A prediction study of path loss models from 2-73.5 GHz in an urban-macro environment

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publication2016 IEEE 83rd Vehicular Technology Conference, VTC Spring 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509016983
StatePublished - Jul 5 2016
Event83rd IEEE Vehicular Technology Conference, VTC Spring 2016 - Nanjing, China
Duration: May 15 2016May 18 2016

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252


Other83rd IEEE Vehicular Technology Conference, VTC Spring 2016


  • 5G.
  • Path loss
  • Shadow fading
  • Urban macro

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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