Wireless Networks

, Volume 25, Issue 2, pp 805–817 | Cite as

A frequency hopping method for spatial RFID/WiFi/Bluetooth scheduling in agricultural IoT

  • Tao ChiEmail author
  • Ming Chen


Currently, a variety of wireless modules are purposed for different criteria in the area of the agricultural internet of things; however, there is a lack of appropriate methods enabling these wireless modules to operate in the same frequency band. The goal of this paper is to make a very thorough quantitative analysis on the theoretical maximum collision time and collision probability of WiFi or Bluetooth network with RFID interferers. We propose the interference avoidance scheme which requires the knowledge of the theoretical maximum collision time and collision probability between RFID and WiFi/Bluetooth packets. This scheme generates an optimal channel based on the current usage of the adjacent frequency channels thereby reducing the interference. We also propose two solutions from this scheme: a frequency hopping combined with white space exploitation method and an intelligent frequency hopping scheme; for maintaining a quality connection of the WiFi or Bluetooth network in the presence of heavy RFID interferers. We implement a hybrid backscatter-based RFID architecture in existence of the WiFi/Bluetooth infrastructure for efficient operations within the 2.4 GHz ISM band. Results obtained are very encouraging and indicate that quantifying the maximum collision time and collision probability is a vital step for the interference avoidance scheme, which can be adopted in the avoidance of the interference from RFID modules.


Wireless communication Agricultural IoT Coexistence solution RFID WiFi Bluetooth 



The authors would like to thank the TEXAS A&M RFID Sensor Lab for use of its laboratory space, as well as Professor Ben Zoghi (director of RFID/Sensor Lab) for his fruitful discussions and advice. We thank Dr. Feng guofu, Cao Guangpu, Wang Lei and Yan Haowei for their work. Thanks are also to the anonymous reviewers for their insightful suggestions for this work. This work is supported in part by the key program of National Natural Science Foundation of China under Grant No. 61561027, and the Natural Science Foundation of Shanghai under Grant No. 16ZR1415100.


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.College of information TechnologyShanghai Ocean UniversityShanghaiChina
  2. 2.Key Laboratory of Fisheries InformationMinistry of AgricultureShanghaiChina

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