Joint statistical modeling of received power, mean delay, and delay spread for indoor wideband radio channels

Ayush Bharti, Laurent Clavier, Troels Pedersen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Abstract

We propose a joint statistical model for the received power, mean delay, and rms delay spread, which are derived from the temporal moments of the radio channel responses. Indoor wideband measurements from two different data sets show that the temporal moments are strongly correlated random variables with skewed marginals. Based on the observations, we propose a multivariate log-normal model for the temporal moments, and validate it using the experimental data sets. The proposed model is found to be flexible, as it fits different data sets well. The model can be used to jointly simulate the received power, mean delay, and rms delay spread. We conclude that independent fitting and simulation of these statistical properties is insufficient in capturing the dependencies we observe in the data.
Original languageEnglish
Title of host publicationEuropean Conference on Antennas and Propagation
Number of pages5
Publication statusAccepted/In press - 2020

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Random variables
Statistical Models

Keywords

  • temporal moments
  • mean delay
  • rms delay spread
  • multivariate log-normal
  • wideband radio channels
  • indoor propagation

Cite this

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title = "Joint statistical modeling of received power, mean delay, and delay spread for indoor wideband radio channels",
abstract = "We propose a joint statistical model for the received power, mean delay, and rms delay spread, which are derived from the temporal moments of the radio channel responses. Indoor wideband measurements from two different data sets show that the temporal moments are strongly correlated random variables with skewed marginals. Based on the observations, we propose a multivariate log-normal model for the temporal moments, and validate it using the experimental data sets. The proposed model is found to be flexible, as it fits different data sets well. The model can be used to jointly simulate the received power, mean delay, and rms delay spread. We conclude that independent fitting and simulation of these statistical properties is insufficient in capturing the dependencies we observe in the data.",
keywords = "temporal moments, mean delay, rms delay spread, multivariate log-normal, wideband radio channels, indoor propagation",
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Joint statistical modeling of received power, mean delay, and delay spread for indoor wideband radio channels. / Bharti, Ayush; Clavier, Laurent; Pedersen, Troels.

European Conference on Antennas and Propagation. 2020.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

TY - GEN

T1 - Joint statistical modeling of received power, mean delay, and delay spread for indoor wideband radio channels

AU - Bharti, Ayush

AU - Clavier, Laurent

AU - Pedersen, Troels

PY - 2020

Y1 - 2020

N2 - We propose a joint statistical model for the received power, mean delay, and rms delay spread, which are derived from the temporal moments of the radio channel responses. Indoor wideband measurements from two different data sets show that the temporal moments are strongly correlated random variables with skewed marginals. Based on the observations, we propose a multivariate log-normal model for the temporal moments, and validate it using the experimental data sets. The proposed model is found to be flexible, as it fits different data sets well. The model can be used to jointly simulate the received power, mean delay, and rms delay spread. We conclude that independent fitting and simulation of these statistical properties is insufficient in capturing the dependencies we observe in the data.

AB - We propose a joint statistical model for the received power, mean delay, and rms delay spread, which are derived from the temporal moments of the radio channel responses. Indoor wideband measurements from two different data sets show that the temporal moments are strongly correlated random variables with skewed marginals. Based on the observations, we propose a multivariate log-normal model for the temporal moments, and validate it using the experimental data sets. The proposed model is found to be flexible, as it fits different data sets well. The model can be used to jointly simulate the received power, mean delay, and rms delay spread. We conclude that independent fitting and simulation of these statistical properties is insufficient in capturing the dependencies we observe in the data.

KW - temporal moments

KW - mean delay

KW - rms delay spread

KW - multivariate log-normal

KW - wideband radio channels

KW - indoor propagation

M3 - Article in proceeding

BT - European Conference on Antennas and Propagation

ER -