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The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces

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dc.contributor.author Lysko, Albert A
dc.contributor.author Masonta, Moshe T
dc.contributor.author Johnson, DL
dc.date.accessioned 2015-03-12T09:38:48Z
dc.date.available 2015-03-12T09:38:48Z
dc.date.issued 2015
dc.identifier.citation Lysko, A.A., Johnson, D.L. and Masonta, M.T. 2015. The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces. In: White Space Communication. Springer International Publishing: New York, USA, pp 75-116 en_US
dc.identifier.isbn 978-3-319-08746-7
dc.identifier.issn 1860-4862
dc.identifier.uri http://link.springer.com/chapter/10.1007%2F978-3-319-08747-4_4
dc.identifier.uri http://hdl.handle.net/10204/7898
dc.description Copyright: Springer International Publishing: New York, USA en_US
dc.description.abstract The lack of sufficient fixed-line communication infrastructure in African rural areas has resulted in wireless communication being the only cost effective alternative solution for broadband connectivity. However, access to valuable spectrum—specifically sub-1 GHz spectrum—is mostly allocated to broadcasting or mobile telephony. The global digital switch over (DSO) of television (TV) broadcasting systems will see more sub-1 GHz TV band spectrum being made available for the digital dividend and also result in more TV white space (TVWS) spectrum. In order to ensure dynamic and efficient utilization of the TV white space spectrum, there is an increasing trend to use cognitive radiosystems that use geo-location spectrum databases and spectrum sensing as an enabling technology. In this paper, we overview the relevant signals and standards and present field measurement results showing the actual usage of TV bands before the DSO in selected urban and rural areas of Southern Africa. Measurements were conducted using low-cost and high-grade radio instruments. The low-cost spectrum analyser was built in-house using the Universal Software Radio Peripheral (USRP-2) and GNU Radio software. A metric to quantify available TV white space, based on the minimum acceptable field strength, is introduced and applied to quantify the availability of TV white space. Our results show medium spectrum usage in urban areas and very low spectrum usage in rural areas, making TVWS an attractive solution for rural broadband connectivity. en_US
dc.language.iso en en_US
dc.publisher Springer International Publishing en_US
dc.relation.ispartofseries Workflow;13918
dc.subject African rural area communication infrastructure en_US
dc.subject Digital switch over en_US
dc.subject DSO en_US
dc.subject Radio frequency en_US
dc.subject Southern Africa en_US
dc.subject Spectrum en_US
dc.subject Television white spaces en_US
dc.subject Universal Software Radio Peripheral en_US
dc.subject USRP-2 en_US
dc.title The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces en_US
dc.type Book Chapter en_US
dc.identifier.apacitation Lysko, A. A., Masonta, M. T., & Johnson, D. (2015). The television white space opportunity in Southern Africa: From field measurements to quantifying white spaces., <i>Workflow;13918</i> Springer International Publishing. http://hdl.handle.net/10204/7898 en_ZA
dc.identifier.chicagocitation Lysko, Albert A, Moshe T Masonta, and DL Johnson. "The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces" In <i>WORKFLOW;13918</i>, n.p.: Springer International Publishing. 2015. http://hdl.handle.net/10204/7898. en_ZA
dc.identifier.vancouvercitation Lysko AA, Masonta MT, Johnson D. The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces.. Workflow;13918. [place unknown]: Springer International Publishing; 2015. [cited yyyy month dd]. http://hdl.handle.net/10204/7898. en_ZA
dc.identifier.ris TY - Book Chapter AU - Lysko, Albert A AU - Masonta, Moshe T AU - Johnson, DL AB - The lack of sufficient fixed-line communication infrastructure in African rural areas has resulted in wireless communication being the only cost effective alternative solution for broadband connectivity. However, access to valuable spectrum—specifically sub-1 GHz spectrum—is mostly allocated to broadcasting or mobile telephony. The global digital switch over (DSO) of television (TV) broadcasting systems will see more sub-1 GHz TV band spectrum being made available for the digital dividend and also result in more TV white space (TVWS) spectrum. In order to ensure dynamic and efficient utilization of the TV white space spectrum, there is an increasing trend to use cognitive radiosystems that use geo-location spectrum databases and spectrum sensing as an enabling technology. In this paper, we overview the relevant signals and standards and present field measurement results showing the actual usage of TV bands before the DSO in selected urban and rural areas of Southern Africa. Measurements were conducted using low-cost and high-grade radio instruments. The low-cost spectrum analyser was built in-house using the Universal Software Radio Peripheral (USRP-2) and GNU Radio software. A metric to quantify available TV white space, based on the minimum acceptable field strength, is introduced and applied to quantify the availability of TV white space. Our results show medium spectrum usage in urban areas and very low spectrum usage in rural areas, making TVWS an attractive solution for rural broadband connectivity. DA - 2015 DB - ResearchSpace DP - CSIR KW - African rural area communication infrastructure KW - Digital switch over KW - DSO KW - Radio frequency KW - Southern Africa KW - Spectrum KW - Television white spaces KW - Universal Software Radio Peripheral KW - USRP-2 LK - https://researchspace.csir.co.za PY - 2015 SM - 978-3-319-08746-7 SM - 1860-4862 T1 - The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces TI - The television white space opportunity in Southern Africa: from field measurements to quantifying white spaces UR - http://hdl.handle.net/10204/7898 ER - en_ZA


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