Master’s Thesis Presentation • Systems and Networking — Performance Evaluation of WiFi Backscatter SystemsExport this event to calendar

Friday, September 25, 2020 2:00 PM EDT

Please note: This master’s thesis presentation will be given online.

Farzan Dehbashi, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Omid Abari

WiFi backscatter communication has been proposed to enable battery-free sensors to transmit data using WiFi networks. The main advantage of WiFi backscatter technologies over RFID is that data from their tags can be read using existing WiFi infrastructures instead of specialized readers. This can potentially reduce the complexity and cost of deploying battery-free sensors. Despite extensive work in this area, none of the existing systems are in widespread use today. We hypothesize that this is because WiFi-based backscatter tags do not scale well in WiFi networks, and their range and capabilities are limited when compared with RFID. 

This thesis uses real-world experiments to test this hypothesis. Our results show that existing WiFi backscatter tags cannot rely on RF harvesting (on the contrary to RFID tags) due to their high power consumption. We find that WiFi backscatter tags must be quite close to a WiFi device to work robustly in non-line-of-sight scenarios, limiting their operating range. Furthermore, our results show that some WiFi backscatter systems can cause significant interference for existing WiFi traffic since they do not perform carrier sensing. Moreover, we compare WiFi backscatter with RFID in terms of range, bitrate, and RF harvesting capabilities. Finally, we provide some insights into addressing several challenges in building practical WiFi backscatter systems.


To join this master’s thesis presentation on Zoom, please go to https://us02web.zoom.us/j/76191861713?pwd=cUpZZUFaaXUrUW1MeDFoeWNINDN0QT098vrbP5.

Location 
Online presentation
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

S M T W T F S
30
31
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
1
2
3
  1. 2024 (96)
    1. April (19)
    2. March (27)
    3. February (25)
    4. January (25)
  2. 2023 (296)
    1. December (20)
    2. November (28)
    3. October (15)
    4. September (25)
    5. August (30)
    6. July (30)
    7. June (22)
    8. May (23)
    9. April (32)
    10. March (31)
    11. February (18)
    12. January (22)
  3. 2022 (245)
  4. 2021 (210)
  5. 2020 (217)
  6. 2019 (255)
  7. 2018 (217)
  8. 2017 (36)
  9. 2016 (21)
  10. 2015 (36)
  11. 2014 (33)
  12. 2013 (23)
  13. 2012 (4)
  14. 2011 (1)
  15. 2010 (1)
  16. 2009 (1)
  17. 2008 (1)