TY - GEN
T1 - Analyzing a 5G Dataset and Modeling Metrics of Interest
AU - Mehmeti, Fidan
AU - Porta, Thomas F.La
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The level of deployment of 5G networks is increasing every day, making this cellular technology become ubiquitous soon. Therefore, characterizing the channel quality and signal characteristics of 5G networks is of paramount importance as a first step in understanding the achievable performance of cellular users. Then, it can also serve for other important processes, such as resource planning and admission control. In this paper, we use the results of a publicly available measurement campaign of 5G users conducted by a third party and analyze various figures of merit. The analysis shows that the downlink and uplink rates for static and mobile users can be captured either by a lognormal or a Generalized Pareto distribution. Also, the time spent in the same cell by a mobile (driving) user can be captured to the best extent by a Generalized Pareto distribution. We also show some potential practical applications, among which is the prediction of the number of active users in the cell.
AB - The level of deployment of 5G networks is increasing every day, making this cellular technology become ubiquitous soon. Therefore, characterizing the channel quality and signal characteristics of 5G networks is of paramount importance as a first step in understanding the achievable performance of cellular users. Then, it can also serve for other important processes, such as resource planning and admission control. In this paper, we use the results of a publicly available measurement campaign of 5G users conducted by a third party and analyze various figures of merit. The analysis shows that the downlink and uplink rates for static and mobile users can be captured either by a lognormal or a Generalized Pareto distribution. Also, the time spent in the same cell by a mobile (driving) user can be captured to the best extent by a Generalized Pareto distribution. We also show some potential practical applications, among which is the prediction of the number of active users in the cell.
UR - http://www.scopus.com/inward/record.url?scp=85128726480&partnerID=8YFLogxK
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U2 - 10.1109/MSN53354.2021.00027
DO - 10.1109/MSN53354.2021.00027
M3 - Conference contribution
AN - SCOPUS:85128726480
T3 - Proceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021
SP - 81
EP - 88
BT - Proceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th International Conference on Mobility, Sensing and Networking, MSN 2021
Y2 - 13 December 2021 through 15 December 2021
ER -