From wbell@CS.Cornell.EDU Mon Oct 29 20:59:57 2001 Return-Path: <wbell@CS.Cornell.EDU> Received: from postoffice.mail.cornell.edu (postoffice.mail.cornell.edu [132.236.56.7]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9U1xto21491 for <egs@cs.cornell.edu>; Mon, 29 Oct 2001 20:59:56 -0500 (EST) Received: from dhcp-190.rover.cornell.edu (dhcp-190.rover.cornell.edu [128.84.24.190]) by postoffice.mail.cornell.edu (8.9.3/8.9.3) with ESMTP id UAA06958 for <egs@cs.cornell.edu>; Mon, 29 Oct 2001 20:59:54 -0500 (EST) Subject: 615 PAPER #40 From: Walter Bell <wbell@CS.Cornell.EDU> To: egs@CS.Cornell.EDU Content-Type: text/plain Content-Transfer-Encoding: 7bit X-Mailer: Evolution/0.16.99+cvs.2001.10.18.15.19 (Preview Release) Date: 29 Oct 2001 20:59:32 -0500 Message-Id: <1004407194.1130.18.camel@brute> Mime-Version: 1.0 40) RADAR: An In-Building RF-Based User Location and Tracking System RADAR is an analysis of the positional information that can be determined from triangulating a client's position from two or more inexpensive wireless base stations. The goal is to use the location information from these available and inexpensive devices to provide user location data and tracking for location aware services and applications. The insight is that most location aware applications do not require positional applications on the order of precision of inches, but just on the order of the size of a room. Their intuition is that reception signal strengths of beacon packets from wireless base stations are stable enough to provide approximate location information. They first examine the problem via empirical means; they choose several points throughout the environment and determine the signal strength of each base station. From these sample points, they can approximate a users location in real time based on the observed signal strengths of the user. The empirical study yields good results, as user's positions can be determined to within a few meters. This is a promising solution for low cost location based systems. The problem with the empirical system is that it requires a large amount of setup overhead. One would prefer a non-calibrated system instead of the highly calibrated empirical system. In order to improve on the empirical system, they attempt to model the system as one of radio propagation, and attempt to find a good propagation model that models indoor environments well. Using the Floor Attenuation Model they found a good amount of accuracy without much complexity. The floor attenuation model accounts for large-scale path loss and includes an attenuation factor for building floors and helps mask the effects of obstacles between the sender and the receiver. From this model, they empirically determined the constants for their radios and found this model to be similar to the empirical model in precision, but with significantly less setup overhead. This paper was very encouraging; it implies that with commonly available hardware we can build location aware applications without much added complexity. Their results do imply that most wireless driver interfaces should provide signal strength information up to the driver user such that these methods can be used, which most wireless drivers do not. From gleason@CS.Cornell.EDU Tue Oct 30 03:29:49 2001 Return-Path: <gleason@CS.Cornell.EDU> Received: from postoffice2.mail.cornell.edu (postoffice2.mail.cornell.edu [132.236.56.10]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9U8Tlo01366 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 03:29:47 -0500 (EST) Received: from cypher.cs.cornell.edu (dhcp-147.rover.cornell.edu [128.84.24.147]) by postoffice2.mail.cornell.edu (8.9.3/8.9.3) with ESMTP id DAA00176 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 03:29:45 -0500 (EST) Message-Id: <5.0.2.1.2.20011030031648.00b07d10@postoffice.mail.cornell.edu> X-Sender: gleason@pop.cs.cornell.edu X-Mailer: QUALCOMM Windows Eudora Version 5.0.2 Date: Tue, 30 Oct 2001 03:29:32 -0500 To: egs@CS.Cornell.EDU From: Sunny Gleason <gleason@CS.Cornell.EDU> Subject: 615 PAPER #40 Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii"; format=flowed 40) RADAR: An In-Building RF-Based User Location and Tracking System Despite their lack of originality in naming their project, the system outlined by Bahl and Padmanabhan is indeed an exciting application of radio frequency signals for determining the location of a single user in an indoor setting. A couple of notable ideas that this paper presents: 1) Existing wireless LAN hardware has sufficient capabilities for deploying a user tracking system 2) The directionality of RF LAN equipment must be taken into account when computing distance information 3) A theoretical model of RF propagation can obtain comparable results to an empirical method The authors have developed a user tracking system; Read: a system for tracking *one* user. It is highly questionable whether this system would work for any reasonable number of users, given the wide variation in traffic that 802.11 networks could experience. I tend to doubt the utility of 802.11 signal strength as an indication of anything. Microwave ovens and 2.4ghz cordless phones are two instant headaches for this system. The directionality of antennae in 802.11 pcmcia cards is a useful result. It is interesting that they were able to find a theoretical model that fit their building's RF absorption signature. But, in general, is it really possible to gain useful effects by considering only line-of-sight propagation effects? From papadp@ece.cornell.edu Tue Oct 30 09:46:58 2001 Return-Path: <papadp@ece.cornell.edu> Received: from memphis.ece.cornell.edu (memphis.ece.cornell.edu [128.84.81.8]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UEkvo02203 for <egs@CS.Cornell.EDU>; Tue, 30 Oct 2001 09:46:57 -0500 (EST) Received: from photon (photon.ece.cornell.edu [128.84.239.166]) by memphis.ece.cornell.edu (8.11.6/8.11.2) with ESMTP id f9UEknk01199; Tue, 30 Oct 2001 09:46:49 -0500 Date: Tue, 30 Oct 2001 09:51:04 -0500 (EST) From: "Panagiotis (Panos) Papadimitratos" <papadp@ece.cornell.edu> To: Emin Gun Sirer <egs@CS.Cornell.EDU> cc: Panagiotis Papadimitratos <papadp@ece.cornell.edu> Subject: 615 PAPER 40 Message-ID: <Pine.LNX.4.21.0110300911170.23987-100000@photon.ece.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII Review of: "RADAR: An In-Building RF-based User Location and Tracking System," by P. Bahl, V.N. Padmanabhan Panagiotis Papadimitratos papadp@ece.cornell.edu The proposed system is capable of locating and tracking users (i.e., their portable devices) inside buildings. Unlike its predecessors that were based on IR technology, RADAR relies on singal strength measurements and Wireless LAN COTS, thus reducing the deployment cost. The basic idea is that the measured (at the mobile node) strength of signals is a function of the mobile node's location and more than one values measured from different access points (AP's) can be used to infer an accurate user location. First, given a set of BS's, a Radio Map of the space has to be created; the measurements of the received beacon from each AP within range are recorded along with the exact location coordinates, or in conjunction with a inner space RF propagation model. Should a mobile node wish to determine its position, it looks up the database to determine the closest signal tuple to the actual measurement and determine the location. The underlying method is triangulation, i.e., the determination of the direction of a received RF signal given at least two known points/receivers or the other way around in RADAR's case (the mobile knows where the AP's are and receives two or more signals). The problems with this approach are the possible estimation errors and shortcomings with the user tracking, i.e., the continuous update of the location of a mobile node. The basic limitation lies in that RF measurements are highly dependent on the ambient transmissions, which may dynamically change, rendering the Radio Map inconsistent (e.g., contrast the collection of measurements with a single RADAR-enabled node to the operational system with numerous stations present). Moreover, the issue of mobile nodes' location tracking has inherent difficulties, due to the limited number of measurements received by a certain AP. A more accurate estimation method is needed in order to remove ambiguities of location, given a history of measurements; that of course would require some modeling of the mobility pattern, and could draw from works relevant to cellular mobile systems. From eyh5@ee.cornell.edu Tue Oct 30 10:00:14 2001 Return-Path: <eyh5@ee.cornell.edu> Received: from memphis.ece.cornell.edu (memphis.ece.cornell.edu [128.84.81.8]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UF0Do03750 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 10:00:13 -0500 (EST) Received: from james (james.ee.cornell.edu [128.84.236.65]) by memphis.ece.cornell.edu (8.11.6/8.11.2) with ESMTP id f9UF06k01630 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 10:00:06 -0500 Date: Tue, 30 Oct 2001 09:58:41 -0500 (EST) From: Edward Hua <eyh5@ece.cornell.edu> To: egs@CS.Cornell.EDU Subject: 615 Paper 40 Message-ID: <Pine.GSO.4.21.0110300958210.1227-100000@james.ee.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII RADAR: An Inbuilding RF-based User Location and Tracking System Paramvir Bahl and Venkata N. Padmanabhan This paper introuduces RADAR, a RF-based system for locating and tracking users inside a building. The basic idea of RADAR is it uses both the measured and computed signal strength information from multiple receiver locations to triangulate a user's coordinates. In the authors' experiment with RADAR, which is carried out on a floor of a building with three testing base stations (BSs) that are equipped with RADAR, one piece of information that must be learned a priori is the coordinates of the three BSs as well as the coordinates of each room on the floor. In evaluating the performance of the RADAR system, the authors compare the data obtained by the empirical method with two other methods: random selection and strongest bast station selection. The results show that the empirical method fares better in correctly estimating the user location than the other two methods. In order to reduce the dependence on the empirical data gathered in real-time, a radio propagation model is proposed that takes advantage of tehoretically-computed signal strength data, whose operation can be performed off-line. This alternative method removes some of the complexity inherent in the empirical method, and its performance suggests that although there is a little suffering in the obtained data accuracy compared with the empirical method, it is not significant enough and can be fully justified by the amount of computational power and time saved from the latter. In the experiment, only one user is studied whose location and movements are located and tracked. There are no results presented to show how well RADAR performs with multiple users. One of the concerns is the interference due to signal strenth measured from a neighboring user that is mistakenly used to compute the location of the intended user. This concern is essential in addressing the capacity question. That is, how may users a network of RADAR-equipped BSs may serve to provide sufficient location information. This is not discussed in the paper. From avneesh@csl.cornell.edu Tue Oct 30 11:03:55 2001 Return-Path: <avneesh@csl.cornell.edu> Received: from capricorn.ds.csl.cornell.edu (capricorn.csl.cornell.edu [132.236.71.92]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UG3so14335 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 11:03:54 -0500 (EST) content-class: urn:content-classes:message Subject: 615 Paper 40 MIME-Version: 1.0 Content-Type: text/plain; charset="iso-8859-1" Date: Tue, 30 Oct 2001 11:05:25 -0500 Message-ID: <97C142C1212ED545B0023A177F5349C4053B22@capricorn.ds.csl.cornell.edu> X-MimeOLE: Produced By Microsoft Exchange V6.0.4712.0 X-MS-Has-Attach: X-MS-TNEF-Correlator: Thread-Topic: 615 Paper 40 Thread-Index: AcFhXK+4MQLCIPQQSo+/LL6SvzHiUg== From: "Avneesh Bhatnagar" <avneesh@csl.cornell.edu> To: <egs@CS.Cornell.EDU> Content-Transfer-Encoding: 8bit X-MIME-Autoconverted: from quoted-printable to 8bit by sundial.cs.cornell.edu id f9UG3so14335 RADAR: An in-Building RF-based User Location and Tracking service The RADAR system provides location service, based upon RF signal strength received from nodes within an RF data network. The RF signal strength of a transmitter is looked up in a signal strength database to obtain the accurate transmitter position. The main technique used here is triangulation based upon measured signal strength from multiple receivers. The authors present results based upon an emperical evaluation and a random method and strongest bast station method. The emperical method gives the best results. This is however aided by an offline process which builds a data base of signal strength at a set of fixed receivers. This data base is then looked up for accurate location discovery. The problems that are faced with this technique are that RF signals are affected by ambient signals and mobility might involve decrease in accuracy. It would have been helpful to see some results with more than one user which would bring into light another aspect of the system, i.e how scalable it is. From daehyun@csl.cornell.edu Tue Oct 30 11:10:44 2001 Return-Path: <daehyun@csl.cornell.edu> Received: from wilkes.csl.cornell.edu (wilkes.csl.cornell.edu [132.236.71.69]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UGAgo15991 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 11:10:42 -0500 (EST) Received: (from daehyun@localhost) by wilkes.csl.cornell.edu (8.9.3/8.9.2) id LAA26163 for egs@cs.cornell.edu; Tue, 30 Oct 2001 11:10:37 -0500 (EST) (envelope-from daehyun) From: Daehyun Kim <daehyun@csl.cornell.edu> Message-Id: <200110301610.LAA26163@wilkes.csl.cornell.edu> Subject: 615 PAPER 40 To: egs@CS.Cornell.EDU Date: Tue, 30 Oct 2001 11:10:37 -0500 (EST) X-Mailer: ELM [version 2.4ME+ PL54 (25)] MIME-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit This paper presented a location support system called RADAR. RADAR is a radio-frequency based system for locating and tracking users inside building. RADAR uses the triangulation technique. Multiple receivers gather user signal and triangulate the user's coordinates. They use both empirically and theoretically computed signal strength information. They placed three base stations which is equipped with a wireless adaptor. Mobile hosts broadcast packets periodically. Then, base stations record signal strength information and determine the location that best matches the observed signal strength data by triangulation. The algorithm is as follows; 1. Summarize the signal strength samples using the sample mean. 2. Determine the location and orientation that match a given signal strength form 1. 3. compare multiple locations form 2 and pick the one that best match the observed signal strength. They named their technique as Nearest Neighbor in Signal Space (NNSS). Their experiments showed that a few meters of precision. I think RADAR is better than Cricket in several points. It does not require beacons spread through building and listeners on nodes, so it does not cost extra equipments. And small number of centralized base stations might be easier to maintain than lots of beacons. The privacy problem can also be solved if user nodes compute the location instead of the base stations. Of cause, there are also shortcomings. For the accurate location detection, RF measurement should be performed. And scalability might be worse than Cricket. From ranveer@CS.Cornell.EDU Tue Oct 30 11:26:12 2001 Return-Path: <ranveer@CS.Cornell.EDU> Received: from exchange.cs.cornell.edu (exchange.cs.cornell.edu [128.84.97.8]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UGQAo18876 for <egs@popsrv.cs.cornell.edu>; Tue, 30 Oct 2001 11:26:10 -0500 (EST) content-class: urn:content-classes:message MIME-Version: 1.0 Content-Type: text/plain; charset="utf-8" X-MimeOLE: Produced By Microsoft Exchange V6.0.4712.0 Subject: 615 PAPER 40 Date: Tue, 30 Oct 2001 11:26:10 -0500 Message-ID: <706871B20764CD449DB0E8E3D81C4D430213A7BD@opus.cs.cornell.edu> X-MS-Has-Attach: X-MS-TNEF-Correlator: Thread-Topic: 615 PAPER 40 Thread-Index: AcFhX5Wu8UsOVk+pQXO68WDy//TJnA== From: "Ranveer Chandra" <ranveer@CS.Cornell.EDU> To: "Emin Gun Sirer" <egs@CS.Cornell.EDU> Content-Transfer-Encoding: 8bit X-MIME-Autoconverted: from base64 to 8bit by sundial.cs.cornell.edu id f9UGQAo18876 RADAR: An In-Building RF-based User Location and Tracking System This work presents a novel scheme for location tracking without the use of extra hardware. Signal Strength measures at base stations coupled with triangulation techniques are used to determine a user's location. In the warming off-line phase, data is collected at the base stations for a number of locations in the coverage area. Signal strength in the real-time phase is used to determine the exact user location. Overall, RADAR does a great job in user location and tracking. It is a follow-up work to the active badge system and a precursor to the BAT system. It is the first system to move away from IR and use RF signal strength to come up with reasonably accurate location information. No extra hardware is required in this system and this feature greatly adds to the ease in deployability of RADAR. RADAR should not be compared with Cricket because of different goals of location tracking compared to location support of Cricket. A better comparison would be with the BAT system. RADAR compromises accuracy compared to the BAT system for a lesser cost of deployment. However, there are other features of RADAR which need more work. Firstly, the warming or training in the off-line phase could be a long and painful process for accurate real-time information. An alternative theoretical model has been worked on, but it needs much more work to give good results. Secondly, and more importantly, RADAR would give incorrect results in the presence of power optimization features. It works as long as all the mobile nodes transmit with the same power throughout the coverage area, and this assumption rules out the possibility of any power optimization. From ramasv@CS.Cornell.EDU Tue Oct 30 11:29:07 2001 Return-Path: <ramasv@CS.Cornell.EDU> Received: from exchange.cs.cornell.edu (exchange.cs.cornell.edu [128.84.97.8]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UGT6o19474 for <egs@popsrv.cs.cornell.edu>; Tue, 30 Oct 2001 11:29:06 -0500 (EST) content-class: urn:content-classes:message MIME-Version: 1.0 Content-Type: text/plain; charset="iso-8859-1" X-MimeOLE: Produced By Microsoft Exchange V6.0.4712.0 Subject: cs615 PAPER 40 Date: Tue, 30 Oct 2001 11:29:05 -0500 Message-ID: <706871B20764CD449DB0E8E3D81C4D4301E7F283@opus.cs.cornell.edu> X-MS-Has-Attach: X-MS-TNEF-Correlator: Thread-Topic: cs615 PAPER 40 Thread-Index: AcFhX/4Y03pfWNBtR9mNBaY5jMlalQ== From: "Venu Ramasubramanian" <ramasv@CS.Cornell.EDU> To: "Emin Gun Sirer" <egs@CS.Cornell.EDU> Content-Transfer-Encoding: 8bit X-MIME-Autoconverted: from quoted-printable to 8bit by sundial.cs.cornell.edu id f9UGT6o19474 RADAR: An In-Building User Location and Tracking System RADAR is a location traking system that uses comparision of signal stength to pre-determined emperical values and triangulation to locate and track users in any environment. This system depends on a few (3) centralized servers that stores the emperical information and compares upon request by a node. The emperical values are pre-determined by measuring signal strngths at different location in the environment. An interesting point made by the paper relates to variation in signal strength due to a change in direction of transmission or reception. Whenever a location is needed, the signal strength seen at that point is compared with the table of pre-determined values. Several closest distances from the the signal source are considered. The same is done for 3 different signal sources. A triangulation is then employed to locate the correct location based on the distance from these sources. In my opinion comparing with a pre-determined values has several drawbacks. First of all, changes in the environment such as new noise sources (microwave), different temperature could affect the signal strenght values. Further it is a big pain to walk across the entire environment in advance and take sample measurements. An alternative explored in the paper is to use path propagation models to estimate distances. But path propagation models are not accurate and may not be realistic for many environments. Even though this paper claims that they could successfully use the WAF model, it may still not be applicatble in a different environment say with a metal-lined wall. From teifel@csl.cornell.edu Tue Oct 30 11:41:00 2001 Return-Path: <teifel@csl.cornell.edu> Received: from disney.csl.cornell.edu (disney.csl.cornell.edu [132.236.71.87]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UGewo22102 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 11:40:58 -0500 (EST) Received: from localhost (teifel@localhost) by disney.csl.cornell.edu (8.11.3/8.9.2) with ESMTP id f9UGeri78485 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 11:40:53 -0500 (EST) (envelope-from teifel@disney.csl.cornell.edu) X-Authentication-Warning: disney.csl.cornell.edu: teifel owned process doing -bs Date: Tue, 30 Oct 2001 11:40:53 -0500 (EST) From: "John R. Teifel" <teifel@csl.cornell.edu> To: <egs@CS.Cornell.EDU> Subject: 615 PAPER 40 Message-ID: <20011030114009.A65596-100000@disney.csl.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII RADAR: This paper describes a location-aware system called RADAR, a RF based system for locating and tracking users inside buildings. This system uses base stations to record, process, and track signal strength from mobile nodes. This allows the system to accurately track (within a few meters) mobile nodes--hence allowing the system to provide location-dependent services. Their experimental setup consisted of a few base stations (running FreeBSD of course, rather than the weaker Linux) and mobile nodes consisting of laptops. The targeted domain for RADAR is in-building, RF domain tracking. They use an empirical method and a signal propagation model for calculating a user's location. This paper was a good start at attempting to provide location-dependent services for mobile computing networks. Tracking mobile nodes using this base-station scheme is a simple, yet effective idea and is practical and efficient to implement with current technology--and I expect any such future location-dependent servicing for mobile nodes will look like the setup in this paper. From viran@csl.cornell.edu Tue Oct 30 11:44:50 2001 Return-Path: <viran@csl.cornell.edu> Received: from moore.csl.cornell.edu (moore.csl.cornell.edu [132.236.71.83]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UGino22379 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 11:44:49 -0500 (EST) Received: from localhost (viran@localhost) by moore.csl.cornell.edu (8.11.3/8.9.2) with ESMTP id f9UGihq07062 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 11:44:44 -0500 (EST) (envelope-from viran@moore.csl.cornell.edu) X-Authentication-Warning: moore.csl.cornell.edu: viran owned process doing -bs Date: Tue, 30 Oct 2001 11:44:43 -0500 (EST) From: "Virantha N. Ekanayake" <viran@csl.cornell.edu> To: <egs@CS.Cornell.EDU> Subject: 615 Paper 40 Message-ID: <20011030114407.G6932-100000@moore.csl.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII RADAR is another in-building user location and tracking system, that is based purely on RF signal strength. The system consists of mobile hosts that broadcast pings to base stations that then triangulate the position of the mobile node. Unlike Cricket, this system relies on the nodes actively advertising their presence, thus removing any privacy even if the node is just passing through the environment without taking part in the network. The centralized tracking provides a single point of failure; however this does allow central monitoring of all users, if that is the required purpose of the system. Another downsideis that each node has much higher power consumption, since instead of just passively listening to beacons like in Cricket, they now actively broadcast signals constantly, alleviating any chance to go into a power saving mode. Another disadvantage lies in the need to take prior measurements of signal strength, thus reducing the flexibility of the system. From samar@ece.cornell.edu Tue Oct 30 12:09:28 2001 Return-Path: <samar@ece.cornell.edu> Received: from memphis.ece.cornell.edu (memphis.ece.cornell.edu [128.84.81.8]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UH9Ro26153 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 12:09:27 -0500 (EST) Received: from descartes (descartes.ee.cornell.edu [128.84.236.60]) by memphis.ece.cornell.edu (8.11.6/8.11.2) with ESMTP id f9UH9Jk05103 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 12:09:19 -0500 Date: Tue, 30 Oct 2001 12:08:28 -0500 (EST) From: Prince Samar <samar@ece.cornell.edu> X-Sender: samar@descartes.ee.cornell.edu To: egs@CS.Cornell.EDU Subject: 615 PAPER 40 Message-ID: <Pine.GSO.4.21.0110301208020.17228-100000@descartes.ee.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII 40) RADAR: An In-Building RF-based User Location and Tracking System This paper describes a radio frequency based system for locating and tracking users inside a building. RADAR depends on a few base-stations to record/transmit beacons to the mobile nodes. It is based on empirical strength measurements in the building as well as a simple propagation model for radio frequencies. The authors find that the empirical, signal strength measurements to later predict the location of the user is more effective than using the radio propagation model. RADAR uses the signal strength measurements at the multiple base-stations to triangulate the user's coordinates. The triangulation can be done based on empirically determined signal strengths or one based on a rather simple radio propagation model. In the former case, signal strength measurements (which are averaged) are done at many points which effectively cover the whole area along with the orientation of the user. Then a look-up table is maintained and a nearest neighbor in signal strength (NNSS) is found out using the Euclidean measure. Then this corresponding point is concluded to be the user's location. In the latter case, signal strength measurements are done at different locations to find out the parameters of a Wall Attenuation Factor (WAF) model of radio propagation. WAF is essentially a path loss exponent model with a corrective factor for attenuation due to walls. Then the location of the user is predicted based on the received signal strength. Both these models suffer from some limitations. Before setting up either of the two model at any place, a significant amount of measurements need to be performed to construct the data-set or to find the attenuation model parameters. This may need to be repeated every time a base station needs to be located. For the empirical data set, data needs to collected for multiple user orientations at each location. This severely limits the scalability of RADAR and may increase its cost. Furthermore, many base-stations may be needed as these signal strength values obtained may not be unique for all the locations. The author don't seem to have touched the issue of uniqueness of the signal strength at all (which probably wasn't a issue in their particular set-up). Also, the authors claim that the parameters for their wall attenuation propagation model are similar across base-stations have a lot to do with their particular physical location plan. This may not hold true if the surroundings of the base-stations (or even the user for that matter) are markedly different. Also I feel that the authors could have done better with their radio propagation model. The authors put the Rayleigh fading model, the Rician model and their "Wall Attenuation Factor" model at par, which is not technically correct as the first two are Multipath or short term fading models (which are used in conjunction with a long term or shadow fading model) and their WAF model is simply a long term fading model. From ashish@CS.Cornell.EDU Tue Oct 30 12:10:24 2001 Return-Path: <ashish@CS.Cornell.EDU> Received: from cucsloan4 (pit066.cs.cornell.edu [128.84.223.166]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with SMTP id f9UHAMo26238 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 12:10:22 -0500 (EST) Message-ID: <000f01c16165$c25f4820$a6df5480@cs.cornell.edu> From: "Ashish Motivala" <ashish@CS.Cornell.EDU> To: <egs@CS.Cornell.EDU> Subject: 615 PAPER #40 Date: Tue, 30 Oct 2001 12:10:21 -0500 MIME-Version: 1.0 Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Priority: 3 X-MSMail-Priority: Normal X-Mailer: Microsoft Outlook Express 6.00.2600.0000 X-MimeOLE: Produced By Microsoft MimeOLE V6.00.2600.0000 RADAR: An Inbuilding RF-based User Location and Tracking System Paramvir Bahl and Venkata N. Padmanabhan The paper introduces a simple and cost efficient way to identify user location by triangulating a the position from two or more wireless base stations. It uses Signal Strenght as a basis for its position match, on 70 points and 4 directions in the space. It determines the location by finding the Nearest Neighbor in the Search Space using lowest Euclidian Distance as their metric. They go on to suggest a number of methods to improve and get better position information I am unsure of the scalability this location detection scheme. Also using radio frequency, has it disadvantages, especially in terms of SS and SNR which will vary drastically everytime in put my taco in the microwave. I believe that using a couple of metrics together might help.Using machine learing to identify common locations a user might be in should as be benefitial as most users are more likely to be at a few places most of the time. ie A person's location distibution is also more likely to be Zipfian. From andre@CS.Cornell.EDU Tue Oct 30 13:02:31 2001 Return-Path: <andre@CS.Cornell.EDU> Received: from postoffice.mail.cornell.edu (postoffice.mail.cornell.edu [132.236.56.7]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UI2To04125; Tue, 30 Oct 2001 13:02:29 -0500 (EST) Received: from khaffy (d7b102.dialup.cornell.edu [128.253.157.102]) by postoffice.mail.cornell.edu (8.9.3/8.9.3) with ESMTP id NAA09018; Tue, 30 Oct 2001 13:02:27 -0500 (EST) Received: from andre by khaffy with local (Exim 3.31 #1 (Debian)) id 15yXd2-00007F-00; Tue, 30 Oct 2001 13:04:24 +0100 Date: Tue, 30 Oct 2001 13:04:24 +0100 From: =?iso-8859-1?Q?Andr=E9?= Allavena <andre@CS.Cornell.EDU> To: egs@CS.Cornell.EDU Cc: andre@CS.Cornell.EDU Subject: 615 PAPER 40 Message-ID: <20011030130424.B404@khaffy> Mime-Version: 1.0 Content-Type: text/plain; charset=iso-8859-1 Content-Disposition: inline Content-Transfer-Encoding: 8bit User-Agent: Mutt/1.3.20i Sender: =?iso-8859-1?Q?Andr=E9_Allavena?= <andre@CS.Cornell.EDU> RADAR, An In Buildinng RF User Location and Tracking System. In this paper, the author describe a location system using the following idea: there are bases stations which receive beacons from the user, and the set of coordiantes (base staion $i$, strength of the signal received at $i$) is then matched with a set of predetermined points for which we know the actual physical location. Put it another way: we know a set of physical point and their values. Given a set of values, we look to find the point with the closest values, and assume we are near this physical location. The set of reference points can be constucted by hand (you input were you are as well as signal strenght). They call this the empirical model. Another way to do it is to know the propagation model (the attenuation model), to be able to take into account the walls, and have a one-to-one mapping between signal strength and distance from the station. This gives slightly less good results. In both cases, the user direction has some importance, and not knowing it decreases the perofmances. In tsead of picking the best match when looking for the location but averaging on the few best matches can improve the location. There system needs the space to be covrered by at least two base stations. The "empirical model" can be quite long to set up. Regarding the propagation model, they needeed to mesure the wall attenuation. There could be some plave where the walls are heterogeneous, and there model might be somehow wrong. Also, I am wondring if the structure of the building (steel vs concrete or reinforced concrete) wouldmake a difference (the quantity of steel and its alignement will be quite different). What about different floors? It might be straightfowrad to add a 3rd dimension, maybe not -- Andr� Allavena (local) 154 A Valentine Place �cole Centrale Paris (France) Ithaca NY 14850 USA Cornell University (NY) (permanent) 879 Route de Beausoleil PhD in Computer Science 06320 La Turbie FRANCE From jcb35@cornell.edu Tue Oct 30 14:01:21 2001 Return-Path: <jcb35@cornell.edu> Received: from travelers.mail.cornell.edu (travelers.mail.cornell.edu [132.236.56.13]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UJ1Jo12070 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 14:01:19 -0500 (EST) Received: from travelers.mail.cornell.edu (travelers.mail.cornell.edu [132.236.56.13]) by travelers.mail.cornell.edu (8.9.3/8.9.3) with SMTP id OAA27243 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 14:01:13 -0500 (EST) From: jcb35@cornell.edu Date: Tue, 30 Oct 2001 14:01:13 -0500 (EST) X-Sender: jcb35@travelers.mail.cornell.edu To: egs@CS.Cornell.EDU Subject: 615 PAPER 40 Message-ID: <Pine.SOL.3.91.1011030130944.12409A-100000@travelers.mail.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII This paper evaluated a method of using triangulation over RF-based devices to track a mobile node's location. The RADAR system uses a method based on triangulation based on signal strength to approximate location. Their experiments were carried out on a floor with three base stations and one mobile laptop. By obtaining a tuple of the mean signal strength from a few base stations, they can try to accurately determine the location based on previous signal measurements by determining which tuple the measurements are "closest" to. They also store information about orientation, since the direction a wireless unit is facing can dramatically affect its signal. They mention the main limitation of their empirical model is that you must know the measurements of many of the tuples before you can be used. I could image this would not be reasonable for all cases. This method also seems highly dependent on the RF environment, since anything that would weaken a base station's signal could affect the location reading you are given. From gupta@CS.Cornell.EDU Tue Oct 30 14:24:50 2001 Return-Path: <gupta@CS.Cornell.EDU> Received: from ringding.cs.cornell.edu (ringding.cs.cornell.edu [128.84.96.109]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UJOno16102 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 14:24:49 -0500 (EST) From: Indranil Gupta <gupta@CS.Cornell.EDU> Received: (from gupta@localhost) by ringding.cs.cornell.edu (8.11.3/8.11.3/C-3.2) id f9UJOmh25177 for egs@cs.cornell.edu; Tue, 30 Oct 2001 14:24:49 -0500 (EST) Message-Id: <200110301924.f9UJOmh25177@ringding.cs.cornell.edu> Subject: 615 PAPER 40 To: egs@CS.Cornell.EDU Date: Tue, 30 Oct 2001 14:24:48 -0500 (EST) X-Mailer: ELM [version 2.5 PL3] MIME-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit RADAR: an in-building RF-based user location and tracking system, P. Bahl and V.N. Padmanabhan. Reviewer: Indranil Gupta This paper presents a location algorithm for tracking stationary or slow-moving mobile users. The algorithms basically work by using triangulation depending on the estimated distance to several base stations, calculated from signal strength information of beacons transmitted from the base stations. The radio propagation model attempts to account for signal attenuation due to distance and wall interference, the only possible major attenuation source within a building. The testing set-up maintains a set of 70 X 4 data points for 70 sample user locations in the buildings, each with four possible orientations. The location is found by a state space search among these data points. Multiple nearest neighboring data points can be used to average out a more accurate user location. Different orientations can be attempted to hone the space search. Comments: Users can have multiple orientations - four is a simplification. Is it possible that if the user's handheld is not in one of the standard four positions, the algorithms in the paper might deduce the wrong location ? Do the authors explain the exact state space search algorithm used ? If the number of data points is large (say 100000 X 4 instead of 70 X 4) and users are fairly mobile (restricting the time to do a state space search until the position changes again), a more efficient search algorithm would be needed. From gupta@CS.Cornell.EDU Tue Oct 30 14:25:07 2001 Return-Path: <gupta@CS.Cornell.EDU> Received: from ringding.cs.cornell.edu (ringding.cs.cornell.edu [128.84.96.109]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9UJP6o16149 for <egs@cs.cornell.edu>; Tue, 30 Oct 2001 14:25:06 -0500 (EST) From: Indranil Gupta <gupta@CS.Cornell.EDU> Received: (from gupta@localhost) by ringding.cs.cornell.edu (8.11.3/8.11.3/C-3.2) id f9UJP6r25185 for egs@cs.cornell.edu; Tue, 30 Oct 2001 14:25:06 -0500 (EST) Message-Id: <200110301925.f9UJP6r25185@ringding.cs.cornell.edu> Subject: 615 PAPER 40 To: egs@CS.Cornell.EDU Date: Tue, 30 Oct 2001 14:25:05 -0500 (EST) X-Mailer: ELM [version 2.5 PL3] MIME-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit GPS-less low cost outdoor localization for very small devices, N. Bulusu J. Heidemann and D. Estrin. Reviewer: Indranil Gupta This paper describes a very simple algorithm to estimate a user position - this is done by estimating distances from various beacons (by using a simplistic attenuation model), and estimating the position as the centroid. Experiments show that the theoretical error is close to that given by the authors' implementation. Comments: Signal strength differences across beacons, and interference are not considered while calculating the position. The errors are rather large (50 % probability for more than a 2 m error on a 10m quadrant - that's a 20% error with .5 probability). This is ostensibly due to the simplistic propagation model. What are the other arguments, besides simplicity of the algorithm, for using a central beacon (beacons) to measure the _absolute_ position of each user ? In an ad-hoc routing scenario, it is the _relative_ positions that matter more (it is ok for two neighboring handhelds to both measure their positions as 2 m s-w of their actual positions). This could call for a more localized location algorithm - one that does not require nodes to run through the entire database of data points whenever the beacon is used to estimate the user location. Beacons' data is used less frequently, perhaps periodically. But most of the location update is done only when the user or one of its neighbors moves - the protocol is more "reactive" in that sense. From haom@csl.cornell.edu Tue Oct 30 16:25:24 2001 Return-Path: <haom@csl.cornell.edu> Received: from mauchly.csl.cornell.edu (mauchly.csl.cornell.edu [132.236.71.68]) by sundial.cs.cornell.edu (8.11.3/8.11.3/M-3.7) with ESMTP id f9ULPMo13795 for <egs@CS.Cornell.EDU>; Tue, 30 Oct 2001 16:25:23 -0500 (EST) Received: from localhost (haom@localhost) by mauchly.csl.cornell.edu (8.9.3/8.9.2) with ESMTP id QAA24401 for <egs@CS.Cornell.EDU>; Tue, 30 Oct 2001 16:25:16 -0500 (EST) (envelope-from haom@mauchly.csl.cornell.edu) X-Authentication-Warning: mauchly.csl.cornell.edu: haom owned process doing -bs Date: Tue, 30 Oct 2001 16:25:16 -0500 (EST) From: Ming Hao <haom@csl.cornell.edu> To: Emin Gun Sirer <egs@CS.Cornell.EDU> Subject: 615 PAPER 40 In-Reply-To: <200110300148.f9U1mpm03163@zinger.cs.cornell.edu> Message-ID: <Pine.BSF.4.10.10110301624590.22630-100000@mauchly.csl.cornell.edu> MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII RADAR: An In-Building RF-based User Location and Tracking System by Paramvir Bahl and Venkata N. Padmanabhan themain idea of this paper is to complement the data networking capabilities of RF wireless LANs with accurate user location and tracking capabilities, thereby enhancing the value of such networks. personally, i think it is a very good approach by taking advantage of existing wireless LAN. the way it works is : 1. there are multiple stations which overlap the cover area. 2. the signal information of each location is collected off-line 3. for the real-time analysis, the nearest neighbor earch is used. the paper discusses the impact of orientation and multiple neighbors averaging and teh size of sampling locations. one of disdvantages of this scheme is that it requires the pre-training to collect the location-signal strength pair information. it is not flexible. above is the empirical model. there is also a Radio Propagation Model which does not need to pre-sample the location-signal strengh pair info. Rayleigh fading model, Rician distribution model and Floor Attenuation Factor propagation model. an adapted FAF, called WFA is proposed. the benefit of using WFA is that no much measurements are needed and parameters of model do not depend on the locations of base stations. comments. i still think the size of building mustbe very big in order to make location-aware service make sense. so it would better to for the paper to consider a larger building with more base stations. and each station can not cover the whole area. -ming Ming Hao PH.D Candidate, EE mh97@cornell.edu Cornell University Office: (607) 255-0817 Ithaca, NY 14853 http://www.ee.cornell.edu/~haom/