Avoiding Multipath to Revive Inbuilding WiFi Localization Mobisys ’13 Souvik Sen, Jeongkeun Lee, Kyu-Han Kim, Paul Congdon Hewlett-Packard Labs Taehoon Ha, 2013.8.23 Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Outline Introduction CUPID : WiFi based Indoor Localization Estimating Distance Estimating Angle Evaluation Conclusion This is outline. First I will explain Instruction and next introduce CUPID system that is WIFI base Indoor Localization. While introducing CUID system, I will explain how CUPID estimate distance and angle in detail. Next I will show you result of evaluation. Lastly I will conclude this presentation Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Introduction Current Indoor Location Technologies Fingerprinting based War-driving is expensive Crowdsourcing is unattractive to user WiFi based Rely on distance or angle Highly susceptible to indoor multipath WiFi based approach is easier to adopt but Needs to distinguish direct path from multipath reflections Extensive interest in location-aware services has driven many novel indoor localization techniques. The accuracy of fingerprinting based technologies come at the cost of war-driving. And such war-driving is not one time cost because environment can change due to change in layouts and objects, or something. To reduce the overhead of war-driving, crowdsourcing can be used. But they remain unattractive because a lack of clear user incentive to share sensor and location information. Wifibased : it is posible to estimate distance using signal strenght(RSSI ), but RS냐 performs poorly because of multipath reflection Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Multipath Reflection RSSI = Direct path energy + Reflected path energy If we can accurately estimate the direct path, localization performance will improve significantly. Multimedia and Mobile Communications Laboratory

CUPID:WiFi based Indoor Localization Locates Clients using angle and distance Captures distance and angle more accurately Distance of direct path(Energy of direct path:EDP) Angle of direct path(ANDP) Multimedia and Mobile Communications Laboratory

Estimating EDP from CSI Inverse Fast Fourier Transformation Energy of Direct Path 푸리에변환: 시간영역의함수를주파수영역의함수로변환하는것. By an appropriate Inverse Fast Fourier Transformation , the frequency domain C S I can be translated time-domain power-delay profile(PDF) Energy of Reflected Path Multimedia and Mobile Communications Laboratory

Estimating Distance from EDP Estimate distance from EDP using the path loss equation Path loss exponent can vary between 2 and 4, depending on environment Incorrect path loss exponent an cause large errors in distance estimation Needs to determine the correct path loss exponent PR: EDP at AP P0: Measured EDP at a distance of 1 meter γ : Path loss exponent d : Distance PR = P0 - 10γlog(d) Gamma Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Path-loss exponent Path loss exponent depends on the likelihood of line-of-sight How can we determine line of sight? This is CDF of Path-loss exponent from 500 known locations. Almost Path loss exponent is distributed between 2 and 3. 2 path los exponent means transmitter and receiver is in the line-of-sight environment like corridor, on the other hand for complex indoor scenarios the path loss can go upto 4. since rs냐 does not capture any information regarding wireless propagation, choosing the right path-loss exponent for each received packet is difficult. Complex indoor environment Line-of-sight environment Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Line-of-sight factor LoS blockage may not affect reflected paths Energy of direct path RSSI = EDP + Reflected Energy 𝐿𝑜𝑆𝑓𝑎𝑐𝑡𝑜𝑟 𝑙𝑓𝑎𝑐𝑡𝑜𝑟 = 𝐸𝐷𝑃 𝑅𝑆𝑆𝐼 Multimedia and Mobile Communications Laboratory

Path-loss Exponent and lfactor 500 known locations, 1AP Linear relationship between path loss exponent and the lfactor 5 APs Relationship does not vary much over different environments This graph shows the EDP path loss exponent with increasing lfactor for transmissions to a single. From these measurements we can apply linear fitting to establish a relationship between path loss exponent and the lfactor. Sencond graph show that the path loss vs. lfactor relationship may not depent on a particular AP, or event environment the line are similar because lfactor directly escimates the environmental factor affecting the EDP 쎄 Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Estimating ANDP Angle-of-arrival(AoA) estimation AoA algorithm can identify multiple path and the output of MUSIC(AoA) is psudospectrum ∆𝑑= 𝜆/2sin⁡(𝜃) Δd 𝑝ℎ𝑎𝑠𝑒 𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 ∆𝜑 =2𝜋∆𝑑/𝜆 → 𝜃=arcsin⁡(∆𝜑/ 𝜋) Multimedia and Mobile Communications Laboratory

Angle Estimation Using Human Mobility Strongest Peak may not ANDP because of LoS blockage Then compare spectrum of different locations. When weaker path is consistent, then ANDP can be approximated. Multimedia and Mobile Communications Laboratory

AoA with dead reckoning Compute the physical distance between the two location by consulting her phone’s accelerometer and gyroscope Law of cosine 𝑐 2 = 𝑎 2 + 𝑏 2 −2𝑎𝑏𝑐𝑜𝑠𝛾 Multimedia and Mobile Communications Laboratory

AoA with dead reckoning Determine angle of each Find similar difference of two angle, then it is ANDP Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Side Ambiguity A linear antenna array can differentiate between signals from one arrays side only Identifies side by observing the user’s turn 3 antenna placed in straight line , can differentiate between signals from one arr Multimedia and Mobile Communications Laboratory

Leveraging Multiple APs Multiple Aps can estimate other Aps clients’ location by overhear transmission estimates across them using a weighted centroid approach di : distance 𝜃i : angle APi,x , APi, y : location of AP Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory CUPID Architecture Overall Architecture Changing Angle New Angle Distance Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Evaluation Methodology Client broadcasted 5 packets per second Receive the last 2 seconds; 10 packets Blue triangle is AP (5) Walk around for an hour Multimedia and Mobile Communications Laboratory

Distance estimation error Different APs Greatly reduces distance error Different number of known location used to find lfactor-to-mapping Even with a few known locations, perform well Multimedia and Mobile Communications Laboratory

Angle estimation error Different Aps Median angle estimation accuracy is 20° The error is mostly due to weak links. Needs to exclude for better performance Multimedia and Mobile Communications Laboratory

Performance using multiple APs Increasing number of Aps More APs, Smaller error Exising RSSI and AoA schemes Larger error than CUPID Multimedia and Mobile Communications Laboratory

Multimedia and Mobile Communications Laboratory Conclusion Multilateration and triangulation has traditionally suffered from the randomness of multipath reflections. We find that CSI information can accurately estimate the distance, and angle from only the direct path. CUPID identifies and harnesses only the direct path, avoiding the affect of multipath reflections. Multimedia and Mobile Communications Laboratory