TY - GEN
T1 - A prediction study of path loss models from 2-73.5 GHz in an urban-macro environment
AU - Thomas, Timothy A.
AU - Rybakowski, Marcin
AU - Sun, Shu
AU - Rappaport, Theodore S.
AU - Nguyen, Huan
AU - Kovacs, Istvan Z.
AU - Rodriguez, Ignacio
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/5
Y1 - 2016/7/5
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 mod-els 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 to 28 GHz and ray-tracing studies from 2 to 73.5 GHz, both in an urban-macro environ-ment, to assess the prediction performance of the two PL model-ing 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 per- formance in the prediction sets while also providing a parameter-ization which is more stable over a substantial number of differ-ent 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 mod-els 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 to 28 GHz and ray-tracing studies from 2 to 73.5 GHz, both in an urban-macro environ-ment, to assess the prediction performance of the two PL model-ing 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 per- formance in the prediction sets while also providing a parameter-ization which is more stable over a substantial number of differ-ent measurement sets.
KW - 5G.
KW - Path loss
KW - Shadow fading
KW - Urban macro
UR - http://www.scopus.com/inward/record.url?scp=84979781093&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979781093&partnerID=8YFLogxK
U2 - 10.1109/VTCSpring.2016.7504094
DO - 10.1109/VTCSpring.2016.7504094
M3 - Conference contribution
AN - SCOPUS:84979781093
T3 - IEEE Vehicular Technology Conference
BT - 2016 IEEE 83rd Vehicular Technology Conference, VTC Spring 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 83rd IEEE Vehicular Technology Conference, VTC Spring 2016
Y2 - 15 May 2016 through 18 May 2016
ER -