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 Grouphttp://dgt.dei.unipd.it

Department of Information Engineering, University of Padova, Italy

Special Interest Group on

NEtworking & Telecommunications

Outline

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

Motivation

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

RSSI: Received Signal Strength IndicatorSupported by most commercial RF transceiversLargely used to assess channel quality and/or used in many localization algos for rangingHigh variability

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)

2405 MHz

2480 MHz

5 MHz 3 MHz

fm = 2405 + 5(m-11) Mhzm = 11, …, 26

Experimental setup

indoor & outdoor

• N fixed nodes• 1 mobile node

for each positionfor each couple of nodesfor each channel

10 RSSI samplescollected over time

Outline

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

Classical path loss model with Gaussian shadowing

)(/log10 010 tddKPP txrx

rx power (in [dBm])

tx power (in [dBm]) reference

distance

actual distance slow fading

(shadowing)

constant (free space atten., antenna gain,…)

path loss coefficient

free space +

shadowing ),0(

2)4/(log20

2

010

N

dK

fast fading

Least Mean Square criterion to estimate K and η

Parameter estimationCh 11 Ch 12 Ch 13 Ch 14 ··· Ch 23 Ch 24 Ch 25 Ch 26

K dB -21.7 -21.6 -21.7 -22 ··· -22.1 -22 -22 -21.9η 2.03 2.03 2 1.98 ··· 2.01 1.96 2 1.98σΨ dB 4.8 4.4 4.5 4.4 ··· 4.1 4.3 4.4 4.2For each couple of nodes and channel →10 RSSI samples collected over time

Ψ: fitting the normal pdf

indoor → σΨ = 4.6 dB outdoor → σΨ = 3.5 dB

Rx signal statistic

Extreme Value distributedEV(θlocation, θscale)

Weibull distributed [1]

[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)

z(t)| r(t) | Prx Ptx K 20log10(d /d0)20log10(z(t)) Ptx K 20log10(d /d0)

Ψ: fitting the Extreme Value pdf

Extreme Value distribution fits better the empirical data than the Normal distribution

Indoor (Kullback-Leibler divergence)

KL(emp,norm) = 0,0824KL(emp,ev) = 0,0169

Outdoor (Kullback-Leibler divergence)

KL(emp,norm) = 0,1371KL(emp,ev) = 0,0146

Outline

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

Narrowband fading

tam

plitu

deτ1

τ2 τ3

N

n

jn

tfj mnm eaetutr0

2 ,)()(

Tds → delay spread B → tx signal bandwidth u(t) → baseband signal τn → delay associated with the n-th component

1 BTds )()( tutu n

Example: two rays

d

d1' d1''

if δ1 = (d1' +d1'') – d = 3[m] then τ1 = δ1/vp = 10[ns]and Δϕ = |ϕ1,11 – ϕ1,21| = π

TX @ 2405[MHz] (m=11)TX @ 2455[MHz] (m=21)

nmmn ft 2)(, phase associated with n-th component

Multichannel

Averaging RSSI samples over frequencies

# ch σΨ dB1 4.6

4 3.15

8 3.05

16 3

Outline

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

Communication protocol

Anybody in CH1? (Next CH2)

I’m in CH1! (Next CH2)

I’m in CH1! (Next CH2)

Everybody’s switching on CH2. Let’s follow

them!

Inquirer

next channel = NC(1)start REQ T.O.TX REQUEST

RX REPLY

no reply restart REQ T.O.

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

channel = next channeli = i+1

scheduled channels: default, NC(1), ..., NC(end)

i>endno yes

yes

yes

REQ T.O.elapsed

noRX REPLYEND

no

REQ T.O.elapsed

Replier

IDLEchannel = default

TX REPLY

IDLEchannel = next channel

yes

noRX REQUESTRX REPLY

yes

no

Conclusion RSSI characterization parametric and statistical statistic model validation RSSI variability mitigation RSSI averaged over time RSSI averaged over frequency Communication protocol

simulationtools

Indoor & Outdoor 802.15.4 RSSI and LQI measurementshttp://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