Challenge of Dynamic Body Area Networks

Challenge of a dynamic BAN
channel
Leif Hanlen

with support from
A. Boulis, B. Gilbert, V. Chaganti, L. Craven, D. Fang, T. Lamahewa, D. Lewis,
D. Miniutti, O. Nagy, D. Rodda, K. Sithamparanathan, D. Smith, Y. Tselishchev, A. Zhang,

National ICT Australia, & Australian National University
leif.hanlen@nicta.com.au
Director eHealth @ NICTA

PIMRC: challenge of modeling dynamic BANs c 2011 leif.hanlen@nicta.com.au

Humans are hard to model

PIMRC: challenge of modeling dynamic BANs c 2011 leif.hanlen@nicta.com.au 1

Why are BANs diﬀerent?

• Whole networks are in motion

• Base-station is weak

• base-stations are mobile, AND may be in
range of other networks
vs – some networks stay in range for long
periods (family members)
– some networks pass in and out of range
very quickly (shoppers)
– nodes in network A may have stronger
signal from network B
with thanks: Ohio University
– coordination between BANs impossible


Interference

• Your arm span is approx. 2.5m
tip-of-ﬁnger to tip-of-ﬁnger

• How many BANs in 6m (edge
length) cube around you?

• How much interference?

how many networks is he interfering
with?
[Hanlen et al., 2010b] Hanlen, L. W., Miniutti, D., Smith, D. B., Rodda, D., and Gilbert, B. (2010b). Co-Channel interference
in body area networks with indoor measurements at 2.4GHz: Distance-to-interferer is a poor estimate of received interference
power. Springer Intl. J. Wireless Inform. Net., 17.


Myth busters

1. Distance-based path-loss models? (no)

2. Dynamics (single- and multi-link), little/no ISI

3. Cellular interference models (no!)

4. Sleeping is (very) bad for BANs


Warning Distance considered harmful

[Friis, 1946]
Friis free-space

linear: Preceived ∝ D−a · Ptransmit
dB: Ploss = a · 20 log10 (Dmetres) +b + σ · N (0, 1)
path loss wrt distance modelling noise

• α is exponential path loss, for far-ﬁeld

• ‘Noise’ is actually model error – not measurement error

[Friis, 1946] Friis, H. T. (1946). A note on a simple transmission formula. Proc. IRE, 34(5):254–256.


Co-channel interference

40 −50
Median
30 Max −55
Min
20 Exponent−fit −60
Free−space
10 −65

0 −70

−10 −75

−20 −80

−30 −85

−40 −90 Signal
Interference
−50 −95
0 2 4 6 8 50 60 70 80 90 100

Subjects moved randomly on grid, we selected one subject as “signal”
one as “intererer”: ‘line-of-best ﬁt’ is meaningless: ±20dB errors.
[Hanlen et al., 2010b] Hanlen, L. W., Miniutti, D., Smith, D. B., Rodda, D., and Gilbert, B. (2010b). Co-Channel
interference in body area networks with indoor measurements at 2.4GHz: Distance-to-interferer is a poor estimate of
received interference power. Springer Intl. J. Wireless Inform. Net., 17.


Dynamics

• How to capture real dynamic channels?

• Is frequency/ISI a factor?

• Can we use “simple” transceivers?

• What do we want to know?

[Smith et al., 2008a] Smith, D. B., Hanlen, L. W., Miniutti, D., Zhang, J. A., Rodda, D., and Gilbert, B. (2008a). Statistical
characterization of the dynamic narrowband body area channel. In Intl. Symp. App. Sci. Bio-Med. Comm. Tech., Aalborg,
Denmark.


CDF − Back to Chest Standing CDF − Left ankle to right hip walking
1 1

0.9 0.9

0.8 0.8

0.7 0.7
Cumulative probability

Cumulative probability
0.6 0.6

0.5 0.5

0.4 Measured data 0.4
Normal
0.3 0.3 Measured data
Lognormal
Normal
Gamma
0.2 0.2 Lognormal
Gamma
0.1 0.1

0 0
0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.2 0.4 0.6 0.8 1
Normalized Received Power Normalized Received Power

standing walking

Some measurements based on the National
Instruments approach.


3
Measured Data
Normal fit
2.5 Lognormal
Nakagami−m
Rayleigh
2

Density
1.5

1

0.5

0
0 0.2 0.4 0.6 0.8 1
Normalised Amplitude (0..1)

Left-ankle to Right-hip, walking
Almost every ﬁt is ”ok” except Rayleigh.
[Smith et al., 2010b] Smith, D. B., Hanlen, L. W., Zhang, J. A., Miniutti, D., Rodda, D., and Gilbert, B. (2010b). First and
second-order statistical characterizations of the dynamic body-area propagation channel of various bandwidths. Annals of
Telecommunications.


Inter-symbol Interference?

[Islam and Kwak, 2010]
• “..environment of WBAN causes a dense multipath...”

• “[60GHz] multipath is present...much less deep than [2.4GHz]”
[Hall et al., 2010]

[Smith et al., 2008a]
• “no resolvable multipath..”

[Cao et al., 2009]
• “need to assess [UWB] multipath”

[Islam and Kwak, 2010] Islam, S. M. R. and Kwak, K. S. (2010). A comprehensive study of channel estimation for
WBAN-based healthcare systems: Feasibility of using multiband UWB. J Med Syst.
[Hall et al., 2010] Hall, P. S., Hao, Y., and Cotton, S. L. (2010). Progress in antennas and propagation for body area
networks. In Intl. Symp. Sig., Sys. and Elect.
[Smith et al., 2008a] Smith, D. B., Hanlen, L. W., Miniutti, D., Zhang, J. A., Rodda, D., and Gilbert, B. (2008a). Statistical
characterization of the dynamic narrowband body area channel. In Intl. Symp. App. Sci. Bio-Med. Comm. Tech., Aalborg,
Denmark.
[Cao et al., 2009] Cao, H., Leung, V., Chow, C., and Chan, H. (2009). Enabling technologies for wireless body area networks:
A survey and outlook. IEEE Commun. Mag., 47(12):84–93.


Frequency response from mean tap values
0.1
2360MHz
0 820MHz
427MHz
−0.1

Response (dB) −0.2

−0.3

−0.4

−0.5

−0.6

−0.7 4 5 6 7 8
10 10 10 10 10
Frequency
[Smith et al., 2009a]
Tap values in

[Smith et al., 2009a] Smith, D. B., Miniutti, D., Hanlen, L. W., Zhang, J. A., Rodda, D., and Gilbert, B. (2009a). Power
delay proﬁles for dynamic narrowband body area network channels ID: 802.15-09-0187. IEEE submission.


How to model the real body area channel?

test subject "free" to move as per normal

Velcro(TM)

sounder on chest

3rd party accelerometer
on waist

sounder on wrist

NICTA
open source channel sounder [250kHz @ 2.4GHz]

Build transceiver, transmit 200 packets per second, measure RSSI
[Hanlen et al., 2010a] Hanlen, L. W., Chaganti, V. G., Gilbert, B., Rodda, D., Lamahewa, T. A., and Smith, D. B. (2010a).
Open-source testbed for body area networks: 200 sample/sec, 12 hrs continuous measurement. In IEEE PIMRC.


How do we ﬁt the distributions?

2nd Order, Akaike Information Criterion

2K(K + 1)
AICc = −2 ln Lθ,data
ˆ + 2K +
n−K −1
AIC 1st order

ˆ
• Lθ,data maximum log-likelihood score over parameters θ
ˆ

• K number of parameters (=1,2 for us)

• n number of sample points (=4000 for us)

Lower scores imply better ﬁts.


Stat ﬁts: what we want

• First order stats: gives simple independent sample model for channel.
Ensemble amplitude distribution.
– Likelihood of having (in)suﬃcient receive signal strength

• Second order stats: level crossing rate, and fade durations
– Likelihood of dropping (1 or more) packets
– Likelihood of achieving latency requirements
– Indication of packet length

[Smith et al., 2010b] Smith, D. B., Hanlen, L. W., Zhang, J. A., Miniutti, D., Rodda, D., and Gilbert, B. (2010b). First and
second-order statistical characterizations of the dynamic body-area propagation channel of various bandwidths. Annals of
Telecommunications.
[Chaganti et al., 2010] Chaganti, V. G., Smith, D. B., and Hanlen, L. W. (2010). Second order statistics for many-link body
area networks. IEEE Antennas Wireless Propagat. Lett., 9:322–325.


Example of body-worn channel

Human subject with sensors for 15 hours continuous use
Data online @ nicta.com.au


Open source hardware

Transceiver, all design ﬁles are online @ nicta.com.au


Example of body-worn sleeping channel

−75
off−body
on−body
−80

−85

−90

−95

−100

−105
0 20 40 60 80 100
Time (minutes)


Some of the measurement setup

(moved away during exp.)
subject

researcher


Complexity and Error

Error (inaccurate)
poor
lossy models

complexity
accuracy trade

the ideal the system is
model the model

complexity (# params)


−4
x 10
6
median

2
mean per link
5
Error E = H − F mean

4

3 stat ﬁt per link

2 agglomerate ﬁt agglomerate hist.

1 mean per link
& agglomerate stat
per-link hist.
0
0 1 2 3 4 5 6 7 8
Complexity C = log2(P )
[Hanlen et al., 2011] Hanlen, L. W., Smith, D. B., and Lamahewa, T. A. (2011). A new look at the body area network
channel model. In Europe. Conf. Ant. Prop.


PHY simulation
1. Generate Weibull random numbers

2. Generate Rayleigh random numbers with appropriate Doppler spread
[Filho et al., 2007]
3. Apply order-statistics
(a) {Rp, I} = sort(Rayleigh power)
(b) Weibull power = sort(Weibull power)
(c) Weibull power(I) = Weibull power

Available from NICTA website
[Filho et al., 2007] Filho, J., Yacoub, M., and Fraidenraich, G. (2007). A simple accurate method for generating autocorrelated
Nakagami-m envelope sequences. IEEE Commun. Lett., 11(3):231–233.
[Smith et al., 2008b] Smith, D. B., Miniutti, D., Zhang, J. A., and Hanlen, L. W. (2008b). Matlab code for generating BAN
fading proﬁle ID: 802.15-08-0850. IEEE submission.
[Smith et al., 2009b] Smith, D. B., Zhang, J. A., Hanlen, L. W., Miniutti, D., Rodda, D., and Gilbert, B. (2009b). A
simulator for the dynamic on-body area propagation channel. In IEEE Int. Symp. Antennas & Propagation, Charleston,
USA.


MAC simulation

• Event-based MAC simulation
tool, based on Omnet++

• channel gain conditional
probability

P (at+τ = γ|at = γ )

Available open-source from NICTA • Allows complete sensor
network simulation (cross-
layer)
[Tselishchev et al., 2010] Tselishchev, Y., Boulis, A., and Libman, L. (2010). Experiences and lessons from implementing a
wireless sensor network MAC protocol in the Castalia simulator. In IEEE Wireless Commun. Net. Conf., WCNC.


Having the right model is key

[Boulis et al., 2010] Boulis, A., Tselishchev, Y., Libman, L., Smith, D. B., and Hanlen, L. W. (2010). Impact of wireless
channel temporal variation on MAC design for body area networks. ACM Transactions on Embedded Computing, to appear.


Conclusion

• Models are for using, not for demonstrating mathematical skill

• Beware models that match intuition: likely they are wrong!

• Good models make good simulators

• We built it: so you don’t have to


References
[ACIL Tasman, 2009] ACIL Tasman (2009). The ‘apartments for life’ housing, care & support concept
for older people: An assessment of economic and budgetary implications of The Benevolent Society’s
proposed model for some housing developments for older people in Australia. prepared for The
Benevolent Society of Australia.
[Bartlett et al., 2010] Bartlett, C., Boehncke, K., Wallace, V., and Johnstone-Burt, A. (2010). Optimising
e-health value using an investment model to build a foundation for program success. online, Booz-Allen
http://www.booz.com/anzsea/home/40212171/40212709/40213345/eHealth.
[Boulis et al., 2010] Boulis, A., Tselishchev, Y., Libman, L., Smith, D. B., and Hanlen, L. W. (2010).
Impact of wireless channel temporal variation on MAC design for body area networks. ACM
Transactions on Embedded Computing, to appear.
[Cao et al., 2009] Cao, H., Leung, V., Chow, C., and Chan, H. (2009). Enabling technologies for wireless
body area networks: A survey and outlook. IEEE Commun. Mag., 47(12):84–93.
[Chaganti et al., 2011] Chaganti, V. G., Hanlen, L. W., and Lamahewa, T. A. (2011). Semi-Markov
modeling for body area networks. In IEEE Intl. Conf. Commun., ICC.
[Chaganti et al., 2010] Chaganti, V. G., Smith, D. B., and Hanlen, L. W. (2010). Second order statistics
for many-link body area networks. IEEE Antennas Wireless Propagat. Lett., 9:322–325.
[Chebbo, 2008] Chebbo, H. (2008). Literature review of energy eﬃcient MAC in WSN/BAN ID:802-15-
08-0331. IEEE submission.
[Chen and Viberg, 2009] Chen, M. and Viberg, M. (2009). Long-range channel prediction based on
nonstationary parameteric modeling. IEEE Trans. Signal Processing, 57(2):622–634.


[Chipcon, 2009] Chipcon (2009). CC2500 low-cost low-power 2.4 GHz RF transceiver (rev. c). Datasheet
http://focus.ti.com/docs/prod/folders/print/cc2500.html.
[Continua Health Alliance, 2009] Continua Health Alliance (2009). Continua health alliance:the next
generation of personal telehealth is here. online.
[Cotton and Scanlon, 2009] Cotton, S. and Scanlon, W. (2009). Channel characterization for single-
and multiple-antenna wearable systems used for indoor body-to-body communications. IEEE Trans.
Antennas Propagat., 57(4):980–990.
[Filho et al., 2007] Filho, J., Yacoub, M., and Fraidenraich, G. (2007). A simple accurate method for
generating autocorrelated Nakagami-m envelope sequences. IEEE Commun. Lett., 11(3):231–233.
[Fox, 2010] Fox, S. (2010). The future of health: Robots, enchanted
objects, and networks. online http://e-patients.net/archives/2010/11/
the-future-of-health-robots-enchanted-objects-and-networks.html.
[Fraidenraich and Yacoub, 2006] Fraidenraich, G. and Yacoub, M. D. (2006). The α-η -κ and α-κ-µ
fading distributions. In IEEE Intl. Symp. Spread Spectrum Techniques and Applications ISSSTA, pages
16–20.
[Friis, 1946] Friis, H. T. (1946). A note on a simple transmission formula. Proc. IRE, 34(5):254–256.
[Fu, 1975] Fu, J. C. (1975). The rate of convergence of consistent point estimators. Ann. Stat.,
3(1):234–240.
[G´ron and Villian, 2009] G´ron, E. and Villian, A. (2009). A new insight into Bluetooth piconets
e e
coexistence. Wireless Commun. Mob. Comput., 9:673–683.
[Hall et al., 2010] Hall, P. S., Hao, Y., and Cotton, S. L. (2010). Progress in antennas and propagation
for body area networks. In Intl. Symp. Sig., Sys. and Elect.


[Hanlen et al., 2010a] Hanlen, L. W., Chaganti, V. G., Gilbert, B., Rodda, D., Lamahewa, T. A., and
Smith, D. B. (2010a). Open-source testbed for body area networks: 200 sample/sec, 12 hrs continuous
measurement. In IEEE PIMRC.
[Hanlen et al., 2010b] Hanlen, L. W., Miniutti, D., Smith, D. B., Rodda, D., and Gilbert, B. (2010b).
Co-Channel interference in body area networks with indoor measurements at 2.4GHz: Distance-to-
interferer is a poor estimate of received interference power. Springer Intl. J. Wireless Inform. Net.,
17.
[Hanlen et al., 2011] Hanlen, L. W., Smith, D. B., and Lamahewa, T. A. (2011). A new look at the
body area network channel model. In Europe. Conf. Ant. Prop.
[Hanlen et al., 2009] Hanlen, L. W., Smith, D. B., Lewis, D., and Zhang, J. A. (2009). Key-sharing via
channel randomness in body area networks: Is everyday movement suﬃcient? In Bodynets.
[Hao et al., 2006] Hao, Y., Alomainy, A., Zhao, Y., Parini, C., Nechayev, Y., Hall, P., and Constantinou,
C. (2006). Statistical and deterministic modelling of radio propagation channels in wban at 2.45 ghz.
In Antennas and Propagation Society International Symposium 2006, IEEE, pages 2169–2172.
[Islam and Kwak, 2010] Islam, S. M. R. and Kwak, K. S. (2010). A comprehensive study of channel
estimation for WBAN-based healthcare systems: Feasibility of using multiband UWB. J Med Syst.
[Jung et al., 2008] Jung, J. W., Kailas, A., Ingram, M. A., and Popovici, E. M. (2008). An evaluation
of cooperative transmission considering practical energy models and passive reception. In Intl. Symp.
App. Sci. Bio-Med. Comm. Tech., Aalborg, Denmark.
[Katayama et al., 2008] Katayama, N., Takizawa, K., Aoyagi, T., Takada, J.-i., Li, H.-B., and Kohno, R.
(2008). Channel model on various frequency bands for wearable body area network. In Intl. Symp.


[Lamahewa et al., 2010] Lamahewa, T., Hanlen, L., Miniutti, D., Smith, D., Rodda, D., and Gilbert,
B. (2010). BAN sleeping channel: Implications for relays, IEEE 802.15-10-0306-00-0006. IEEE
submission.
[Miniutti et al., 2008] Miniutti, D., Hanlen, L. W., Smith, D. B., Zhang, J. A., Lewis, D., Rodda, D., and
Gilbert, B. (2008). Narrowband channel characterization for body area networks ID: 802.15.08.0421.
IEEE submission.
[Moulton et al., 2010] Moulton, B., Hanlen, L. W., Chen, J., Croucher, G., Mahendran, L., and Varis, A.
(2010). Body-area-network transmission power control using variable adaptive feedback periodicity. In
Aust. Commun. Theory Workshop AusCTW, pages 139–144.
[Nagaoka et al., 2004] Nagaoka, T., Watanabe, S., Sakurai, K., Kunieda, E., Watanabe, S., Taki,
M., and Yamanaka, Y. (2004). Development of realistic high-resolution whole-body voxel models
of Japanese adult males and females of average height and weight, and application of models to
radio-frequency electromagnetic-ﬁeld dosimetry. Physics in Medicine and Biology, 49:1.
[Price Waterhouse Coopers, 2010] Price Waterhouse Coopers (2010). Healthleaders media breakthoughs:
The impact of personalized medicine today. online http://www.healthleadersmedia.com/
breakthroughs/250079/The-Impact-of-Personalized-Medicine-Today.
[Smith et al., 2010a] Smith, D., Miniutti, D., Hanlen, L. W., Rodda, D., and Gilbert, B. (2010a).
Dynamic narrowband body area communications: Link-margin based performance analysis and
second-order temporal statistics. In IEEE Wireless Commun. Net. Conf., WCNC.
[Smith, 2008] Smith, D. B. (2008). Electromagnetic characterisation through and around human body by
simulation using SEMCAD X. Technical Report CRL-3282 http://www.nicta.com.au/research/
research_publications/show?id=1504, NICTA.
[Smith et al., 2011a] Smith, D. B., Hanlen, L. W., Miniutti, D., and Zhang, J. A. (2011a). Power


delay profiles for narrowband body area networks: Flat fading is reasonable. submitted 2010, see
[Smith et al., 2009a].
[Smith et al., 2008a] Smith, D. B., Hanlen, L. W., Miniutti, D., Zhang, J. A., Rodda, D., and Gilbert,
B. (2008a). Statistical characterization of the dynamic narrowband body area channel. In Intl. Symp.
[Smith et al., 2010b] Smith, D. B., Hanlen, L. W., Zhang, J. A., Miniutti, D., Rodda, D., and Gilbert,
B. (2010b). First and second-order statistical characterizations of the dynamic body-area propagation
channel of various bandwidths. Annals of Telecommunications.
[Smith et al., 2011b] Smith, D. B., Lamahewa, T. A., Hanlen, L. W., and Miniutti, D. (2011b). Simple
prediction-based power control for the on-body area communications channel. In IEEE Intl. Conf.
Commun., ICC.
[Smith et al., 2009a] Smith, D. B., Miniutti, D., Hanlen, L. W., Zhang, J. A., Rodda, D., and Gilbert, B.
(2009a). Power delay profiles for dynamic narrowband body area network channels ID: 802.15-09-0187.
IEEE submission.
[Smith et al., 2008b] Smith, D. B., Miniutti, D., Zhang, J. A., and Hanlen, L. W. (2008b). Matlab code
for generating BAN fading profile ID: 802.15-08-0850. IEEE submission.
[Smith et al., 2009b] Smith, D. B., Zhang, J. A., Hanlen, L. W., Miniutti, D., Rodda, D., and Gilbert, B.
(2009b). A simulator for the dynamic on-body area propagation channel. In IEEE Int. Symp. Antennas
& Propagation, Charleston, USA.
[Stuart et al., 2008] Stuart, E., Moh, M., and Moh, T.-S. (2008). Privacy and security in biomedical
applications of wireless sensor networks. In Intl. Symp. App. Sci. Bio-Med. Comm. Tech., Aalborg,
Denmark.


[Takizawa et al., 2008a] Takizawa, K., Aoyagi, T., Takada, J.-i., Katayama, N., Yekeh, K., Takehiko, Y.,
and Kohno, K. (2008a). Channel models for wireless body area networks. In Proc. 30th Annual Inter.
Conf. of the IEEE Engineering in Medicine and Biology Society (EMBS), pages 1549–1552, Vancouver,
BC.
[Takizawa et al., 2008b] Takizawa, K., Yazdandoost, K. Y., Aoyagi, T., Katayama, N., Takada, J.-i.,
Kobayashi, T., Li, H.-b., and Kohno, R. (2008b). Preliminary channel models for wearable WBAN, ID:
802.15-08-0155. IEEE submission.
[Tegart, 2010] Tegart, W. G. M. G. (2010). Smart technology for health longevity: Report of a
study by the Australian Academy of Technological Sciences and Engineering. Australian Academy of
Technological Sciences and Engineering.
[Timo et al., 2010] Timo, R. C., Blackmore, K. L., and Hanlen, L. W. (2010). Word-valued sources:
An ergodic theorem, an AEP, and the conservation of entropy. IEEE Trans. Inform. Theory,
56(7):3139–3148.
[Tselishchev et al., 2010] Tselishchev, Y., Boulis, A., and Libman, L. (2010). Experiences and lessons
from implementing a wireless sensor network MAC protocol in the Castalia simulator. In IEEE Wireless
Commun. Net. Conf., WCNC.
[Ullah et al., 2010] Ullah, S., Higgins, H., Braem, B., Latre, B., Blondia, C., Moerman, I., Saleem, S.,
Rahman, Z., and Kwak, K. S. (2010). A comprehensive survey of wireless body area networks : On
phy, mac, and network layers solutions. J Med Syst.
[Yazdandoost and Sayraﬁan-Pour, 2008] Yazdandoost, K. Y. and Sayraﬁan-Pour, K. (2008). Channel
model for body area network (BAN) ID:-802.15-08-0033. IEEE submission,.
[Zhang et al., 2009] Zhang, J. A., Smith, D. B., Hanlen, L. W., Miniutti, D., Rodda, D., and Gilbert, B.


(2009). Stability of narrowband dynamic body area channel. IEEE Antennas Wireless Propagat. Lett.,
8:53–56.


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