Cooperative communications in ultra-wideband wireless body area networks: channel modeling and system diversity analysis

  • Authors:

  • Yifan Chen;Jianqi Teo;Joshua Chong Yue Lai;Erry Gunawan;Kay Soon Low;Cheong Boon Soh;Predrag B. Rapajic

  • Affiliations:

  • School of Engineering, University of Greenwich, Kent, United Kingdom and School of Computer, Electronic and Information, Guangxi University, Nanning, China;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Engineering, University of Greenwich, Kent, United Kingdom

  • Venue:
  • IEEE Journal on Selected Areas in Communications - Special issue on body area networking: Technology and applications
  • Year:
  • 2009

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Abstract

In this paper, we explore the application of cooperative communications in ultra-wideband (UWB) wireless body area networks (BANs), where a group of on-body devices may collaborate together to communicate with other groups of on-body equipment. Firstly, time-domain UWB channel measurements are presented to characterize the body-centric multipath channel and to facilitate the diversity analysis in a cooperative BAN (CoBAN). We focus on the system deployment scenario when the human subject is in the sitting posture. Important channel parameters such as the pathloss, power variation, power delay profile (PDP), and effective received power (ERP) cross-correlation are investigated and statistically analyzed. Provided with the model preliminaries, a detailed analysis on the diversity level in a CoBAN is provided. Specifically, an intuitive measure is proposed to quantify the diversity gains in a single-hop cooperative network, which is defined as the number of independent multipaths that can be averaged over to detect symbols. As this measure provides the largest number of redundant copies of transmitted information through the body-centric channel, it can be used as a benchmark to access the performance bound of various diversity-based cooperative schemes in futuristic body sensor systems.