Link Quality Estimation of Cross-Technology Communication
Jia Zhang, Xiuzhen Guo, Haotian Jiang, Xiaolong Zheng, Yuan He
Abstract
Research on cross-technology communication (CTC) has made rapid progress in recent years. While the CTC links are complex and dynamic, how to estimate the quality of a CTC link remains an open and challenging problem. Through our observation and study, we find that none of the existing approaches can be applied to estimate the link quality of CTC. Built upon the physical-level emulation, transmission over a CTC link is jointly affected by two factors: the emulation error and the channel distortion. Furthermore, the channel distortion can be modeled and observed through the signal strength and the noise strength. We, in this article, propose a new link metric called C-LQI and a joint link model that simultaneously takes into account the emulation error and the channel distortion in the In-phase and Quadrature (IQ) domain. We accurately describe the superimposed impact on the received signal. We further design a lightweight link estimation approach including two different methods to estimate C-LQI and in turn the packet reception rate (PRR) over the CTC link. We implement C-LQI and compare it with two representative link estimation approaches. The results demonstrate that C-LQI reduces the relative estimation error by 49.8% and 51.5% compared with s-PRR and EWMA, respectively.
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Cited by top-tier papers2
- WiRa: Enabling Cross-Technology Communication from WiFi to LoRa with IEEE 802.11axDan Xia, Xiaolong Zheng, Fu Yu, Liang Liu et al.INFOCOM 2022 · 42 citations
- Parallel Cross-technology Transmission from IEEE 802.11ax to Heterogeneous IoT DevicesDan Xia, Xiaolong Zheng, Liang Liu, Huadong MaINFOCOM 2023 · 15 citations
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