Frequency Allocation Table.

M. Mohammed, Estimation of Detection Threshold For Spectrum Sensing In Cognitive Radio Using Adaptive Neuro Fuzzy Inference System and Monte Carlo Techniques, Ph.D-2015, Ahamdu Bello University.

V. H. Patil, P. Doshi, S. Dhomeja, and S. Thakur, Spectrum Sensing in Cognitive Radio, International Research Journal of Engineering and Technology (IRJET), Vol. 04 No. 06, June 2017
http://dx.doi.org/10.15623/ijret.2015.0406083

A. I. F, W.-Y. L, M. C. V, and S. M, Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey, Computer Networks, pp. 2127-2159, 2006.
http://dx.doi.org/10.1016/j.comnet.2006.05.001

H. Simon, Invited Paper. Cognitive Radio Brain Empowered Wireless Communications. IEEE Journals on Selected Areas in Communications, pp. 201-220, 2005.
http://dx.doi.org/10.1109/jsac.2004.839380

A. Saman, T. C, and J. H, Energy Detection for Spectrum Sensing in Cognitive Radio, Springer, New York, pp. 11-26, 2014.
http://dx.doi.org/10.1007/978-1-4939-0494-5_2

N. Basumatary, N. Sarma, and B. Nath, Applying Classification Methods for Spectrum Sensing in Cognitive Radio Networks: An Empirical Study, in Advances in Electronics, Communication and Computing, ed: Springer, 2018, pp. 85-92.
http://dx.doi.org/10.1007/978-981-10-4765-7_10

P. Vijayakumar, J. George, S. Malarvizhi, and A. Sriram, Analysis and Implementation of Reliable Spectrum Sensing in OFDM Based Cognitive Radio, in Smart Computing and Informatics, ed: Springer, 2018, pp. 565-572.
http://dx.doi.org/10.1007/978-981-10-5544-7_55

J. Wang, R. Chen, J. J. Tsai, and D.-C. Wang, Trust-based mechanism design for cooperative spectrum sensing in cognitive radio networks, Computer Communications, vol. 116, pp. 90-100, 2018.
http://dx.doi.org/10.1016/j.comcom.2017.11.010

R. Paul, P. Nath, and S. Bera, Design of Spectrum Sensing System, in Advances in Systems, Control and Automation, ed: Springer, 2018, pp. 537-544.
http://dx.doi.org/10.1007/978-981-10-4762-6_51

S. S. Company, General Survey of Radio Frequency Bands 30 MHz to 3 GHz, 2010.

R. S. Kale, V. M. Wadhai, and J. B. Helonde, Novel Threshold Formulation for Energy Detection Method to Efficient Spectrum Sensing in Cognitive Radio, in Sensors and Image Processing, ed: Springer, 2018, pp. 25-35.
http://dx.doi.org/10.1007/978-981-10-6614-6_3

K. Bani and V. Kulkarni, Simulink-Based Estimation of Spectrum Sensing in Cognitive Radio, in Innovations in Electronics and Communication Engineering, ed: Springer, 2018, pp. 387-398.
http://dx.doi.org/10.1007/978-981-10-3812-9_41

A. J and T. K, Simulink Based Spectrum Sensing, International Journal of Engineering and Technology vol. 5, pp. 872-877, 2013.

T. S. Syed and G. A. Safdar, Spectrum Sensing Mechanisms in Cognitive Radio Based LTE Femtocells, LTE Communications and Networks: Femtocells and Antenna Design Challenges, pp. 150-183, 2018.
http://dx.doi.org/10.1002/9781119385271.ch6

Orumwense, E., Oyerinde, O., Mneney, S., Impact of Primary User Emulation Attacks on Cognitive Radio Networks, (2014) International Journal on Communications Antenna and Propagation (IRECAP), 4 (1), pp. 19-26.

Alnabelsi, S., Finding an Immuned Path Against Single Primary User Activity in Cognitive Radio Networks, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (7), pp. 562-571.
http://dx.doi.org/10.15866/irecap.v7i7.12830

Esenogho, E., Srivastava, V., Channel Assembling Strategy in Cognitive Radio Networks: a Queuing Based Approach, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (1), pp. 31-47.
http://dx.doi.org/10.15866/irecap.v7i1.9840
E. Astaiza, P. Jojoa, and H. Bermúdez, Compressive local wideband spectrum sensing algorithm for multiantenna cognitive radios, 2016 8th IEEE Latin-American Conference on Communications (LATINCOM), 2016, pp. 1-6.
http://dx.doi.org/10.1109/latincom.2016.7811577

Anusha, M., Srikanth, V., An Efficient Mac Protocol for Reducing Channel Interference and Access Delay in Cognitive Radio Wireless Mesh Networks, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (1), pp. 14-18.
http://dx.doi.org/10.15866/irecap.v6i1.7891

S. S. Hashmi, S. A. Sattar, and K. Soundararajan, Optimal Spectrum Utilization and Flow Controlling In Heterogeneous Network with Reconfigurable Devices, International Journal of Electronics and Telecommunications, vol. 63, pp. 269-277, 2017.
http://dx.doi.org/10.1515/eletel-2017-0036

S. A. Hoven and T. R, Some Fundamental Limits in Cognitive radio, Proceedings of the Allerton Conference on Communication, Control and Computing, 2004.

H. K. Jhajj, R. Garg, and N. Saluja, Implementation of Particle Swarm Optimization Technique for Spectrum Sensing in Cognitive Radio Networks, Advances in Wireless and Mobile Communications, Vol. 10, No. 4, 2017, pp. 661-669

N. Nkordeh, F. Idachaba, I. Bob-Manuel, and O. Oni, Received Signal Strength Measurement: Suboptimal Handing-over, in Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering, 2016.

C. Danijela, T. A, and B. R. W, Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection, Berkeley: Berkeley Wireless Research Center, University of California, 2003.

O. Obinna, O. Kennedy, O. Osemwegie, and N. Nsikan, Comparative Analysis of Channel Estimation Techniques in SISO, MISO and MIMO Systems, International Journal of Electronics and Telecommunications, vol. 63, pp. 299-304, 2017.
http://dx.doi.org/10.1515/eletel-2017-0040

A. Kumar, R. Goyal, and D. Ray, Spectrum sensing using energy detection algorithm for cognitive radio, International Research Journal of Engineering and Technology (IRJET), Vol. 4, No, 5, 2017.

Building Cognitive Radios in MATLAB Simulink – A Step Towards Future Wireless Technology, Wireless Advanced, pp. 15-20, 2011.
http://dx.doi.org/10.1109/wiad.2011.5983278

W. Beibei and L. K. J, Advances in Cognitive Radio Networks: A Survey, IEEE Journal of Selected Topics in Signal Processing, vol. 5, pp. 5-23.
http://dx.doi.org/10.1109/jstsp.2010.2093210

Okokpujie, K., Chukwu, E., Noma-Osaghae, E., Okokpujie, I., Novel Active Queue Management Scheme for Routers in Wireless Networks, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (1), pp. 52-61.
http://dx.doi.org/10.15866/irecap.v8i1.13408

Idowu-Bismark, O., Kennedy, O., Idachaba, F., Atayero, A., A Primer on MIMO Detection Algorithms for 5G Communication Network, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (3), pp. 194-205.
http://dx.doi.org/10.15866/irecap.v8i3.13731


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