Caraoke: An E-Toll Transponder Network for Smart Cities

Abari et al., ACM SIGCOMM ‘15

Motivation/Introduction

• Background: RFID is pervasive, everyone has an EZPass, e.g., transponder (mandatory in PA?)
• Deploy RFID readers on street lamps, intersections, everywhere in city (at some cost), as shown in Figure 3.
• Interact with e-toll (EZPass) transponders anywhere in an urban environment
• Enables some new use cases:
  1. Vehicle flow at traffic intersections
  2. Red light enforcement via localization
  3. Street parking management and billing

Transponder Background

• Reader (high powered multi-Watt radio + directional antenna) sends message to tags, tag replies
• But no MAC protocol so common practice is to place readers in non-overlapping locations (spatial reuse)
• Figure 2: Shows the reader transmitting the 915 MHz sinewave Query signal and the transponder’s Response data packet
  • Simple radio so carrier frequency offset up to 1.2 MHz (that’s one part per thousand – typical Wi-Fi radio CFOs are 10-30 parts per million)
  • Transponder response is On-Off Keyed (OOK): Each symbol period, transmit carrier for a one, or be silent for a zero.
  • Receive picture – peaks at the CFO value Delta-f (on board)

Contribution/Key Idea

• Let tags collide when they are read simultaenously but view collision in the frequency domain – use carrier frequency offset (CFO) to separate the tags

Design

• LTE backhaul, solar-powered lamppost-mounted reader

§5: CFO-Based Sharing

• Goal: Estimate the number of vehicles crossing a busy intersection

• Take the FFT of collision (sum of many received tags replying at the same time)

  • Figure 4: Most likely, # peaks = # transponders responding

1. Need to look at the distribution of the transponder CFOs

2. Need to consider frequency resolution of the FFT

   • Inversely proportional to FFT *time window T
   • Tag response 512 us so frequency resolution = 1.95 KHz
   • That’s 615 “bins” over a range of 1.2 MHz
   • Eq. 7 gives prob of an accurate transponder count if we just count peaks in the frequency domain

• Insight: Time shifting property of DFT – time shift in in the time domain transforms with a phase shift linear with frequency, in the frequency domain.

• Receive two signals R(f) and R(f’), then looking at that with a time shift you get R(f)exp{j2pi*f*tau} + R(f')exp{j2pi*f'*tau}

  • Paper claim: Then magnitude of that bin changes b/c the two frequencies rotate by different amounts and then sum…

• Now a miscount happens when three transponders end up in same FFT bin

  • Very unlikely (math in Eq. 9)

§6: Localizing Transponders

• Goal: Localize the transponders, to enable smart parking, red-light violations
• Calculate the AoA at a two-antenna reader via the same math as spatial signatures (Figure 5 and Eq. 10)
• Do this on a per-frequency basis to separate the AoA estimates for each tag (unnumbered equation on p. 302, lower right column)
• Issue: Sensitivity to small perturbations of Delta-phi at the ends of the two antenna array
  • Fix: Use three antennas in a triangle, switch to the pair that doesn’t end-face the tag
  • But need a story for either adding a radio OR switching and then re-querying to get more readings (only partially discussed in paper)
• Result (Figure 7): A cone locus, which intersects the road at a hyperbola
  • Two readings from two readers results in two hyperbolas, intersect them for location fix.

§7: Measuring Speed

• Localize car at two different locations, NTP timesync, compute average speed

§8: Decoding IDs

• Spectrum is sinc-squared power versus frequency, not white noise
• Nice trick to separate closely-spaced replies in frequency:
  • Estimate channel to one tag
  • Receive another batch of collisions, estimate channel to the same tag and equalize
  • Add the results: the one tag adds coherently, the others are random and average to zero
  • Repeat with even more readings for better results (Figure 8)

§9: Coordinating Multiple Readers

• Preceding was interference between tag replies; now consider two readers initiating queries at the same time
  • This is usually OK: sum of two sinuoids is a sinusoid
• Collision of query with tag reply:
  • Listen for duration of query + reply (this is the slot time), then use CSMA/CA like Ethernet/ALOHA

§11: Evaluation

• Implemented in hardware, experimented on quiet urban environment streets
• EZPass transponders in real cars, on real street

Counting Accuracy

• Figure 11: Vary the number of transponders responding, accuracy maintains high
  • Collect traces by measuring each transponder in isolation, using highly directional antenna
  • Then sum up varying numbers of transponders (so know ground truth) to obtain another trace instance

Localization Accuracy

• Two readers, 175 localization instances
• Measure bearing estimation accuracy, not localization accuracy
  • Accurate to within 4 degrees on average – low intensity multipath reflections outside, line-of-sight path from car to elevated reader.
  • Measured the MUSIC AoA profile (Figure 14) to support this.