Sparse characterization of body-centric radio channels

Xiaodong Yang, Aifeng Ren, Zhiya Zhang, Qammer Hussain Abbasi, Erchin Serpedin, Wei Zhao, Shuyuan Yang, Akram Alomainy

Research output: Book/ReportBook

Abstract

In this chapter, sparse characterization of BWCS is discussed. First of all, a novel sparse non-parametric model is proposed to characterize BWCS channels, it has been demonstrated that it is an important supplement to the existing parametric models; and then, compressive sensing technique is applied to the on-body UWB channel estimation, the impulse response of the channel is perfectly reconstructed; finally, particle swarm optimization based support vector regression technique is used to explore obesity’s effect on the on-body narrowband wireless channels. This chapter provides readers a totally new angle of view of looking at the current channel modelling technique in BWCS; thus will be beneficial to the ones who aim to developnew radio channel models for BWCS.

Original languageEnglish
PublisherInstitution of Engineering and Technology
Number of pages15
ISBN (Electronic)9781849199902
ISBN (Print)9781849199896
DOIs
Publication statusPublished - 1 Jan 2016

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Keywords

  • Body centric radio channels
  • Bwcs channels
  • Channel modelling technique
  • Compressed sensing
  • Compressive sensing technique
  • Impulse response
  • On-body uwb channel estimation
  • Onbody narrowband wireless channels
  • Parametric models
  • Particle swarm optimisation
  • Particle swarm optimization
  • Radio networks
  • Regression analysis
  • Sparse characterization
  • Support vector regression technique
  • Wireless channels

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Yang, X., Ren, A., Zhang, Z., Abbasi, Q. H., Serpedin, E., Zhao, W., Yang, S., & Alomainy, A. (2016). Sparse characterization of body-centric radio channels. Institution of Engineering and Technology. https://doi.org/10.1049/PBTE065E_ch4