utilizing physical layer information to improve rfid tag

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may cause. Figure 6.7. Strong and weak tag collision waveform. For this evaluation, three data sets of 10,000 readings each are generated. Each data set follows a Poisson distribution. Data sets A and B have the same value of λ while dataset C has a different value. Each data set represents a unique RFID tag. Tags A and B have the same RFID chip and thus follow the same distribution. A fixed Q value of 5 giving 32 slots is used in this analysis. Thus in each of the 10,000 rounds the data set has an integer value between 1 and 32 denoting the slot chosen by the tag. Fig. 6.9 shows the histogram for tags A and B with a λ value of 10 while Fig. 6.10 shows the histogram for tag C with a λ value of 15. Analysis of the data gives the following result: Collisions when Tag A and B are in range = 898 Collisions when Tag A and C are in range = 442 30
Figure 6.8. Strong and weak tag collision I-Q plot. An experiment was carried out by using some standard RFID tags to find the distribution function of their random number generators. Pearson’s chi-square test was carried out for all the 4 tags as well as a data set generated using a uniform pdf. The results are summarized in table 6.5 Table 6.5. Random number generator performance of common tags 6.5 Effect of non-uniform PDF Tag Mean Square Error bow-tie 41.43 excalibur 31.25 squiggle 22.53 TI 20.77 Reference data set 26.22 Tag random number generators have a uniform distribution for the output val- ues and they are distributed between 0 and 2 Q -1. In this section we analyze the 31
Page 1 and 2: UTILIZING PHYSICAL LAYER INFORMATIO
Page 3 and 4: ACKNOWLEDGEMENTS My first encounter
Page 5 and 6: This thesis proposes a method of us
Page 7 and 8: 5.3 Signal separation . . . . . . .
Page 9 and 10: 6.7 Strong and weak tag collision w
Page 11 and 12: CHAPTER 1 INTRODUCTION Radio-Freque
Page 13 and 14: and signal absorption or reflection
Page 15 and 16: 2.1 RFID Reader CHAPTER 2 PASSIVE U
Page 17 and 18: Figure 2.2. Alien Squiggle Tag. Fig
Page 19 and 20: CHAPTER 3 ISO 18000-6C PROTOCOL The
Page 21 and 22: eply immediately. Tags that pick a
Page 23 and 24: identification times even if the nu
Page 25 and 26: difficult problem as field nulls ar
Page 27 and 28: Figure 5.1. Passive tag structure.
Page 29 and 30: Figure 5.4. Software defined radio.
Page 31 and 32: Figure 5.7. I-Q plot. Figure 5.8. 2
Page 33 and 34: 6.1 Tag estimation from collision C
Page 35 and 36: Figure 6.3. 4 tag collision. tags i
Page 37 and 38: 2. Anti-collision with enhanced tag
Page 39: Table 6.4. Results for enhanced ant
Page 43 and 44: Figure 6.10. Random number distribu
Page 45 and 46: Figure 6.13. Squiggle tag. Figure 6
Page 47 and 48: Figure 6.17. Gaussian PDFs used for
Page 49 and 50: CHAPTER 7 USRP SYSTEM A software-de
Page 51 and 52: 7.2 Software GNU Radio is a free so
Page 53 and 54: CHAPTER 8 CONCLUSIONS AND FUTURE WO
Page 55 and 56: probabilty distribution. Thus there
Page 57 and 58: tions. This section contains the th
Page 59 and 60: A.1.2 Algortihm A (Reference Algori
Page 61 and 62: end end 51
Page 63 and 64: A.2.2 Inventory Round Simulation %R
Page 65 and 66: A.2.3 Predicting Number of Tags %Ru
Page 67 and 68: REFERENCES [1] EPCglobal, “Uhf cl
Page 69 and 70: [21] K. Finkenzeller, RFID Handbook

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