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Updated: Jun 26, 2025

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
Published on: June 2, 2020
Reliability Analysis and Optimization of a Reconfigurable Matching Network for Communication and Sensing Antennas in
Seppe Van Brandt1, Kamil Yavuz Kapusuz1, Joryan Sennesael1
1Internet Technology and Data Science Lab, Department of Information Technology, Faculty of Engineering and Architecture, Ghent University and Imec, 9052 Gent, Belgium.
Abstract:
During the implementation of the Internet of Things (IoT), the performance of communication and sensing antennas that are embedded in smart surfaces or smart devices can be affected by objects in their reactive near field due to detuning and antenna mismatch. Matching networks have been proposed to re-establish impedance matching when antennas become detuned due to environmental factors. In this work, the change in the reflection coefficient at the antenna, due to the presence of objects, is first characterized as a function of the frequency and object distance by applying Gaussian process regression on experimental data. Based on this characterization, for random object positions, it is shown through simulation that a dynamic environment can lower the reliability of a matching network by up to 90%, depending on the type of object, the probability distribution of the object distance, and the required bandwidth. As an alternative to complex and power-consuming real-time adaptive matching, a new, resilient network tuning strategy is proposed that takes into account these random variations. This new approach increases the reliability of the system by 10% to 40% in these dynamic environment scenarios.
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