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ECCR: Edge-Cloud Collaborative Recovery for Low-Power Wide-Area Networks Interference Mitigation

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Wireless Algorithms, Systems, and Applications (WASA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12937))

Abstract

Recent advances in Low-Power Wide-Area Networks have mitigated interference by using cloud assistance. Those methods transmit the RSSI samples and corrupted packets to the cloud to restore the correct message. However, the effectiveness of those methods is challenged by the high transmission data amount. This paper presents a novel method for interference mitigation in a Edge-Cloud collaborative manner, namely ECCR. It does not require transmitting RSSI sample any more, whose length is eight times of the packet’s. We demonstrate the disjointness of the bit errors of packets at the base stations via real-word experiments. ECCR leverages this to collaborate with multiple base stations for error recovery. Each base station detects and reports bit error locations to the cloud, then both error checking code and interfered packets from other receivers are utilized to restore correct packets. ECCR takes the advantages of both the global management ability of the cloud and the signal to perceive the benefit of each base station, and it is applicable to deployed LP-WAN systems (e.g. sx1280) without any extra hardware requirement. Experimental results show that ECCR is able to accurately decode packets when packets have nearly \(51.76\%\) corruption.

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Acknowledgement

This work was supported in part by National Natural Science Foundation of China under Grant No. 61902066, Natural Science Foundation of Jiangsu Province under Grant No. BK20190336, China National Key R&D Program 2018YFB2100302 and Fundamental Research Funds for the Central Universities under Grant No. 2242021R41068.

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Correspondence to Xiaolei Zhou .

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Mei, L., Yin, Z., Zhou, X., Wang, S., Sun, K. (2021). ECCR: Edge-Cloud Collaborative Recovery for Low-Power Wide-Area Networks Interference Mitigation. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12937. Springer, Cham. https://doi.org/10.1007/978-3-030-85928-2_39

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  • DOI: https://doi.org/10.1007/978-3-030-85928-2_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85927-5

  • Online ISBN: 978-3-030-85928-2

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