An improved radio channel characterisation for ultra wideband on-body communications using regression method

Qammer H. Abbasi, Sidrah Liaqat, Liaqat Ali, Akram Alomainy

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

1 Citation (Scopus)

Abstract

In body centric wireless communication (BCWC), radio propagation modelling is an important parameter for an accurate system design like any other wireless system. To investigate and analyse the performance of single and multiple antennas for body-centric wireless communication channels, various approaches can be adopted. It can either be predicted through detailed simulations using numerical digital phantom, by real time measurements or by using a statistical channel model, which completely characterises the channels and the environment. The statistical model plays an important role in BCWC radio propagation characterization. However, a traditional statistical model is not necessarily the best choice for limited samples. In this paper statistical modeling is performed using regression method on the mean delay data to improve the density estimation of body-centric radio propagation channel.

Original languageEnglish
Title of host publication2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013
PublisherIEEE Computer Society
ISBN (Print)9781479907663
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013 - Jinhua, China
Duration: 1 Jul 20133 Jul 2013

Other

Other2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013
CountryChina
CityJinhua
Period1/7/133/7/13

Fingerprint

Statistical Models
Radio
Ultra-wideband (UWB)
Radio transmission
Communication
Time measurement
Systems analysis
Antennas
Computer simulation

Keywords

  • radio propagation modelling
  • Ultra wideband
  • wireless body area networks

ASJC Scopus subject areas

  • Information Systems
  • Health Informatics

Cite this

Abbasi, Q. H., Liaqat, S., Ali, L., & Alomainy, A. (2013). An improved radio channel characterisation for ultra wideband on-body communications using regression method. In 2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013 [6708063] IEEE Computer Society. https://doi.org/10.1109/Ubi-HealthTech.2013.6708063

An improved radio channel characterisation for ultra wideband on-body communications using regression method. / Abbasi, Qammer H.; Liaqat, Sidrah; Ali, Liaqat; Alomainy, Akram.

2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013. IEEE Computer Society, 2013. 6708063.

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

Abbasi, QH, Liaqat, S, Ali, L & Alomainy, A 2013, An improved radio channel characterisation for ultra wideband on-body communications using regression method. in 2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013., 6708063, IEEE Computer Society, 2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013, Jinhua, China, 1/7/13. https://doi.org/10.1109/Ubi-HealthTech.2013.6708063
Abbasi QH, Liaqat S, Ali L, Alomainy A. An improved radio channel characterisation for ultra wideband on-body communications using regression method. In 2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013. IEEE Computer Society. 2013. 6708063 https://doi.org/10.1109/Ubi-HealthTech.2013.6708063
Abbasi, Qammer H. ; Liaqat, Sidrah ; Ali, Liaqat ; Alomainy, Akram. / An improved radio channel characterisation for ultra wideband on-body communications using regression method. 2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013. IEEE Computer Society, 2013.
@inproceedings{8e274be133e54fa9bfc7883b28bd3f20,
title = "An improved radio channel characterisation for ultra wideband on-body communications using regression method",
abstract = "In body centric wireless communication (BCWC), radio propagation modelling is an important parameter for an accurate system design like any other wireless system. To investigate and analyse the performance of single and multiple antennas for body-centric wireless communication channels, various approaches can be adopted. It can either be predicted through detailed simulations using numerical digital phantom, by real time measurements or by using a statistical channel model, which completely characterises the channels and the environment. The statistical model plays an important role in BCWC radio propagation characterization. However, a traditional statistical model is not necessarily the best choice for limited samples. In this paper statistical modeling is performed using regression method on the mean delay data to improve the density estimation of body-centric radio propagation channel.",
keywords = "radio propagation modelling, Ultra wideband, wireless body area networks",
author = "Abbasi, {Qammer H.} and Sidrah Liaqat and Liaqat Ali and Akram Alomainy",
year = "2013",
doi = "10.1109/Ubi-HealthTech.2013.6708063",
language = "English",
isbn = "9781479907663",
booktitle = "2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013",
publisher = "IEEE Computer Society",

}

TY - GEN

T1 - An improved radio channel characterisation for ultra wideband on-body communications using regression method

AU - Abbasi, Qammer H.

AU - Liaqat, Sidrah

AU - Ali, Liaqat

AU - Alomainy, Akram

PY - 2013

Y1 - 2013

N2 - In body centric wireless communication (BCWC), radio propagation modelling is an important parameter for an accurate system design like any other wireless system. To investigate and analyse the performance of single and multiple antennas for body-centric wireless communication channels, various approaches can be adopted. It can either be predicted through detailed simulations using numerical digital phantom, by real time measurements or by using a statistical channel model, which completely characterises the channels and the environment. The statistical model plays an important role in BCWC radio propagation characterization. However, a traditional statistical model is not necessarily the best choice for limited samples. In this paper statistical modeling is performed using regression method on the mean delay data to improve the density estimation of body-centric radio propagation channel.

AB - In body centric wireless communication (BCWC), radio propagation modelling is an important parameter for an accurate system design like any other wireless system. To investigate and analyse the performance of single and multiple antennas for body-centric wireless communication channels, various approaches can be adopted. It can either be predicted through detailed simulations using numerical digital phantom, by real time measurements or by using a statistical channel model, which completely characterises the channels and the environment. The statistical model plays an important role in BCWC radio propagation characterization. However, a traditional statistical model is not necessarily the best choice for limited samples. In this paper statistical modeling is performed using regression method on the mean delay data to improve the density estimation of body-centric radio propagation channel.

KW - radio propagation modelling

KW - Ultra wideband

KW - wireless body area networks

UR - http://www.scopus.com/inward/record.url?scp=84894148652&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84894148652&partnerID=8YFLogxK

U2 - 10.1109/Ubi-HealthTech.2013.6708063

DO - 10.1109/Ubi-HealthTech.2013.6708063

M3 - Conference contribution

SN - 9781479907663

BT - 2013 1st International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare, Ubi-HealthTech 2013

PB - IEEE Computer Society

ER -