DUTY CYCLE ANALYSIS OF RADIO SPECTRUM PROFILE UTILIZATION FOR CELLULAR BANDS

Isa, A. A., Akanni, J., Thomas, C. T., Alao, R. A., Adeshola, A. S

Abstract

The high increase in the growth of wireless devices with the present static radio spectrum management has created an inadequacy in the available radio spectrum and presently the spectrum regulatory bodies are of the view that static spectrum management approach giving right of way to use licensed is still efficient. In this paper spectrum occupancy of GSM 900 MHz, GSM 1800 MHz and 3G are investigated. The measurement is done with Advantest U3741 spectrum analyzer with the frequency range of 9 kHz to 3 GHz using energy detection method and selecting a 10 dBm noise floor value as proposed by the International Telecommunication Union (ITU). The study reveals a duty cycle of 35.31%, 9.59% and 28.08 for GSM 900 MHz, 1800 MHz and 3G respectively. The results show that the spectrum is highly underutilized. Read full PDF

Keywords: Spectrum occupancy, Duty cycle, Cognitive Radio (CR), 3G

References

[1] J. Akanni, A. A. Isa, R. A. Alao and C. T. Thomas (2020) “Assessment of Internet Service Provided Using UMTS Operators at the University of Ilorin Main Campus,” Nigerian Journal of Technology, vol. 39, no. 2, pp. 500 – 505

[2] A. Ranjan and B. Singh (2016) “Design and Analysis of Spectrum Sesning in Cognitive Based on Energy Detection,” In Proceding of the International Conference on Signal and Information Precessing, Vishnupuri, India, pp. 1 – 5.

[3] J. J. Popoola, O. A. Ogunlana, F. O. Ajie, O. Olakunle, O. A. Akiogbe, S. M. Ani-Initi, and S. K. Omotola (2016) “Dynamic Spectrum Access: A New Paradigm of Converting Radio Spectrum Wastage to Wealth,” International Journal of Engineering Technologies, vol. 2, No.3, pp. 124 – 131

[4] Cisco (2015) “Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update. (2014–2019)”. [Online] Available: http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-indexvni/white_paper_c11-520862.html

[5] Y. Arjoune and N. Kaabouch (2019) “A Comprehensive Survey on Spectrum Sensing in Cognitive Radio Networks: Recent Advances, New Challenges, and Future Research Directions,” Sensor, vol. 19, no. 1, pp. 126

[6] T. Nechiporenko, P. Kalansuriya, C. Tellambura (2008). “Performance of Optimum Switching Adaptive M-QAM for Amplify-and-Forward Relays,” IEEE Transactions on Vehicular Technology, vol. 58, no. 5, pp. 2258-2268

[7] G. Amarasuriya, M. Ardakani, C. Tellambura (2010). “Output-Threshold Multiple-Relay-Selection Scheme for Cooperative Wireless Networks,” IEEE Transactions on Vehicular Technology, vol. 59, no. 6, pp. 3091 – 3097

[8] Qualcomn (2011) The visible light communications motivation. [Online] Available: http://visiblelightcomm.com/thevisible-light-communications-motivation/

[9] M. M. Buddhikot, K. Ryan, (2005) “Spectrum Management in Coordinated Dynamic Spectrum Access Based Cellular Networks”, Proceeding of First IEEE International Conference on Dynamic Spectrum Access Networks, Baltimore, USA, November 8-11, pp. 299-307.

[10] G. Ding, Q. Wu, Y. Zou, J. Wang, Z. Gao, (2014) “Joint Spectrum Sensing and Transmit Power Adaptation in InterferenceAware Cognitive Radio Networks”, Transaction on Emerging Telecommunications Technology, vol. 25, no. 2, pp. 231- 238.

[11] J. Wang, G. Diang, Q. Shen, F. Song, (2014) “Spatial-Temporal Spectrum Hole Discovery: A Hybrid Spectrum Sensing and Geolocation Database Framework”, Chinese Science Bulletin, vol. 59, no. 16, pp. 1896-1902.

[12] R. Shukla, D. Sharma, (2013) “Estimation of Spectrum Holes in Cognitive Radio using PSD”, International Journal of Information and Computer Technology, vol. 3, no. 7, pp. 663-670

[13] A.S. Kadhim, H.M. AI-Sabbagh, (2012) “Detecting the Spectrum Holes in The Primary Bandwidth of the Cognitive Radio Systems in Presence Noise and Attenuation”, International Journal of Communication Networks and System Science., vol. 5, no. 10, pp. 685-690.

[14] S. Haykin, D.J. Ehomson, J.H. Reed, (2009) “Spectrum Sensing for Cognitive Radio”, Proceeding of the IEEE, vol. 97, no. 5, pp. 849-977

[15] G. Zhao, J. Ma, G.Y. Li. T. Wu, Y. Kwon, A. Song, C. Yang, (2009) “Spatial Spectrum Holes for Cognitive Radio with Relay-Assisted Directional Transmission”, IEEE Transaction on Wireless Communication., vol. 8, no. 10, pp. 5270-5279.

[16] I.F. Akyildiz, W.Y. Lee, M. C. Vuran, S. Mohanty, (2006) “Next Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A survey”, Computer Networks, vol. 50, no. 13, pp. 2127-2159.

[17] S. Haykin, (2005) “Cognitive Radio: Brain-empowering Wireless Communications”, IEEE Journal on Selected Areas in Communication., vol. 23, no. 2, pp. 201-220.

[18] P. Rawat, K. D. Singh & J. M. Bonnin, (2016) “Cognitive Radio for M2M and Internet of Things: A Survey “Computer Communication”, vol. 94, pp. 1 – 29

[19] I.F. Akyildiz, W.Y. Lee, M.C. Vuran, S. Mohanty, (2008) “A Survey on Spectrum Management in Cognitive Radio Networks,” IEEE Communication Magazine, vol. 46 no. 4, pp. 40 – 48.

[20] C. Tellambura, and S. Kusaladharma (2017) “An Overview of Cognitive Radio Networks” A.A. Isa et al./ NIPES Journal of Science and Technology Research 2(2) 2020 pp. 158 – 165 165

[21] R. Menon, R. Buehrer and J. Reed (2005) “Outage Probability Based Comparison of Underlay and Overlay Spectrum Sharing Techniques,” In Proceeding First IEEE International Symposium on New Frontiers in Dynamic Access Network, DYSPAN; pp 101- 109

[22] S. Srinivasa and S. A. Jafar (2007) “Cognitive Radios for Dynamic Spectrum Access – The Throughput Potential of Cognitive Radio: A Theoretical Perspective,” In IEEE Communications Magazine, vol. 45, no. 5, pp. 73-79

[23] E. Hossain, D. Niyato and Z. Han (2009) “Dynamic Spectrum Access and Management in Cognitive Radio Networks,” Cambridge University Press

[24] B. Wang and K. Liu (2011) “Advances in Cognitive Radio Networks: A survey,” IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 1, pp. 5–23

[25] S. K. Sharma, T. E. Bogale, S. Chatzinotas, B. Ottersten, L. B. Le and X. Wang (2015) “Cognitive Radio Techniques under Practical Imperfection: A survey,” IEEE Communications Surveys and tutorials; vol. 17, no 4, pp. 1858 – 1884

[26] F. H. Sanders (1998) “Broadband Spectrum Surveys in Denver, CO, San Diego, CA, and Los Angeles, CA: Methodology, Analysis, and Comparative Results,” In Proceeding of IEEE International Symposium on Electromagnetic Compatibility, vol. 2, pp. 988–993.

[27] M. A. McHenry, P. A. Tenhula, D. McCloskey, D. A. Roberson, and C. S. Hood (2006) “Chicago Spectrum Occupancy Measurements & Analysis and a Long-term Studies Proposal,” In Proceeding of Workshop on Technology and Policy for Accessing Spectrum (TAPAS), Boston, USA

[28] R. I. C. Chiang, G. B. Rowe, and K. W. Sowerby (2007) “A Quantitative Analysis of Spectral Occupancy Measurements for Cognitive Radio,” In Proceeding of IEEE Vehicular Technology Conference (VTC), Dublin, Ireland, pp. 3016- 3020.

[29] M. Wellens, J. Wu, and P. Mähönen (2007) “Evaluation of Spectrum Occupancy in Indoor and Outdoor Scenario in the Context of Cognitive Radio,” In Proceeding of International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Orlando, FL, USA, pp. 420–427. [

30] M. Islam, G. L. Tan, F. Chin, B. E. Toh, Y. C. Liang, C. Wang, Y. Y. Lai, X. Qing, S. W. Oh, C. L. Koh, and W. Toh (2008) “Spectrum Survey in Singapore: Occupancy Measurements and Analyses”, In Proceeding of International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), Singapore, pp. 1-7.

[31] Y. Sixing, C. Dawei, Z. Qian, L. Mingyan, and L. Shufang (2012) “Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study,” IEEE Transactions on Mobile Computing, vol. 11, no. 6, pp. 1033-1046.

[32] M. Lopez-Benitez, A. Umbert, and F. Casadevall (2009) “Evaluation of Spectrum Occupancy in Spain for Cognitive Radio Applications,” In Proceeding of Vehicular Technology Conference, VTC Spring

[33] K. A. Qaraqe, H. Celebi, A. Gorcin, A. El-Saigh, H. Arslan and M. S. Alouini (2009) “Empirical Results for Wideband Multidimensional Spectrum Usage,” In Proceeding of IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, Tokyo, Japan, pp. 1262-1266.

[34] V. Valenta, R. Marsálek, G. Baudoin, M. Villegas, M. Suarez, and F. Robert (2010) “Survey on Spectrum Utilization in Europe: Measurements, Analyses and Observations,” In Proceeding of the Fifth International Conference on Cognitive Radio Oriented Wireless Networks & Communications (CROWNCOM), pp. 1-5.

[35] Q. B. Vo. Nguyen, Q. C. Le, Q. P. Le, D. T. Tran, T. Q. Nguyen, and M. T. Lam (2011) “Vietnam Spectrum Occupancy Measurements and Analysis for Cognitive Radio Applications,” In Proceeding of International Conference on Advanced Technologies for Communications (ATC), pp. 135-143.

[36] K. Patil, K. Skouby, A. Chandra, and R. Prasad, (2011) “Spectrum Occupancy Statistics in the Context of Cognitive Radio,” In Proceeding of 14th International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 1-5.

[37] R. de Francisco (2010) “Spectrum Occupancy in the 2.36–2.4 GHZ band: Measurements and Analysis,” In Proceeding of European Wireless Conference (EW), pp. 231–237

[38] J.J. Popoola, R. Van Olst, (2011) “Application of Neural Network for Sensing Primary Radio Signals in a Cognitive Radio Environment”, In Proceeding of IEEE AFRICON, Livingstone, Zambia, September 13 – 15, pp. 1-6

[39] S. D. Barnes, P. A. J. van Vuuren, B.T. Maharaj (2013) “Spectrum Occupancy Investigation: Measurements in South Africa”, Measurement, vol. 46, no. 9, pp. 3098-3112.

[40] G. Ayugi, A. Kisolo, T.W. Ireeta, (2015) “Telecommunication Frequency Band Spectrum Occupancy in Kampala Uganda”, International Journal Research in Engineering and Technology, vol. 4, no. 9, pp. 390-396.

[41] S. Jayavalan, H. Mohamad, N. Moh’d Aripin, A. Ismail, N. Ramli, A. Yaacob, and M. A. Ng (2014) “Measurements and Analysis of Spectrum Occupancy in the Cellular and TV bands,” Lecture Notes on Software Engineering, vol. 2, no. 2 pp. 133 – 138

[42] Y. Liang , Y. Si-xing, W. Shuai, Z. Er-qing, H. Wei-jun, L. Shu-fang. (2012) “Quantitative Spectrum Occupancy Evaluation in China: Based on a Large Scale Concurrent Spectrum Measurement”, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China, The Journal of China Universities of Posts and Telecommunications, vol. 19 issue 3, pp. 122-128

[43] A. A. Ayeni, N. Faruk, O. W. Bello, O. A. Sowande, S. O. Onidare, and M. Y. Muhammad (2016) “Spectrum Occupancy Measurements and Analysis in the 2.4-2.7 GHz Band in Urban and Rural Environments” International Journal of Future Computer and Communication, vol. 5, no. 3, pp. 142 – 147

[44] B.G. Najashi, W. Feng, C. Kadri, (2013) “An Insight into Spectrum Occupancy in Nigeria”, International Journal of Computer Science Issues, vol. 10, no. 1, pp. 394-399

[45] B.G. Najashi, M.D. Almustapha, A.S. Abdi, S.A. Ashurah, (2015) “Spectrum Occupancy Measurements in Nigeria: Results and Analysis,” International Journal of Computer Science Issues, vol. 12, no. 4, pp. 156-165

[46] Radio communication Bureau, International Telecommunication Union (ITU), (2011) Handbook Spectrum Monitoring