1 / 24

Advancing Wireless Link Signatures for Location Distinction

Advancing Wireless Link Signatures for Location Distinction. J. Zhang, M. H. Firooz, N. Patwari, S. K. Kasera MobiCom’ 08 Presenter: Yuan Song. Introduction. What we want to do: Detecting whether a transmitter is changing its location or not.

elise
Download Presentation

Advancing Wireless Link Signatures for Location Distinction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Advancing Wireless Link Signatures for Location Distinction J. Zhang, M. H. Firooz, N. Patwari, S. K. Kasera MobiCom’ 08 Presenter: Yuan Song

  2. Introduction • What we want to do: Detecting whether a transmitter is changing its location or not. • Unlike localization or location estimation, location distinction does not attempt to determine where a transmitter is • Useful in many applications, especially it can enforce physical security by identifying illegal transmitter

  3. Methodology • Basic Method Estimating Channel Impulse Response (CIR), called Signature of the channel,to checking whether multipath channel is changing or not. • Multipath CIR (time-variant channel)

  4. Methodology (cont.) • Multipath CIR (time-invariant channel) • Sending s(t), received signal r(t) will be • In frequency domain

  5. Methodology (cont.)Estimating methods • Two methods (used in existing papers related to location distinction and this paper) • 1 • 2 • Both need S(f) to be known in receiver • is nearly constant within the band

  6. Previous Work in Location Distinction1Multi Tone Probing • Signature • K carrier waves are simultaneously transmitted to the receiver • fk is separated by an amount greater than Channel Coherence Bandwidth, and thus each carrier wave is attenuated by the channel complex gain. • Signature of the Channel (nth recorded signature), in frequency domain • Based on the method

  7. Previous Work in Location Distinction (Cont.)1Multi Tone Probing • Metric (The paper also proposes a slightly modified version for enhancing detection stability) • the Nth multiple tone signature h(N) is compared with each previously measured signature in the history Hi,j using a measure called the correlation statistic • T(n) is the correlation of the nth and the Nth measurements

  8. Previous Work in Location Distinction 2Temporal CIR Signatures • Signature • Using sampled CIR, in time domain • Based on the method

  9. Previous Work in Location Distinction (Cont.)2Temporal CIR Signatures • Metric • the difference between the Nth signature h(N) and those in the history Hi,j is given as the minimum normalized Euclidean distance between the new signature and any signature in the history set.

  10. Comparison Between Two Previous Work • Cons of Multi Tone Probing the channel frequency response is sensitive to each multipath. An impulse in the time domain is a constant in the frequency domain, and thus a change to a single path may change the entire multiple tone link signature. • Temporal CIR signature use a time domain signature, and thus are more robust against small changes of channel. • Cons of Temporal CIR Signature Lack of phase information limits its ability in uniquely identifying links. • This paper addressed these two cons and made improvement. It proposes a new signature called complex temporal link signature

  11. Complex Temporal Signature • Signature • Slight modification to Temporal CIR Signature, “without taking the magnitude of each gain” • Contrast to Signature of Temporal CIR Signature • Special issues: Difficult to discriminate between channel response phase and oscillator drift, and thus some phase changes in the link signature have nothing to do with any changes in the link. • Solution gived.

  12. Complex Temporal Signature • Metric (same as Temporal CIR Signature)

  13. Performance EvaluationFramework of Location Distinction • 1For a given transmitter i and a receiver j, a history of N-1 link signatures is measured and stored • 2 The Nth signature h(N) at j from an unknown transmitter in the neighborhood of j is then taken, and an evaluation criterion ei,j = sigEval(h(N); Hi,j ) is computed. • 3ei,j is compared to a threshold • 4When ei,j does not satisfy certain condional relationship with threshold, the new signature is determined to be from the same transmitter, i.e. h(N) = h(N)i,j, and we include it in history of H. For constant memory usage, the oldest measurement in His then discarded. The algorithm returns to step 2 until enough measurements have been collected

  14. Performance EvaluationFramework of Location Distinction (Cont.) • 5 Final Step (Principles used to compare the algorithms) • We first define the null and alternate hypotheses: • Then we treat ei,j as a random variable and define

  15. Performance EvaluationMultiple Tone and Temporal CIR

  16. Performance EvaluationMultiple Tone, Temporal CIR and Complex Temporal CIR

  17. Temporal Behavior of Link SignaturesIntroduction • The multipath characteristics of a link can change with time. A link can thus be in different distinct states. • A location distinction mechanism that does not consider the temporal changes in link behavior can significantly increase the probability of false alarms. • The paper propose a Markov Model to further decrease the probability of false alarm

  18. Temporal Behavior of Link SignaturesIntuition 1 • Using non-linear dimensionality reduction (a method in Statistics to visualize high dimensional data) to reduce the 100 dimension vectors to just 1-2 dimensions. • Below is a 2-D embedding plotted with one set of 333 complex link signature measurements.

  19. Temporal Behavior of Link SignaturesIntuition • Two States • With 1D embedding of Isomap algorithm, from the total number of state changes, and the number of times we are in a state, we calculate the state transition probabilities and the limiting probabilities of the Markov chain

  20. Temporal Behavior of Link SignaturesMarkov Model

  21. Performance EvaluationFurther Definitions of Probability of False Alarm • 1. Same-State False Alarm (SSFA): A link signature is measured in state i while there exists in the history some other signatures of state i, however, the new measurement is far enough away from the measurements in the history that they are detected as different, thus a false alarm is raised. • 2 Different-State False Alarm (DSFA): A link signature is measured in state i, but no signature previously measured in state i exists in the history. Because link signatures from states j <> i are very different from those measured in state i, this new measurement does not match any in the history, and a false alarm is raised.

  22. Performance EvaluationFurther Definitions of Probability of False Alarm (Cont.) • Caculation of P[DSFA]

  23. Performance EvaluationP[DSFA]

  24. The END Thank You~~

More Related