Enhancing Efficient Link Performance in ZigBee Under Cross-Technology Interference

  • Zhenquan Qin
  • Yingxiao Sun
  • Junyu Hu
  • Wei Zhou
  • Jialin Liu


The coexistence of heterogenous wireless networks has long been a problem especially with the explosive development in recent years. These heterogenous, such as WiFi, ZigBee and Bluetooth operating in the crowded ISM band, have to compete with each other for scarce spectrum resources, generating cross-technology interference (CTI). Since CTI may lead to severe performance degradation of ZigBee networks, especially under high density WiFi interference. In this paper, we propose a novel adaptive packet delivery (APD) algorithm that enables ZigBee links to achieve enhanced performance under the presence of heavy WiFi traffic. First, we pre-analyze the coexistence of co-located networks, we find the WiFi frame cluster well follow the power law distribution model with burst WiFi traffic, then the PER analysis is also determined to help obtain the probability of delivering packets successfully. Second, we propose a new metric called channel idle state indicator (CISI) to quantify current channel quality. Third, based on CISI and the pre-analysis, we build APD to instruct ZigBee nodes to transmit, besides, we consider the occasion where the packet contains an emergency message. Extensive experimental results show that, under the coverage of different WiFi traffic, our lightweight mechanism can achieve 4x and 1.5x performance gains over WISE and CII. Particularly, when WiFi traffic is 4 Mbps, we can still obtain over 90%. Furthermore, the energy consumption efficiency can be improved markedly with compared protocols.


CTI ZigBee WiFi Health telemonitoring system 



The work is supported by “National Natural Science Foundation of China” with No. 61733002 and “the Fundamental Research Funds for the Central University” with No. DUT17LAB16, No. DUT2017TB02. This work is also supported by Tianjin Key Laboratory of Advanced Networking (TANK), School of Computer Science and Technology, Tianjin University, Tianjin, China, 300350.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of SoftwareDalian University of TechnologyDalianChina

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