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An Off-Body Channel Model for Body Area Networks in Indoor Environments

Abstract

This paper presents an off-body channel model for body area networks (BANs) in indoor environments. The proposed model, which is based on both simulations and measurements in a realistic environment, consists of three components: mean path loss, body shadowing, and multipath fading. Seven scenarios in a realistic indoor office environment containing typical scatterers have been measured: five were static (three standing and two sitting) and two dynamic (walk in a fixed place and real walk). The measurement equipment and measurement procedures are described. The mean path loss component is modeled as a log function of distance, the path loss exponent being in the range between 0.4 and 1.6, while a statistical perspective is taken for the other two components, i.e., body shadowing is found to be well modeled by a ognormal distribution and multipath fading by Rice or Nakagami-m distributions, depending on body motion characteristics. The correlation between the selected distributions and empirical data is not lower than 0.95, typically being greater than 0.98. The novelty of this model is that it takes the statistical influence of various parameters and features present in BANs into account, such as body influence, placement of the wearable antennas, user orientation in the environment, dynamism of the BAN scenario, and propagation conditions.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION no. 64, pages 4022 - 4035,
ISSN: 0018-926X
Language:
English
Publication year:
2016
Bibliographic description:
Ambroziak S., Correia L., Katulski R., Maćkowiak M., Oliveira C., Sadowski J., Turbić K.: An Off-Body Channel Model for Body Area Networks in Indoor Environments// IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. -Vol. 64, nr. 9 (2016), s.4022-4035
DOI:
Digital Object Identifier (open in new tab) 10.1109/tap.2016.2586510
Verified by:
Gdańsk University of Technology

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