Customizing Indoor Wireless Coverage via 3D-Fabricated Reflectors

Xi Xiong1, Justin Chan2, Ethan Yu1, Nisha Kumari1, Ardalan Amiri Sani3, Changxi Zheng4, and Xia Zhou1
Department of Computer Science
1Dartmouth College, 2University of Washington, 3UC Irvine, 4Columbia University

Abstract

Judicious control of indoor wireless coverage is crucial in built environments. It enhances signal reception, reduces harmful interference, and raises the barrier for malicious attackers. Existing methods are either costly, vulnerable to attacks, or hard to configure. We present a low-cost, secure, and easy-to-configure approach that uses an easily-accessible, 3D-fabricated reflector to customize wireless coverage. With input on coarse-grained environment setting and preferred coverage (e.g., areas with signals to be strengthened or weakened), the system computes an optimized reflector shape tailored to the given environment. The user simply 3D prints the reflector and places it around a Wi-Fi access point to realize the target coverage. We conduct experiments to examine the efficacy and limits of optimized reflectors in different indoor settings. Results show that optimized reflectors coexist with a variety of Wi-Fi APs and correctly weaken or enhance signals in target areas by up to 10 or 6 dB, resulting to throughput changes by up to -63.3% or 55.1%.

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bibtex Xi Xiong, Justin Chan, Ethan Yu, Nisha Kumari, Ardalan Amiri Sani, Changxi Zheng, and Xia Zhou. Customizing Indoor Wireless Coverage via 3D-Fabricated Reflectors, ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys), November, 2017, Delft, The Netherlands. [PDF]
bibtex Justin Chan, Changxi Zheng, and Xia Zhou. 3D Printing Your Wireless Coverage, ACM Workshop on Hot Topics in Wireless (HotWireless), September, 2015, Paris, France. Hot Paper Award. [PDF]

Acknowledgment

We sincerely thank reviewers for their insightful comments. This work is supported in part by the Dartmouth Burke Research Initiation Award and the Class of 1993 Alumni Fund at Dartmouth College, the National Science Foundation (CAREER-1453101), as well as generous gifts from Intel. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the funding agencies or others.

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