Title
Embracing collisions: enabling parallel channel estimation with COTS passive backscatter tags
Abstract
There is a growing interest in backscatter-based sensing systems in recent years. RFID techniques can be used due to low cost and structural simplicity. However, collision caused by simultaneous tag responses is one of the key issues in backscatter systems. Existing anti-collision techniques try to enable parallel decoding without sensing based applications in mind, which can not operate on COTS RFID systems. To address the issue, we propose COFFEE, which is the first work to enable parallel channel estimation of COTS passive tags by harnessing the collision. By exploiting the characteristics of low sampling rate and channel diversity of passive tags, we separate the collided data, extract the channels and identify the tags. COFFEE is compatible with current RFID standards which can be applied to all RFID-based sensing systems without any modification on tag side. To evaluate the real world performance of our system, we build a prototype and conduct extensive experiments. The experimental results show that we can achieve up to 7.33x median time resolution gain for the best case and 3.42x median gain on average.
Year
DOI
Venue
2020
10.1145/3412449.3412545
MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking London United Kingdom September, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-8099-7
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Jiaqi Xu11069.50
Wei Sun202.03
Arjun Bakshi382.12
Kannan Srinivasan41324117.98