Cognitive Radio Simulator for Mobile Networks: Design and Implementation

Pablo Palacios*, Alberto Castro **
*-** Department of Electrical Engineering, Universidad de Chile, Santiago, Chile.
Periodicity:February - April'2018


In this work methods and mathematical algorithms applied to the Cognitive Radio (CR) technology are tested through the  development  of a  CR  simulator applied  to WiFi  and  Long Term  Evolution  (LTE) mobile wireless networks,  structured with each of the four stages of a system CR, using mathematical tools evaluated  in  previous  works  individually.   The implementation of the CR simulator jointly adapts to different algorithms, which are: Singular Value Decomposition (SVD), Coalition Game Theory and Handoff of technologies by Received Signal Strength Indicator (RSSI). The Network Simulator 3 software (NS-3) is used as an environment for the development and execution of a heterogeneous cognitive network based on the created simulator. Results  are obtained,  numerical  data  shown  in  files  for  the SVD methods,  coalition  game and RSSI, these allow to evaluate their  performance comparing them with other theoretical CR algorithms. Validations and comparisons of the detection stage are shown for functional verification of the simulator.


Cognitive Radio, Mobile Networks, CR Simulator, Singular Value Decomposition (SVD), Game Theory, RSSI, NS-3.

How to Cite this Article?

Palacios, P., and Castro, A. (2018). Cognitive Radio Simulator for Mobile Networks: Design and Implementation. i-manager’s Journal on Communication Engineering and Systems, 7(2), 1-9.


[1]. Cabric, D. B. (2007). Cognitive radios: System design perspective (Doctoral Dissertation University of California, Berkeley).
[2]. Crow, B. P., Widjaja, I., Kim, J. G., & Sakai, P. T. (1997). IEEE 802.11 wireless local area networks. IEEE Communications Magazine, 35(9), 116-126.
[3]. Fahim, M. F., & Raeen, M. S. (2012). SVD detection for cognitive radio network based on average of maximumminimum of the ICDF. International Journal of Advanced Computer Research, 2(3), 182-187.
[4]. Held, L., & Sabanés Bové, D. (2014). Applied Statistical Inference. Springer, Berlin Heidelberg.
[5]. Kalil, I. M. (2011). Cognitive radio The IEEE 802.22 standard. Integrated Communication Systems, 15.
rd [6]. Laine, L. (2011). Performance Management of 3 Generation Partnership Project Long Term Evolution (Master's Thesis, Aalto University).
[7]. Mitola, J. (2009). Cognitive radio architecture evolution. Proceedings of the IEEE, 97(4), 626-641.
[8]. Nahas, M., Mjalled, M., Zohbi, Z., Merhi, Z., & Ghantous, M. (2013). Enhancing lte-wifi interoperability using context aware criteria for handover decision. In t h Microelectronics (ICM), 2013 25 International Conference on (pp. 1-4). IEEE.
[9]. Ni, Q., Zhu, R., Wu, Z., Sun, Y., Zhou, L., & Zhou, B. (2013). Spectrum Allocation Based on Game Theory in Cognitive Radio Networks. JNW, 8(3), 712-722.
[10]. Omar, M. H., Hassan, S., & Nor, S. A. (2011). Eigenvalue-based signal detectors performance th comparison. In Communications (APCC), 2011 17 Asia- Pacific Conference on (pp. 1-6). IEEE.
[11]. Palacios, P., Castro, A., Azurdia-Meza, C., & Estevez, C. (2017). SVD detection analysis in cognitive mobile radio networks. In Ubiquitous and Future Networks (ICUFN), 2017 Ninth International Conference on (pp. 222-224). IEEE.
[12]. R Development Core Team. (2011). R: A Language and Environment for Statistical Computing. Vienna, Austria: the R Foundation for Statistical Computing.
[13]. Ramírez, I. C., Barrera, C. J., & Correa, J. C. (2013). Efecto del tamaño de muestra y el número de réplicas bootstrap. Ingeniería y Competitividad, 15(1), 93-101.
[14]. Rentería, J. H. A., & Cadavid, A. N. (2011). Radio cognitiva–Estado del arte. Sistemas & Telemática, 9(16), 31-53.
[15]. Saad, W., Han, Z., Debbah, M., Hjorungnes, A., & Basar, T. (2009). Coalitional games for distributed collaborative spectrum sensing in cognitive radio networks. In INFOCOM 2009, IEEE (pp. 2114-2122). IEEE.
[16]. Spillner, A., Linz, T., & Schaefer, H. (2014). Software testing foundations: A study guide for the certified tester exam. Rocky Nook, Inc.
[17]. Urquía Moraleda, A., & Abarca Junco, A. P. (2013). Modelado y simulación de eventos discretos. Alfonso Urquía Moraleda / Carla Martín Villalba.
[18].Wang, T., Song, L., Han, Z., & Saad, W. (2013). Overlapping coalitional games for collaborative sensing in cognitive radio networks. In Wireless Communications and Networking Conference (WCNC), 2013 IEEE (pp. 4118- 4123). IEEE.
[19]. Yawada, P. S., & Wei, A. J. (2016). Cyclostationary Detection based on Non-cooperative spectrum sensing in cognitive radio network. In Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2016 IEEE International Conference on (pp. 184-187). IEEE.
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