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ASSESSMENT OF RADIO SPECTRUM PROFILE IN NIGERIA USING MULTI-BAND AND MULTI-LOCATION RADIO SPECTRUM OCCUPANCY MEASUREMENTS

Year 2018, Volume: 19 Issue: 4, 948 - 962, 31.12.2018
https://doi.org/10.18038/aubtda.425027

Abstract

This paper presents multi-band and multi-location spectrum measurements campaign conducted in Nigeria in 80-2200 MHz frequency range. The objectives of the study are to quantitatively determine the actual radio spectrum usage profile situation in Nigeria and to determine the radio spectrum usage profile in Nigeria in time, frequency and space. The results from the spectrum measurements campaign shows that a lot of allocated frequency bands in Nigeria have very low signal occupancy rates with the occupancy rates vary randomly in time, frequency and space like other parts of the world. The spectrum measurements campaign results also show that the actual spectral occupancy in Nigeria is less than 10.00%. The low spectral occupancy rate in the five major metropolises suggests a hopeful future for dynamic spectrum access in Nigeria.

References

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  • [2] López-Benítez M, Casadevall F. spectrum usage in cognitive radio networks: from field measurement to empirical models. IEICE Transactions on Communications 2014; E97-B: 242-250.
  • [3] Mehdawi M, Riley N, Paulson K, Fanan A, Ammar M. spectrum occupancy survey in hull-uk for cognitive radio applications: Measurement and analysis. International Journal of Scientific & Technology Research 2013; 2: 231-236.
  • [4] Xue J, Feng Z, Zhang P. spectrum occupancy measurements and analysis in Beijing. IERI Procedia 2013; 4: 295-302.
  • [5] Yin S, Chen D, Zhang Q, Liu M Li S. Mining spectrum usage data: A large-scale spectrum measurement study. IEEE Transactions on Mobile Computing 2012; 11: 1033-1046.
  • [6] Chiang RIC, Rowe GB, Sowerby KW. A quantitative analysis of spectral occupancy measurements for cognitive radio. In: IEEE 2007 Vehicular Technology Conference; 22-25 April 2007; Dublin, Ireland: pp. 3016-3020.
  • [7] Popoola, JJ, van Olst R. Development and demonstration of graphical user interface spectrum sensing algorithm using some wireless systems in South Africa. Journal of Applied Science and Process Engineering 2015; 2: 44-63.
  • [8] Scutari G, Palomar, DP, Barbarossa S. Cognitive MIMO radio competitive optimality design based on subspace projections. IEEE Signal Processing Magazine 2008; 25: 46–59.
  • [9] Najashi BG, Almustaphar MD, Abdi AS, Ashurah SA. Spectrum occupancy measurement in Nigeria: Results and analysis. International Journal of Computer Science Issues 2015; 12: 156-165.
  • [10] Popoola JJ, Ogunlana OA, Ajie FO, Olakunle O, Akiogbe OA, Ani-Initi SM, Omtola SK. Dynamic spectrum access: A new paradigm of converting radio spectrum wastage to wealth. International Journal of Engineering Technologies 2016; 2: 124-131.
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  • [12] Bedogni L, Felice MD, Malabocchia F, Bononi L. Indoor communication over TV gray spaces based on spectrum measurements. In: 2014 IEEE Wireless Communication and Networking Conference; 6-9 April 2014; Istanbul, Turkey: pp. 3218-3223.
  • [13] Höyhtyä M, Matinmikko M, Chen X, Hallio J, Auranen J, Ekman R., Röning J, Engelberg J, Kalliovaara J, Taher T, Riaz A, Roberson D. Measurements and analysis of spectrum occupancy in the 2.3-2.4 GHz band in Finland and Chicago; In: 2014 International Conference on Cognitive Radio Oriented Wireless Networks, 2-4 June 2014; Finland: pp. 96-101.
  • [14] Popoola JJ, van Olst R. Application of neural network for sensing primary radio signals in a cognitive radio environment. In: 2011 IEEE AFRICON, 13-15 September 2011; Livingstone, Zambia. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&amumber=6072009.
  • [15] McHenry MA, Tenhula PA, McCloskey D, Roberson DA, Hood S. Chicago spectrum occupancy measurements and analysis and a long-term studies proposal. In: 2006 International Workshop on Technology and Policy for Accessing Spectrum, 5 August 2006, Boston, USA. Online [Available]: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.518.5560&rep=rep1&type=pdf. Accessed on July 16, 2017.
  • [16] Valenta V, Marsalek R, Baudoin G, Villegas M, Suarez M, Robert F. Survey on spectrum utilization in Europe: Measurements, analyses and observations; In: 2010 International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, June 2010; Cannes, France: pp. 1-5. Online [Available]: https://hal.archives-ouvertes.fr/hal-00492021/document. Accessed on December 11, 2016.
  • [17] López-Benítez M, Umbert MA, Casadevall F. Evaluation of spectrum occupancy in Spain for cognitive radio applications. In: 2009 IEEE Vehicular Technology Conference; 26-29 April 2009; Barcelona, Spain: pp. 1–5.
  • [18] Qaraqe KA, Celebi H, Gorcin A, El-Saigh A, Arslan H, Alouini MS. Empirical results for wideband multidimensional spectrum usage. In: 2009 IEEE International Personal, Indoor and Mobile Radio Communications Symposium; 13 – 16 September 2009; Tokyo, Japan: pp. 1262–1266.
  • [19] Jayavalan ., Mohama, H, Aripin NM, Ismail A, Ramli N, Yaacob A Ng MA. Measurements and analysis of spectrum occupancy in the cellular and TV bands. Lecture Notes on Software Engineering 2014; 2: 133-138.
  • [20] Barnes SD, van Vuuren PAJ, Maharaj BT. Spectrum occupancy investigation: Measurements in South Africa. Measurement 2013; 46: 3098-3112.
  • [21] Ayugi G, Kisolo A, Ireeta TW. Telecommunication frequency band spectrum occupancy in Kampala Uganda. International Journal of Research in Engineering and Technology 2015; 4: 390-396.
  • [22] Matheson RJ. Strategies for spectrum usage measurements. In: 1988 IEEE International Symposium on Electromagnetic Compatibility; 2 – 4 Aug. 1988; Seattle, WA, USA: 235–241.
  • [23] Čabrić D, Mishra SM, Brodersen RW. Implementation issues in spectrum sensing for cognitive radios. In: 2004 Asilomar Conference on Signals, Systems and Computers; Pacific Grove, California, USA: pp. 772-776.
  • [24] Shankar NS, Cordeiro C, Challapali K. Spectrum agile radios: Utilization and sensing architectures. In: 2005 IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks; Baltimore, MD, USA: pp. 160-169.
  • [25] Popoola JJ, and van Olst R. The performance evaluation of a spectrum sensing implementation using an automatic modulation classification detection method with a Universal Software Radio Peripheral. Expert Systems with Applications 2013; 40: 2165-2173.
  • [26] Hamdi K, Letaief KB. Cooperative communications for cognitive radio networks. In: 2007 Postgraduate Symposium, The Convergence of Telecommunications, Networks and Broadcasting, Liverpool John Moores University, pp. 1-5. Online [Available]: http://www.cms.livjm.ac.uk/pgnet2007/proceedungs/Papers/2007-087.pdf. Accessed on February 19, 2009.
  • [27] López-Benítez M, Casadevall F. An overview of Spectrum occupancy models for cognitive radio networks. In: 2011 International Federation for Information Processing, LNCS 6827, Valencia, Spain, pp. 32-41. Online [Available]: https://link.springer.com/content/pdf/10.1007%2F978-3-642-23041-7_4.pdf. Accesssed on July 20, 2017.
  • [28] Chen D, Yang J, Wu J, Tang H, Huang M. Spectrum occupancy analysis based on radio monitoring network. In: 2012 IEEE International Conference on Communications in China: Wireless Networking and Applications; 15-17 August 2012; Beijing, China: pp. 739-744.
  • [29] Popoola JJ, Obafemi AC. Technical Evaluation of Level of Radiation Exposure from GSM Base Stations to the Public in Nigeria. Journal of Engineering and Technology 2016; 7: 60-74.
  • [30] Haykin S. Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications 2005; 23: 201-220.
  • [31] Renk T, Kloeck C, Jondral FK. A cognitive approach to the detection of spectrum holes in wireless networks. In: 2007 IEEE Consumer Communications and Networking Conference; 11-13 January 2007; Las Vegas, NV: pp. 1118– 1122
Year 2018, Volume: 19 Issue: 4, 948 - 962, 31.12.2018
https://doi.org/10.18038/aubtda.425027

Abstract

References

  • [1] Ayeni AA, Faruk N, Bello OW, Sowande OA., Onidare SO, Muhammad MY. 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 2016; 5: 142-147
  • [2] López-Benítez M, Casadevall F. spectrum usage in cognitive radio networks: from field measurement to empirical models. IEICE Transactions on Communications 2014; E97-B: 242-250.
  • [3] Mehdawi M, Riley N, Paulson K, Fanan A, Ammar M. spectrum occupancy survey in hull-uk for cognitive radio applications: Measurement and analysis. International Journal of Scientific & Technology Research 2013; 2: 231-236.
  • [4] Xue J, Feng Z, Zhang P. spectrum occupancy measurements and analysis in Beijing. IERI Procedia 2013; 4: 295-302.
  • [5] Yin S, Chen D, Zhang Q, Liu M Li S. Mining spectrum usage data: A large-scale spectrum measurement study. IEEE Transactions on Mobile Computing 2012; 11: 1033-1046.
  • [6] Chiang RIC, Rowe GB, Sowerby KW. A quantitative analysis of spectral occupancy measurements for cognitive radio. In: IEEE 2007 Vehicular Technology Conference; 22-25 April 2007; Dublin, Ireland: pp. 3016-3020.
  • [7] Popoola, JJ, van Olst R. Development and demonstration of graphical user interface spectrum sensing algorithm using some wireless systems in South Africa. Journal of Applied Science and Process Engineering 2015; 2: 44-63.
  • [8] Scutari G, Palomar, DP, Barbarossa S. Cognitive MIMO radio competitive optimality design based on subspace projections. IEEE Signal Processing Magazine 2008; 25: 46–59.
  • [9] Najashi BG, Almustaphar MD, Abdi AS, Ashurah SA. Spectrum occupancy measurement in Nigeria: Results and analysis. International Journal of Computer Science Issues 2015; 12: 156-165.
  • [10] Popoola JJ, Ogunlana OA, Ajie FO, Olakunle O, Akiogbe OA, Ani-Initi SM, Omtola SK. Dynamic spectrum access: A new paradigm of converting radio spectrum wastage to wealth. International Journal of Engineering Technologies 2016; 2: 124-131.
  • [11] Sanders FH. Broadband spectrum surveys in Denver, CO, San Diego, CA, and Los Angeles, CA: Methodology, analysis, and comparative results. In: 1998 IEEE Electromagnetic Compatibility Symposium; 2-4 August 1998; Seattle, WA, USA: pp. 988-993.
  • [12] Bedogni L, Felice MD, Malabocchia F, Bononi L. Indoor communication over TV gray spaces based on spectrum measurements. In: 2014 IEEE Wireless Communication and Networking Conference; 6-9 April 2014; Istanbul, Turkey: pp. 3218-3223.
  • [13] Höyhtyä M, Matinmikko M, Chen X, Hallio J, Auranen J, Ekman R., Röning J, Engelberg J, Kalliovaara J, Taher T, Riaz A, Roberson D. Measurements and analysis of spectrum occupancy in the 2.3-2.4 GHz band in Finland and Chicago; In: 2014 International Conference on Cognitive Radio Oriented Wireless Networks, 2-4 June 2014; Finland: pp. 96-101.
  • [14] Popoola JJ, van Olst R. Application of neural network for sensing primary radio signals in a cognitive radio environment. In: 2011 IEEE AFRICON, 13-15 September 2011; Livingstone, Zambia. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&amumber=6072009.
  • [15] McHenry MA, Tenhula PA, McCloskey D, Roberson DA, Hood S. Chicago spectrum occupancy measurements and analysis and a long-term studies proposal. In: 2006 International Workshop on Technology and Policy for Accessing Spectrum, 5 August 2006, Boston, USA. Online [Available]: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.518.5560&rep=rep1&type=pdf. Accessed on July 16, 2017.
  • [16] Valenta V, Marsalek R, Baudoin G, Villegas M, Suarez M, Robert F. Survey on spectrum utilization in Europe: Measurements, analyses and observations; In: 2010 International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, June 2010; Cannes, France: pp. 1-5. Online [Available]: https://hal.archives-ouvertes.fr/hal-00492021/document. Accessed on December 11, 2016.
  • [17] López-Benítez M, Umbert MA, Casadevall F. Evaluation of spectrum occupancy in Spain for cognitive radio applications. In: 2009 IEEE Vehicular Technology Conference; 26-29 April 2009; Barcelona, Spain: pp. 1–5.
  • [18] Qaraqe KA, Celebi H, Gorcin A, El-Saigh A, Arslan H, Alouini MS. Empirical results for wideband multidimensional spectrum usage. In: 2009 IEEE International Personal, Indoor and Mobile Radio Communications Symposium; 13 – 16 September 2009; Tokyo, Japan: pp. 1262–1266.
  • [19] Jayavalan ., Mohama, H, Aripin NM, Ismail A, Ramli N, Yaacob A Ng MA. Measurements and analysis of spectrum occupancy in the cellular and TV bands. Lecture Notes on Software Engineering 2014; 2: 133-138.
  • [20] Barnes SD, van Vuuren PAJ, Maharaj BT. Spectrum occupancy investigation: Measurements in South Africa. Measurement 2013; 46: 3098-3112.
  • [21] Ayugi G, Kisolo A, Ireeta TW. Telecommunication frequency band spectrum occupancy in Kampala Uganda. International Journal of Research in Engineering and Technology 2015; 4: 390-396.
  • [22] Matheson RJ. Strategies for spectrum usage measurements. In: 1988 IEEE International Symposium on Electromagnetic Compatibility; 2 – 4 Aug. 1988; Seattle, WA, USA: 235–241.
  • [23] Čabrić D, Mishra SM, Brodersen RW. Implementation issues in spectrum sensing for cognitive radios. In: 2004 Asilomar Conference on Signals, Systems and Computers; Pacific Grove, California, USA: pp. 772-776.
  • [24] Shankar NS, Cordeiro C, Challapali K. Spectrum agile radios: Utilization and sensing architectures. In: 2005 IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks; Baltimore, MD, USA: pp. 160-169.
  • [25] Popoola JJ, and van Olst R. The performance evaluation of a spectrum sensing implementation using an automatic modulation classification detection method with a Universal Software Radio Peripheral. Expert Systems with Applications 2013; 40: 2165-2173.
  • [26] Hamdi K, Letaief KB. Cooperative communications for cognitive radio networks. In: 2007 Postgraduate Symposium, The Convergence of Telecommunications, Networks and Broadcasting, Liverpool John Moores University, pp. 1-5. Online [Available]: http://www.cms.livjm.ac.uk/pgnet2007/proceedungs/Papers/2007-087.pdf. Accessed on February 19, 2009.
  • [27] López-Benítez M, Casadevall F. An overview of Spectrum occupancy models for cognitive radio networks. In: 2011 International Federation for Information Processing, LNCS 6827, Valencia, Spain, pp. 32-41. Online [Available]: https://link.springer.com/content/pdf/10.1007%2F978-3-642-23041-7_4.pdf. Accesssed on July 20, 2017.
  • [28] Chen D, Yang J, Wu J, Tang H, Huang M. Spectrum occupancy analysis based on radio monitoring network. In: 2012 IEEE International Conference on Communications in China: Wireless Networking and Applications; 15-17 August 2012; Beijing, China: pp. 739-744.
  • [29] Popoola JJ, Obafemi AC. Technical Evaluation of Level of Radiation Exposure from GSM Base Stations to the Public in Nigeria. Journal of Engineering and Technology 2016; 7: 60-74.
  • [30] Haykin S. Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications 2005; 23: 201-220.
  • [31] Renk T, Kloeck C, Jondral FK. A cognitive approach to the detection of spectrum holes in wireless networks. In: 2007 IEEE Consumer Communications and Networking Conference; 11-13 January 2007; Las Vegas, NV: pp. 1118– 1122
There are 31 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Jide Popoola This is me

Uche Otuu This is me

Publication Date December 31, 2018
Published in Issue Year 2018 Volume: 19 Issue: 4

Cite

AMA Popoola J, Otuu U. ASSESSMENT OF RADIO SPECTRUM PROFILE IN NIGERIA USING MULTI-BAND AND MULTI-LOCATION RADIO SPECTRUM OCCUPANCY MEASUREMENTS. Estuscience - Se. December 2018;19(4):948-962. doi:10.18038/aubtda.425027