A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment

Timothy Thomas, Marcin Rybakowski, Shu Sun, Theodore S. Rappaport, Huan Cong Nguyen, Istvan Kovacs, Ignacio Rodriguez

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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Resumé

It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve-match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2.0 to 28 GHz and ray-tracing studies from 2.0 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.
OriginalsprogEngelsk
TitelVehicular Technology Conference (VTC Spring), 2016 IEEE 83rd
Antal sider5
ForlagIEEE
Publikationsdato18 maj 2016
ISBN (Elektronisk)978-1-5090-1698-3
DOI
StatusUdgivet - 18 maj 2016
Begivenhed2016 IEEE 83rd Vehicular Technology Conference VTC2016-Spring - Nanjing, Nanjing, Kina
Varighed: 15 maj 201618 maj 2016

Konference

Konference2016 IEEE 83rd Vehicular Technology Conference VTC2016-Spring
LokationNanjing
LandKina
ByNanjing
Periode15/05/201618/05/2016
NavnI E E E V T S Vehicular Technology Conference. Proceedings
ISSN1550-2252

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Macros
Anchors
Ray tracing
Parameterization
Physics

Citer dette

Thomas, T., Rybakowski, M., Sun, S., Rappaport, T. S., Nguyen, H. C., Kovacs, I., & Rodriguez, I. (2016). A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment. I Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd IEEE. I E E E V T S Vehicular Technology Conference. Proceedings https://doi.org/10.1109/VTCSpring.2016.7504094
Thomas, Timothy ; Rybakowski, Marcin ; Sun, Shu ; Rappaport, Theodore S. ; Nguyen, Huan Cong ; Kovacs, Istvan ; Rodriguez, Ignacio. / A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment. Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd. IEEE, 2016. (I E E E V T S Vehicular Technology Conference. Proceedings).
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title = "A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment",
abstract = "It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve-match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2.0 to 28 GHz and ray-tracing studies from 2.0 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.",
author = "Timothy Thomas and Marcin Rybakowski and Shu Sun and Rappaport, {Theodore S.} and Nguyen, {Huan Cong} and Istvan Kovacs and Ignacio Rodriguez",
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Thomas, T, Rybakowski, M, Sun, S, Rappaport, TS, Nguyen, HC, Kovacs, I & Rodriguez, I 2016, A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment. i Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd. IEEE, I E E E V T S Vehicular Technology Conference. Proceedings, 2016 IEEE 83rd Vehicular Technology Conference VTC2016-Spring, Nanjing, Kina, 15/05/2016. https://doi.org/10.1109/VTCSpring.2016.7504094

A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment. / Thomas, Timothy; Rybakowski, Marcin; Sun, Shu; Rappaport, Theodore S.; Nguyen, Huan Cong; Kovacs, Istvan; Rodriguez, Ignacio.

Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd. IEEE, 2016. (I E E E V T S Vehicular Technology Conference. Proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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AU - Rybakowski, Marcin

AU - Sun, Shu

AU - Rappaport, Theodore S.

AU - Nguyen, Huan Cong

AU - Kovacs, Istvan

AU - Rodriguez, Ignacio

PY - 2016/5/18

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N2 - It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve-match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2.0 to 28 GHz and ray-tracing studies from 2.0 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.

AB - It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve-match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2.0 to 28 GHz and ray-tracing studies from 2.0 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.

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Thomas T, Rybakowski M, Sun S, Rappaport TS, Nguyen HC, Kovacs I et al. A Prediction Study of Path Loss Models from 2-73.5 GHz in an Urban-Macro Environment. I Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd. IEEE. 2016. (I E E E V T S Vehicular Technology Conference. Proceedings). https://doi.org/10.1109/VTCSpring.2016.7504094