An Experimental Study on IEEE 802.15.4 Multichannel Transmission to Improve RSSI-Based Service Performance

Andrea Bardella, Nicola Bui, Andrea Zanella and Michele Zorzi {bardella,bui,zanella,zorzi}@dei.unipd.it

Signet Research Group http://dgt.dei.unipd.it Special Interest Group on NEtworking & Telecommunications Department of Information Engineering, University of Padova, Italy

Outline

      motivation experimental setup wireless channel characterization multi-channel analysis communication protocol conclusion

Motivation

RSSI: Received Signal Strength Indicator

 Supported by most commercial RF transceivers  Largely used to assess channel quality and/or used in many localization algos for ranging  High variability

Goals:

 Experimental characterization of RSSI  Reducing RSSI variability by multi-channel samples harvesting

Outline

      motivation experimental setup wireless channel characterization multi-channel analysis communication protocol conclusion

Tmote Sky platform

  CC2420 transceiver 250 kbps @ 2.4 Ghz  external isotropic antenna (5 dBi) 5 MHz 3 MHz f m = 2405 + 5(m-11) Mhz m = 11, …, 26 2405 MHz 2480 MHz

Experimental setup

indoor & outdoor • N fixed nodes • 1 mobile node for each position for each couple of nodes for each channel 10 RSSI samples collected over time

Outline

      motivation experimental setup wireless channel characterization multi-channel analysis communication protocol conclusion

P rx

rx power (in [dBm]) 

P tx



Classical path loss model with Gaussian shadowing

path loss coefficient actual distance slow fading (shadowing)

K

 10  log 10 

d

/

d

0    fast fading   (

t

) tx power (in [dBm]) free space + shadowing constant (free space atten., antenna gain,…) reference distance

K

   2 20 log 10 (  / 4 

d

0 )  

N

( 0 ,   2 ) Least Mean Square criterion to estimate K and η

Parameter estimation

K dB η σ Ψ dB

Ch 11

-21.7 -21.6 -21.7 -22 2.03

4.8

Ch 12

2.03

4.4

Ch 13

2 4.5

Ch 14

1.98

4.4

···

··· ··· ···

Ch 23

-22.1 -22 2.01

4.1

Ch 24

1.96

4.3

Ch 25

-22 2 4.4

Ch 26

-21.9

1.98

4.2

For each couple of nodes and channel →10 RSSI samples collected over time

Ψ: fitting the normal pdf

indoor → σ Ψ = 4.6 dB outdoor → σ Ψ = 3.5 dB



Rx signal statistic

z

(

t

)



|

r

(

t

) |

 Weibull distributed [1]  

P rx



P tx



K

20log

10

(

z

(

t

))

 

20log

10

(

d P tx



K



/

d

0

) 20log

10

(

d

/

d

0

)

 Extreme Value distributed EV(θ location , θ scale )  [1] Sagias, N.C., Karagiannidis, G.K.: “Gaussian Class Multivariate Weibull Distribution: Theory and Applications in Fading Channels”, IEEE Trans. on Information Theory (Oct 2005)

Ψ: fitting the Extreme Value pdf

Indoor (Kullback-Leibler divergence) KL(emp,norm) = 0,0824 KL(emp,ev) = 0,0169 Outdoor (Kullback-Leibler divergence) KL(emp,norm) = 0,1371 KL(emp,ev) = 0,0146 Extreme Value distribution fits better the empirical data than the Normal distribution

Outline

      motivation experimental setup wireless channel characterization multi-channel analysis communication protocol conclusion

Narrowband fading

T ds



B

 1

u

(

t

 

n

) 

u

(

t

)    T ds B → → delay spread tx signal bandwidth u(t) → baseband signal  τ n → delay associated with the n-th component

r

(

t

)     

u

(

t

) τ 1 τ 2

e j

τ 3 2 

f m t

  

n N

  0

a n e



j



n

,

m

      t

Example: two rays



n

,

m

(

t

)  2 

f m



n

phase associated with n-th component d TX @ 2405[MHz] (m=11) TX @ 2455[MHz] (m=21) d 1 ' if δ 1 then and = ( d 1 ' + d 1 '' ) – d = 3[m] τ 1 = δ Δϕ = |ϕ 1 /v p 1,11 = 10[ns] – ϕ 1,21 | = π d 1 ''

# ch

1 4 8 16

Multichannel

Averaging RSSI samples over frequencies

σ Ψ dB

4.6

3.15

3.05

3

Outline

      motivation experimental setup wireless channel characterization multi-channel analysis communication protocol conclusion

Communication protocol

I’m in CH1! (Next CH2) Anybody in CH1? (Next CH2) I’m in CH1! (Next CH2) Everybody’s switching on CH2. Let’s follow them!

Inquirer

scheduled channels: default, NC(1), ..., NC(end) next channel = NC(1) start REQ T.O.

TX REQUEST next channel = NC(i) start REQ T.O.

TX REQUEST no REQ T.O.

elapsed no RX REPLY yes i>end yes no reply restart REQ T.O.

channel = next channel i = i+1 yes no END RX REPLY REQ T.O.

elapsed

Replier

IDLE channel = default IDLE channel = next channel no RX REPLY yes no RX REQUEST yes TX REPLY

Conclusion

   RSSI characterization parametric and statistical   statistic model validation RSSI variability mitigation RSSI averaged over time    RSSI averaged over frequency Communication protocol  Indoor & Outdoor 802.15.4 RSSI and LQI measurements http://telecom.dei.unipd.it/pages/read/59/

Questions?

THANK YOU FOR YOUR ATTENTION!

An Experimental Study on IEEE 802.15.4 Multichannel Transmission to Improve RSSI-Based Service Performance Andrea Bardella, Nicola Bui, Andrea Zanella and Michele Zorzi {bardella,bui,zanella,zorzi}@dei.unipd.it