Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks
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作者
Zhang, Hanzhong; Zhou, Ting; Xu, Tianheng; Hu, Honglin
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刊物名称
SENSORS
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年、卷、文献号
2023, 23, 1424-8220
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关键词
Zhang, Hanzhong; Zhou, Ting; Xu, Tianheng; Hu, Honglin
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摘要
The Internet-of-Things (IoT) massive access is a significant scenario for sixth-generation (6G) communications. However, low-power IoT devices easily suffer from remote interference caused by the atmospheric duct under the 6G time-division duplex (TDD) mode. It causes distant downlink wireless signals to propagate beyond the designed protection distance and interfere with local uplink signals, leading to a large outage probability. In this paper, a remote interference discrimination testbed is originally proposed to detect interference, which supports the comparison of different types of algorithms on the testbed. Specifically, 5,520,000 TDD network-side data collected by real sensors are used to validate the interference discrimination capabilities of nine promising AI algorithms. Moreover, a consistent comparison of the testbed shows that the ensemble algorithm achieves an average accuracy of 12% higher than the single model algorithm.
