The Inverse Gamma Distribution: A New Shadowing Model

Seong Ki Yoo; Simon Cotton; Lei Zhang; Paschalis Sofotasios

The Inverse Gamma Distribution: A New Shadowing Model

Seong Ki Yoo, Simon Cotton, Lei Zhang, Paschalis Sofotasios

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Abstract

In this paper, we provide empirical evidence that the inverse gamma distribution is an excellent alternative for the lognormal and gamma distributions which are often used to model shadowing. To illustrate this, we have used field measurements obtained for wearable communication channels. The goodness-of-fit is compared with two other distributions, namely lognormal and gamma. It has been found that the inverse gamma distribution is chosen as the best model in two out of three cases considered in this study.

Original language	English
Title of host publication	Asia-Pacific Conference on Antennas and Propagation
Publisher	IEEE
Pages	(In-Press)
Number of pages	2
Volume	(In-Press)
Publication status	Accepted/In press - 2019
Externally published	Yes
Event	8th Asia-Pacific Conference on Antennas and Propagation - Incheon, Korea, Republic of Duration: 4 Aug 2019 → 7 Aug 2019 http://apcap2019.org/

Conference

Conference	8th Asia-Pacific Conference on Antennas and Propagation
Abbreviated title	APCAP 2019
Country/Territory	Korea, Republic of
City	Incheon
Period	4/08/19 → 7/08/19
Internet address	http://apcap2019.org/

Cite this

@inproceedings{5666a51e08ef4c7b8c8c20a8a7e51dca,

title = "The Inverse Gamma Distribution: A New Shadowing Model",

abstract = "In this paper, we provide empirical evidence that the inverse gamma distribution is an excellent alternative for the lognormal and gamma distributions which are often used to model shadowing. To illustrate this, we have used field measurements obtained for wearable communication channels. The goodness-of-fit is compared with two other distributions, namely lognormal and gamma. It has been found that the inverse gamma distribution is chosen as the best model in two out of three cases considered in this study.",

author = "Yoo, {Seong Ki} and Simon Cotton and Lei Zhang and Paschalis Sofotasios",

year = "2019",

language = "English",

volume = "(In-Press)",

pages = "(In--Press)",

booktitle = "Asia-Pacific Conference on Antennas and Propagation",

publisher = "IEEE",

address = "United States",

note = "8th Asia-Pacific Conference on Antennas and Propagation , APCAP 2019 ; Conference date: 04-08-2019 Through 07-08-2019",

url = "http://apcap2019.org/",

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TY - GEN

T1 - The Inverse Gamma Distribution: A New Shadowing Model

AU - Yoo, Seong Ki

AU - Cotton, Simon

AU - Zhang, Lei

AU - Sofotasios, Paschalis

PY - 2019

Y1 - 2019

N2 - In this paper, we provide empirical evidence that the inverse gamma distribution is an excellent alternative for the lognormal and gamma distributions which are often used to model shadowing. To illustrate this, we have used field measurements obtained for wearable communication channels. The goodness-of-fit is compared with two other distributions, namely lognormal and gamma. It has been found that the inverse gamma distribution is chosen as the best model in two out of three cases considered in this study.

AB - In this paper, we provide empirical evidence that the inverse gamma distribution is an excellent alternative for the lognormal and gamma distributions which are often used to model shadowing. To illustrate this, we have used field measurements obtained for wearable communication channels. The goodness-of-fit is compared with two other distributions, namely lognormal and gamma. It has been found that the inverse gamma distribution is chosen as the best model in two out of three cases considered in this study.

M3 - Conference proceeding

VL - (In-Press)

SP - (In-Press)

BT - Asia-Pacific Conference on Antennas and Propagation

PB - IEEE

T2 - 8th Asia-Pacific Conference on Antennas and Propagation

Y2 - 4 August 2019 through 7 August 2019

ER -

The Inverse Gamma Distribution: A New Shadowing Model

Abstract

Conference

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