AiFi: AI-Enabled WiFi Interference Cancellation with Commodity PHY-Layer Information
Authors: 
Ruirong Chen, Kai Huang, Wei GaoAuthors Info & Claims
Pages 134 - 148
Abstract
Interference could result in significant performance degradation in WiFi networks. Most existing solutions to interference cancellation require extra RF hardware, which is usually infeasible in many low-power wireless scenarios. In this paper, we present AiFi, a new interference cancellation technique that can be applied to commodity WiFi devices without using any extra RF hardware. The key idea of AiFi is to retrieve knowledge about interference from the locally available physical-layer (PHY) information at the WiFi receiver, including the pilot information (PI) and the channel state information (CSI). AiFi leverages the power of AI to address the possible ambiguity when estimating interference from these PHY information, and incorporates the domain knowledge about WiFi PHY to minimize the neural network complexity. Experiment results show that AiFi can correct 80% of bit errors due to interference and improves the MAC frame reception rate by 18x, with <1ms latency for interference cancellation in each frame.
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Index Terms
- AiFi: AI-Enabled WiFi Interference Cancellation with Commodity PHY-Layer Information
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Published In
November 2022
1280 pages
ISBN:9781450398862
DOI:10.1145/3560905
- General Chairs:
- Jeremy Gummeson,
- Sunghoon Ivan Lee,
- Program Chairs:
- Jie Gao,
- Guoliang Xing
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Published: 24 January 2023
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SenSys '22: The 20th ACM Conference on Embedded Networked Sensor Systems
November 6 - 9, 2022
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SenSys '22 Paper Acceptance Rate 52 of 187 submissions, 28%;
Overall Acceptance Rate 174 of 867 submissions, 20%
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