TY - JOUR
T1 - Database-assisted spectrum prediction in 5g networks and beyond
T2 - A review and future challenges
AU - Höyhtyä, Marko
AU - Mämmelä, Aarne
AU - Chiumento, Alessandro
AU - Pollin, Sofie
AU - Forsell, Martti
AU - Cabric, Danijela
PY - 2019
Y1 - 2019
N2 - This article surveys the state of the art in spectrum prediction and learning, summarizes applications, techniques, main metrics, computational complexity, and provides practical examples. We focus on a cellular case study and define required improvements to database-assisted spectrum sharing. The use of history information and predictive spectrum modeling at different time scales provides valuable information to regulators, operators, and users of dynamic spectrum access networks. Prediction enables dynamic spectrum sharing systems to operate proactively, and consequently improves the performance in terms of reducing delays and interference among coexisting systems. Current database-assisted spectrum sharing concepts are in fact too static for many applications. Our numerical results on local-aware predictive spectrum allocation show the advantage of predictive operation in a vehicle-to-everything (V2X) scenario.
AB - This article surveys the state of the art in spectrum prediction and learning, summarizes applications, techniques, main metrics, computational complexity, and provides practical examples. We focus on a cellular case study and define required improvements to database-assisted spectrum sharing. The use of history information and predictive spectrum modeling at different time scales provides valuable information to regulators, operators, and users of dynamic spectrum access networks. Prediction enables dynamic spectrum sharing systems to operate proactively, and consequently improves the performance in terms of reducing delays and interference among coexisting systems. Current database-assisted spectrum sharing concepts are in fact too static for many applications. Our numerical results on local-aware predictive spectrum allocation show the advantage of predictive operation in a vehicle-to-everything (V2X) scenario.
UR - http://www.scopus.com/inward/record.url?scp=85070608646&partnerID=8YFLogxK
U2 - 10.1109/MCAS.2019.2925293
DO - 10.1109/MCAS.2019.2925293
M3 - Article
AN - SCOPUS:85070608646
SN - 1531-636X
VL - 19
SP - 34
EP - 45
JO - IEEE Circuits and Systems Magazine
JF - IEEE Circuits and Systems Magazine
IS - 3
M1 - 8792447
ER -