VMscatter: A Versatile MIMO Backscatter


Xin Liu, Zicheng Chi, Wei Wang, Yao Yao, and Ting Zhu, University of Maryland, Baltimore County


In this paper, we design and implement a versatile MIMO backscatter (VMscatter) system, which leverages the diversity features of MIMO to dramatically decrease bit error rate (BER) and increase throughput with negligible overhead. Our approach is different from existing WiFi MIMO backscatter approaches which simply reflect the signals from the WiFi MIMO sender and do not take advantage of MIMO technologies' advanced features (i.e., low bit error rate and high throughput). In our approach, the backscatter can achieve the same full diversity gain as traditional MIMO system by implementing the space-time coding on the backscatter tag under the constraint that backscatter tags cannot control the reflected signals to be orthogonal. Moreover, the backscatter can reflect excitation signals from the senders that have either a single antenna or multiple antennas. To implement the VMscatter system, we addressed the special design challenges such as complicated channel estimations among the sender, tag, and receiver by using a novel pre-scatter channels elimination method and a post-scatter channels equalization method. Our VMscatter design introduces negligible overheads (in terms of hardware cost, energy consumption, and computation) on the backscatter tag. We further extended our design to support any number of antennas that the sender, tag, and receiver have. Our MIMO backscatter design is generic and has the potential to be extended to achieve massive MIMO. We extensively evaluated our system in different real-world scenarios. Results show that the BER is reduced by a factor of 862 compared to the most related work MOXcatter.

NSDI '20 Open Access Sponsored by NetApp

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@inproceedings {246324,
author = {Xin Liu and Zicheng Chi and Wei Wang and Yao Yao and Ting Zhu},
title = {{VMscatter}: A Versatile {MIMO} Backscatter },
booktitle = {17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20)},
year = {2020},
isbn = {978-1-939133-13-7},
address = {Santa Clara, CA},
pages = {895--909},
url = {https://www.usenix.org/conference/nsdi20/presentation/liu-xin},
publisher = {USENIX Association},
month = feb,

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