Experimental comparison of RSSI-based localization
algorithms for indoor wireless sensor networks*
Giovanni Zanca, Francesco Zorzi, Andrea Zanella and Michele Zorzi
Signet research Group
Department of Information Engineering, University of Padova, Italy
{zancagio,zorzifra,zanella,zorzi}@dei.unipd.it
RealWSN08 Workshop
ACM Eurosys 2008
April 1st 2008
Glasgow - UK
*This work was partially supported by “Fondazione Cassa di Risparmio Padova e Rovigo” under the
project ``A large scale wireless sensor network for pervasive city-wide ambient intelligence.”
Outline
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Problem statement
Possible approaches
Wireless channel characterization
SOA review
Experimental setup
Results
Conclusions
RealWSN08 Workshop - Glasgow
April 1st 2008
Problem Statement
Position knowledge required by many WSN applications
Two main approaches
Nodes position hard written:
Motes capable of self-localizing:
• High deployment cost/time
• Easy deployment
• Not always feasible
• Need dedicated hardware to
achieve high precision
• Very accurate
RealWSN08 Workshop - Glasgow
April 1st 2008
Localization Approaches
Three main ranging approaches:
• Angle of Arrival
• Time of Arrival
• Received Signal Strength Indicator (RSSI)
Focus on RSSI:
• No specific Hardware required 
• Poor outdoor ranging performance 
• Very poor indoor ranging performance   
RealWSN08 Workshop - Glasgow
April 1st 2008
Indoor Radio Channel Characterization
Indoor Radio channel:
• Highly affected by log-normal shadowing
• Moderate path loss
RealWSN08 Workshop - Glasgow
April 1st 2008
Channel Model
• Path loss channel model: received power Pi @ distance di
environmental
constant
real transmitterreceiver distance
Shadowing
 di 
Pi dBm   PTx  K  10 log 10    i   t 
 d0 
Received
power
Transmitted
power
RealWSN08 Workshop - Glasgow
Path loss
coefficient
reference
distance
fast fading
April 1st 2008
Localization Algorithms
RSSI
samples
Anchor
positions
Localization
Algorithm
Range free approach
• Avoid ranging by direct comparison of RSSI
samples
• Independent of channel parameters
• Imperfect localization even with ideal channel
Range based approach
Mote
position
• Localization based on RSSI ranging
• Depend on channel parameters
•“Potential” perfect localization with ideal channel
RealWSN08 Workshop - Glasgow
April 1st 2008
Selected Localization Algorithms
Range based:
Range free:
• ROCRSSI
• Min-Max
– Computationally demanding
– Extremely simple
– Limited performance
• Multilateration
– Simple and scalable
– Highly affected by noisy samples
• Maximum Likelihood
– Complex
– Asymptotically optimum
RealWSN08 Workshop - Glasgow
April 1st 2008
Mote Platform: EyesIFX V2
• MSP430 MCU 4 MHz
• 10 KB RAM
• 48 KB ROM
• USB interface
• Infineon TDA5250 transceiver
• 900 MHz narrowband FSK
• External omni-directional antenna
RealWSN08 Workshop - Glasgow
April 1st 2008
Experimental Testbeds
Testbed #1
Testbed #2
=1.64
=1.51
s=6.82 dB
s=6.34 dB
RealWSN08 Workshop - Glasgow
April 1st 2008
Results – Mean Error
• Localization error remains quite high
• ML benefits from increasing the number of beacons, unlikely MinMax, ROCRSSI, Multilateration
• Better performance in testbed 2 due to smaller distance to the closest
beacon
RealWSN08 Workshop - Glasgow
April 1st 2008
Results – Error CDF
• Min-Max performance
does not improve by
adding beacons
• Localization error is
confined within a rather
narrow range around 4
meters
• ML improves
performance, though
errors are distributed
over a wide range
RealWSN08 Workshop - Glasgow
April 1st 2008
Conclusions
• ML yields better performance than the others with more than 6-7
beacons
• Multilateration is much simpler but shows very low performance
• ROCRSSI also achieves low performance but it is independent of
channel parameters
• Min-Max is extremely simple but tends to localize nodes in the
center of the area
• RSSI ranging is very unreliable and does not appear suitable for
indoor localization
RealWSN08 Workshop - Glasgow
April 1st 2008
Experimental comparison of RSSI-based localization
algorithms for indoor wireless sensor networks*
Giovanni Zanca, Francesco Zorzi, Andrea Zanella and Michele Zorzi
Signet research Group
Department of Information Engineering, University of Padova, Italy
{zancagio,zorzifra,zanella,zorzi}@dei.unipd.it
RealWSN08 Workshop
ACM Eurosys 2008
April 1st 2008
Glasgow - UK
*This work was partially supported by “Fondazione Cassa di Risparmio Padova e Rovigo” under the
project ``A large scale wireless sensor network for pervasive city-wide ambient intelligence.”