Name
Abstract | ||
|---|---|---|
As the proliferation of backscatter-based applications, exploiting backscatter-based sensing becomes more important. Due to the requirement of accurate estimation of backscatter channels (phase and amplitude), which is often distorted when multiple signals collide with each other, existing works are generally limited to either parallel decoding of collided signals or with non-collided signals only. Motivated by our observation that a channel can be distorted during collisions, the movements of the ON-OFF Keying modulated signal still preserve channel properties of the respective tags, we propose the first approach to channel estimation of parallel 2backscattered signals, called Fireworks. We model the relationship between the channel and the signal moving trajectory in the In-phase and Quadrature (IQ) domain and implement this design in our lab. The results show that Fireworks is able to estimate up to five channels in parallel. When applied to the tracking application, Fireworks achieves 2~4× improvement in the tracking accuracy, compared with the state-of-the-art approach. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IPSN48710.2020.00-44 | 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) |
Keywords | DocType | ISBN |
Computer systems organization → Embedded systems,Redundancy,Robotics,Networks → Network reliability | Conference | 978-1-7281-5498-5 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meng Jin | 1 | 26 | 6.15 |
| Yuan He | 2 | 1012 | 81.82 |
| Chengkun Jiang | 3 | 17 | 3.64 |
| Yunhao Liu | 4 | 8810 | 486.66 |