Valentina Nejković, Nenad Milošević, Filip Jelenković, Zorica Nikolić, Milorad Tošić

DOI Number
First page
Last page


A rapid growth of the wireless communications and heavily occupied spectrum lead to an inevitable interference between the heterogenous systems operating in the same frequency band. Having in mind the development of the Internet of Things (IoT) services and networks and widely present WiFi networks on the one hand, and the fact that these two systems occupy the same 2.4 GHz frequency band on the other hand, it is clear that the control of the interference and the spectrum coordination are of the highest importance. The first step in the interference control is to acquire its properties. Since the simulation of a large IoT network is not entirely possible, due to the numerous factors not known in advance, the interference assessment is performed on the SmartSantander, an IoT testbed, located in Santander, Spain. This paper presents a statistical analysis of the sensor data and describes the interference properties and its influence. These results may be used for the spectrum coordination, together with the neural networks and semantic technologies.


Coordination, Internet of things, semantic technologies, WiFi, ZigBee

Full Text:



M. Weiser, “The Computer for the 21st Century,” SIGMOBILE Mob. Comput. Commun. Rev., vol. 3, no. 3, pp. 3–11, 1999, DOI: 10.1145/329124.329126.

J. Pontin, “Bill Joy’s Six Webs,” MITTechnology Rev., vol. 29, 2005.

M. R. Palattella et al., “Internet of Things in the 5G Era: Enablers, Architecture, and Business Models,” IEEE J. Sel. Areas Commun., vol. 34, no. 3, pp. 510–527, 2016, DOI: 10.1109/JSAC.2016.2525418.

J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): A vision, architectural elements, and future directions,” Futur. Gener. Comput. Syst., vol. 29, no. 7, pp. 1645–1660, 2013, DOI:

A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, “Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications,” IEEE Commun. Surv. Tutorials, vol. 17, no. 4, pp. 2347–2376, 2015, DOI: 10.1109/COMST.2015.2444095.

T. Kumar and P. B. Mane, “ZigBee topology: A survey,” in 2016 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2016, pp. 164–166.

N. V. R. Kumar, C. Bhuvana, and S. Anushya, “Comparison of ZigBee and Bluetooth wireless technologies-survey,” in 2017 International Conference on Information Communication and Embedded Systems (ICICES), 2017, pp. 1–4.

J. r. Lin, T. Talty, and O. K. Tonguz, “On the potential of bluetooth low energy technology for vehicular applications,” IEEE Commun. Mag., vol. 53, no. 1, pp. 267–275, 2015, DOI: 10.1109/MCOM.2015.7010544.

C. Gomez, J. Oller, and J. Paradells, “Overview and evaluation of bluetooth low energy: An emerging low-power wireless technology,” Sensors, vol. 12, no. 9, pp. 11734–11753, 2012.

“Federated Interoperable Semantic IoT Testbeds and Applications (FIESTA-IoT).” [Online]. Available:

“SmartSantander.” [Online]. Available: [Accessed: 01-Jan-2018].

G. Anastasi, M. Conti, and M. Di Francesco, “A Comprehensive Analysis of the MAC Unreliability Problem in IEEE 802.15.4 Wireless Sensor Networks,” IEEE Trans. Ind. Informatics, vol. 7, no. 1, pp. 52–65, Feb. 2011, DOI: 10.1109/TII.2010.2085440.

P. Huang, L. Xiao, S. Soltani, M. W. Mutka, and N. Xi, “The Evolution of MAC Protocols in Wireless Sensor Networks: A Survey,” IEEE Commun. Surv. Tutorials, vol. 15, no. 1, pp. 101–120, 2013, DOI: 10.1109/SURV.2012.040412.00105.

Crossbow Inc., “Avoiding RF Interference Between WiFi and Zigbee.” [Online]. Available:

S. Pollin, I. Tan, B. Hodge, C. Chun, and A. Bahai, “Harmful Coexistence Between 802.15.4 and 802.11: A Measurement-based Study,” in 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), 2008, pp. 1–6.

J. Huang, G. Xing, G. Zhou, and R. Zhou, “Beyond co-existence: Exploiting WiFi white space for Zigbee performance assurance,” in The 18th IEEE International Conference on Network Protocols, 2010, pp. 305–314.

C.-J. M. Liang, N. B. Priyantha, J. Liu, and A. Terzis, “Surviving Wi-fi Interference in Low Power ZigBee Networks,” in Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, 2010, pp. 309–322.

X. Zhang and K. G. Shin, “Cooperative Carrier Signaling: Harmonizing Coexisting WPAN and WLAN Devices,” IEEE/ACM Trans. Netw., vol. 21, no. 2, pp. 426–439, Apr. 2013, DOI: 10.1109/TNET.2012.2200499.

M. S. Kang, J. W. Chong, H. Hyun, S. M. Kim, B. H. Jung, and D. K. Sung, “Adaptive Interference-Aware Multi-Channel Clustering Algorithm in a ZigBee Network in the Presence of WLAN Interference,” in 2007 2nd International Symposium on Wireless Pervasive Computing, 2007.

S. Pollin et al., “Distributed cognitive coexistence of 802.15.4 with 802.11,” in 2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2006, pp. 1–5.

R. Musaloiu-E. and A. Terzis, “Minimising the Effect of WiFi Interference in 802.15.4 Wireless Sensor Networks,” Int. J. Sen. Netw., vol. 3, no. 1, pp. 43–54, 2008, DOI: 10.1504/IJSNET.2008.016461.

L. Tytgat, O. Yaron, S. Pollin, I. Moerman, and P. Demeester, “Analysis and Experimental Verification of Frequency-Based Interference Avoidance Mechanisms in IEEE 802.15.4,” IEEE/ACM Trans. Netw., vol. 23, no. 2, pp. 369–382, Apr. 2015, DOI: 10.1109/TNET.2014.2300114.

J. W. Chong, C. H. Cho, H. Y. Hwang, and D. K. Sung, “An Adaptive WLAN Interference Mitigation Scheme for ZigBee Sensor Networks,” Int. J. Distrib. Sen. Netw., vol. 2015, p. 159:159--159:159, 2015, DOI: 10.1155/2015/851289.

S. Nishikori, K. Kinoshita, Y. Tanigawa, H. Tode, and T. Watanabe, “A cooperative channel control method of ZigBee and WiFi for IoT services,” in 2017 14th IEEE Annual Consumer Communications Networking Conference (CCNC), 2017, pp. 1–6.

A. K. Sharma, Text Book Of Correlations And Regression. New Delhi: Discovery Publishing House, 2005.

D. Raychaudhuri, X. Jing, I. Seskar, K. Le, and J. B. Evans, “Cognitive radio technology: From distributed spectrum coordination to adaptive network collaboration,” Pervasive and Mobile Computing, vol. 4, no. 3. pp. 278–302, 2008.



  • There are currently no refbacks.

Print ISSN: 1820-6417
Online ISSN: 1820-6425