Towards sparse characterisation of on-body ultra-wideband wireless channels

Xiaodong Yang; Aifeng Ren; Zhiya Zhang; Masood Ur Rehman; Qammer Hussain Abbasi; Akram Alomainy

doi:10.1049/htl.2015.0005

Towards sparse characterisation of on-body ultra-wideband wireless channels

Xiaodong Yang
, Aifeng Ren
, Zhiya Zhang
, Masood Ur Rehman
, Qammer Hussain Abbasi
, Akram Alomainy

Institute for Research in Applicable Computing (IRAC)

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

2 Downloads (Pure)

Abstract

With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices.

Original language	English
Pages (from-to)	74-77
Number of pages	4
Journal	Health Technology Letters
Volume	2
Issue number	3
DOIs	https://doi.org/10.1049/htl.2015.0005
Publication status	Published - 1 Jul 2015

Keywords

body area networks
compressed sensing
health care
medical signal processing
ultra wideband communication
wireless channels

ASJC Scopus subject areas

Health Informatics
Health Information Management

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10.1049/htl.2015.0005

07127175Final published version, 339 KBLicence: CC BY-NC-ND

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title = "Towards sparse characterisation of on-body ultra-wideband wireless channels",

abstract = "With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices.",

keywords = "body area networks, compressed sensing, health care, medical signal processing, ultra wideband communication, wireless channels",

author = "Xiaodong Yang and Aifeng Ren and Zhiya Zhang and Rehman, \{Masood Ur\} and Abbasi, \{Qammer Hussain\} and Akram Alomainy",

note = "Publisher Copyright: {\textcopyright} 2015 The Institution of Engineering and Technology.",

year = "2015",

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doi = "10.1049/htl.2015.0005",

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T1 - Towards sparse characterisation of on-body ultra-wideband wireless channels

AU - Yang, Xiaodong

AU - Ren, Aifeng

AU - Zhang, Zhiya

AU - Rehman, Masood Ur

AU - Abbasi, Qammer Hussain

AU - Alomainy, Akram

PY - 2015/7/1

Y1 - 2015/7/1

N2 - With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices.

AB - With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices.

KW - body area networks

KW - compressed sensing

KW - health care

KW - medical signal processing

KW - ultra wideband communication

KW - wireless channels

UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4612537/

U2 - 10.1049/htl.2015.0005

DO - 10.1049/htl.2015.0005

M3 - Article

SN - 2053-3713

VL - 2

SP - 74

EP - 77

JO - Health Technology Letters

JF - Health Technology Letters

IS - 3

ER -

Towards sparse characterisation of on-body ultra-wideband wireless channels

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Keywords

ASJC Scopus subject areas

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