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First- and second-order statistical characterizations of the dynamic body area propagation channel of various bandwidths

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Abstract

Comprehensive statistical characterizations of the dynamic narrowband on-body area and on-body to off-body area channels are presented. These characterizations are based on real-time measurements of the time domain channel response at carrier frequencies near the 900- and 2,400-MHz industrial, scientific, and medical bands and at a carrier frequency near the 402-MHz medical implant communications band. We consider varying amounts of body movement, numerous transmit–receive pair locations on the human body, and various bandwidths. We also consider long periods, i.e., hours of everyday activity (predominantly indoor scenarios), for on-body channel characterization. Various adult human test subjects are used. It is shown, by applying the Akaike information criterion, that the Weibull and Gamma distributions generally fit agglomerates of received signal amplitude data and that in various individual cases the Lognormal distribution provides a good fit. We also characterize fade duration and fade depth with direct matching to second-order temporal statistics. These first- and second-order characterizations have important utility in the design and evaluation of body area communications systems.

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Notes

  1. On-body implies transmission and reception both on the subject’s body.

  2. Off-body implies transmission on the subject’s body and reception somewhere off the subject’s body.

  3. One advantage of this averaging is that it enables the capture of far deeper fades.

  4. Variance of Gamma, Weibull, and Nakagami-m distributions, based on their respective distribution parameters, are given in “Appendix”.

  5. Bin size B s given by

    $$ B_s = 2I_r(x)n^{-1/3}$$

    where I r is the inter-quartile range of the data sample x (in this case measured normalized received signal amplitude) and n is the sample size of x.

  6. Lognormal, Normal, and Rayleigh best-fit PDFs are overlayed, with the best of best fits between Weibull, Gamma, and Nakagami-m PDFs also overlayed; in Fig. 9, Weibull and Gamma are overlayed.

  7. The complete set of on-body fits is in [5].

  8. The complete set of off-body fits is in [6].

  9. This case is specified in the seventh row of Table 6, in the column for 820 MHz.

  10. Although there will be some variation in parameters for each link.

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Author information

Authors and Affiliations

  1. National ICT Australia (NICTA), Locked Bag 8001, Canberra, ACT, 2601, Australia

    David B. Smith, Leif W. Hanlen, Dino Miniutti & David Rodda

  2. ICT Centre, CSIRO, P.O. Box 76, Epping, NSW, 1710, Australia

    Jian (Andrew) Zhang

  3. Air-Services Australia, GPO Box 367, Canberra, ACT, 2601, Australia

    Ben Gilbert

Authors
  1. David B. Smith
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  2. Leif W. Hanlen
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  3. Jian (Andrew) Zhang
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  4. Dino Miniutti
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  5. David Rodda
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  6. Ben Gilbert
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Corresponding author

Correspondence to David B. Smith.

Additional information

Parts of this work appeared in [1–7].

D. Smith, L. Hanlen, J. (A.) Zhang, and D. Miniutti also hold adjunct appointments with the Australian National University.

National ICT Australia is funded by the Australian Government as represented by the Department of Broadband, Communications and the Digital Economy and the Australian Research Council through the ICT Centre of Excellence program.

Appendix

Appendix

Variance of the Gamma distribution, shape parameter a, scale parameter b

$$ Var_{\rm gam}(x)=ab^2. $$
(8)

Variance of the Weibull distribution, scale parameter a, shape parameter b

$$ Var_{\rm wbl}(x)=a^2\left[\Gamma\left(1+\frac{2}{b}\right)-\Gamma^2\left(1+\frac{1}{b}\right)\right]. $$
(9)

Variance of the Nakagami-m distribution, shape parameter m, spread parameter ω

$$ Var_{\rm nak}(x)=\omega\left(1-\frac{1}{m}\left(\frac{\Gamma(m+1/2)}{\Gamma(m)}\right)^2\right). $$
(10)

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Smith, D.B., Hanlen, L.W., Zhang, J.(. et al. First- and second-order statistical characterizations of the dynamic body area propagation channel of various bandwidths. Ann. Telecommun. 66, 187–203 (2011). https://doi.org/10.1007/s12243-010-0233-8

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