Wireless coverage and frequency availability forecasting with sparse geolocation spectrum databases

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ID: 286015
2023
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Abstract
Television white spaces refer to the unused frequencies or channels in broadcasting services. The unused spectrum can be managed to provide internet access in coordination with surrounding TV channels to avoid interference. Geolocation databases, when updated and complete, are helpful when frequencies are dynamically shared. In real life, the spectrum availability for a secondary user lacks numerous information; hence, sparse. This paper aims to forecast wireless coverage and frequency availability in sparse geolocation spectrum databases. Logistic and vector autoregression models were proposed as dynamic sparse forecasting models. Results show that the logistic models had a decent accuracy of at least 84%. In conjunction with thresholding, the linear VAR models have a decent accuracy with some exceptions, such as time predictions.
Reference Key
persistent_1760657322_68f17faa0743b Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ocampo II, Vladimir Christian R.
Journal Malay Journal
Year 2023
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdm_ece/23
Keywords Keywords not found

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