Wireless coverage and frequency availability forecasting with sparse geolocation spectrum databases

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 frequenci...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ocampo, Vladimir Christian R., II
التنسيق: text
اللغة:English
منشور في: Animo Repository 2023
الموضوعات:
الوصول للمادة أونلاين:https://animorepository.dlsu.edu.ph/etdm_ece/23
الوسوم: إضافة وسم
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المؤسسة: De La Salle University
اللغة: English
الوصف
الملخص: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.