fila: f ine - grained i ndoor l ocalization kaishun wu, jiang xiao, youwen yi, min gao, and lionel...

FILA: FINE-GRAINED INDOOR LOCALIZATION

Kaishun Wu, Jiang Xiao, Youwen Yi, Min Gao, and Lionel M. Ni

INFOCOM 2012

- Sowhat 2012.5.21

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

MOTIVATION

WiFi-based indoor localization RSSI range-based localization

Multipath Variance of RSSIs – 5dB in 1 min at immobile receiver

Capable to eliminate multipath effect

OBJECTIVE

An alternative metric to RSSI

Stable

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

FOUNDATION OF FILA

OFDM

CSI

Orthogonal Frequency Division Multiplexing

Channel State Information

OFDM

Multicarrier modulation schemefor wideband wireless communication Modulate data on multiple subcarriers in different

frequencies Transmit simultaneously

CSI

Channel state/status information Fine-grained value from the PHY layer1. Describe how a signal propagate from TX to RX2. Represent combined effect of

scattering, fading and power decay with distance

Channel properties of each subcarrier

Amplitude Phase

SYSTEM ARCHITECTURE

CSI Processing

CalibrationLocation

Determination

CSI PROCESSINGTIME-DOMAIN MULTIPATH MITIGATION

802.11n bandwidth ~40MHz > coherence bandwidth resolvable reflections

1. IFFT – channel response in frequency time domain

2. Filter –keep 1st clustertruncation threshold = 50% of 1st peak

value3. FFT – channel response in time frequency

domain

CSI Processing

CalibrationLocation

Determination

CSI PROCESSINGFREQUENCY-DOMAIN FADING COMPENSATION

Prob. of simultaneous deep fading occurring on multiple uncorrelated fading envelopes> deep fading occurring on a single freq. system

∵ channel bandwidth of 802.11n > coherence bandwidth∴ freq.-selective fading across all subcarriers uncorrelated

Reduce the variance in CSIs owing to small scale factors

Weighted average

CSI Processing

CalibrationLocation

Determination

CALIBRATION

Relationship between CSIeff and distance

σ : environment factor@TX, gain of baseband to RF band@RX, gain of RF band to basebandantenna gain

n : path loss fading exponent Fast training algorithm

1. 2 anchors for training2. Another anchor for testing

CSI Processing

CalibrationLocation

Determination

LOCATION DETERMINATION

1. APs’ coordinate info. from network layer2. Distance between AP/object

Effective CSI Refined radio propagation model

Trilateration!

CSI Processing

CalibrationLocation

Determination

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

HARDWARE CONFIGURATION

AP : TP-LINK TL-WR941ND router @ 2.4~2.4835GHz

Receiver: HP laptop with 2.4GHz dual-core CPU

Intel WiFi Link 5300 802.11n NICsModified driver to collecting CSI values from

NICsPlaced on a plastic cart

EXPERIMENTAL SCENARIOS

1. Chamber 3m x 4m Ideal free space indoor environment

(only LOS signal exist without multipath reflections)

2. Research laboratory 5m x 8m 3 APs Weekday afternoon

(students seating or walking around)

EXPERIMENTAL SCENARIOS

3. Lecture theatre 20m x 20m

4. Corridor 32.5m x 10m Cover corridors, rooms and cubicles Impact of the absence of LOS APs

ROBUSTNESS OF THE REFINED MODAL

TEMPORAL STABILITY OF CSI

DISTANCE DETERMINATION ACCURACY

ChamberResearch laboratoryLecture theatre

10 different locations

Positions with serious multipath effect –Accuracy: FILA > RSSI-based by 10 times

Mean distance error

LOCALIZATION ACCURACY IN SINGLE ROOM

Research laboratoryLecture theatre

90% - 1m/1.8m ; median - 0.45m/1.2m

LOCALIZATION ACCURACY IN MULTIPLE ROOMS

Corridor 6 APs in multiple rooms Experiment procedure

Offline trainingFix the position of the object at reference nodes collect APs’coordinates and CSI

Moving @ 1m/sCollect 20 CSIs and RSSIs at each position

Robust, median = 1.2m

LATENCY

Latency = calibration + determination phase Calibration

Data collectionAP transmit message every 0.8msCollect 20 CSIs20 * 0.8 = 16ms

Calibration processing = 2ms Determination

IFFT, FFT with wireless NICs= ignorable Signal processing + trilateration = 2ms

Total: 16ms + 2ms + 2ms = 20ms

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

DISCUSSION

CSI + fingerprint-based method more accurate localization

Leverage available multiple APs to improve accuracy

Implement FILA on smart phone

OUTLINE Introduction

System Design

Evaluation

Discussion

Conclusion

CONCLUSION

Design and implement FILA CSI with OFDM system

Compared to RSSI-Based in different scenarios Capable to deal with multipath effect

(time domain processing) Stable (freq. domain processing)

Disadvantage Unclear descriptions Comparison of single room/multiple room

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