{"title":"An improved radio channel characterisation for ultra wideband on-body communications using regression method","authors":"Q. Abbasi, S. Liaqat, Liaqat Ali, A. Alomainy","doi":"10.1109/UBI-HEALTHTECH.2013.6708063","DOIUrl":null,"url":null,"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.","PeriodicalId":150578,"journal":{"name":"2013 First International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare (Ubi-HealthTech)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 First International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare (Ubi-HealthTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBI-HEALTHTECH.2013.6708063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
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.