Time-Dependent Bit Error Rate Analysis for Smart Utility Networks in the Presence of WLAN Interferers

The smart grid (SG) modernizes the aging power grid by using two-way reliable communications dedicated to adaptive energy management. To achieve this goal, smart utility networks (SUNs) are used to efficiently connect the SG devices. However, the SUNs are designed to work on unlicensed frequency bands and are very sensitive to interferences from other networks operating in the same band, such as wireless local area networks (WLANs). Therefore, in this paper, the effect of the WLAN interferers on the SUN transmission is investigated and we show that by detecting the initial transmission offset of each WLAN transceiver using energy sensing, the activity of the interferers can be predicted with high accuracy. Furthermore, we prove that the SUN data bit error rate is time dependent and that each SUN bit has a different bit error rate expression depending on its time offset. These expressions are derived analytically and verified by Monte Carlo simulations. In fact, these expressions can be used by the SUN devices to enhance their communication links in the presence of WLAN devices by using adaptive transmission techniques to avoid the interference.

[1]  Hsiao-Hwa Chen,et al.  Coexistence of smart utility networks and WLAN/ZigBee in smart grid , 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

[2]  Chi Zhou,et al.  Developing ZigBee Deployment Guideline Under WiFi Interference for Smart Grid Applications , 2011, IEEE Transactions on Smart Grid.

[3]  Wei Yuan,et al.  Adaptive CCA for IEEE 802.15.4 Wireless Sensor Networks to Mitigate Interference , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[4]  Mario Gerla,et al.  Minimizing 802.11 interference on ZigBee medical sensors , 2009, BODYNETS.

[5]  Ali Hazmi,et al.  Performance comparison between slotted IEEE 802.15.4 and IEEE 802.1 lah in IoT based applications , 2013, 2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[6]  B.F. Wollenberg,et al.  Toward a smart grid: power delivery for the 21st century , 2005, IEEE Power and Energy Magazine.

[7]  Moncef Gabbouj,et al.  Maximum achievable throughput and interference mitigation for SUN in coexistence with WLAN , 2018, 2018 International Conference on Advanced Communication Technologies and Networking (CommNet).

[8]  Andreas Pitsillides,et al.  Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures , 2014, IEEE Communications Surveys & Tutorials.

[9]  Mohsen Guizani,et al.  Cognitive radio based hierarchical communications infrastructure for smart grid , 2011, IEEE Network.

[10]  Hsiao-Hwa Chen,et al.  Smart Grid Communication: Its Challenges and Opportunities , 2013, IEEE Transactions on Smart Grid.

[11]  Nei Kato,et al.  Toward intelligent machine-to-machine communications in smart grid , 2011, IEEE Communications Magazine.

[12]  Hsiao-Hwa Chen,et al.  Coexistence of Smart Utility Networks and WLANs in Smart Grid Systems , 2016, IEEE Transactions on Wireless Communications.

[13]  Chin-Sean Sum,et al.  Coexistence of homogeneous and heterogeneous systems for IEEE 802.15.4g smart utility networks , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[14]  Soumaya Cherkaoui,et al.  Adaptive 802.15.4 backoff procedure to survive coexistence with 802.11 in extreme conditions , 2016, 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC).

[15]  B Hamilton,et al.  Benefits of the Smart Grid [In My View] , 2011 .

[16]  Hsiao-Hwa Chen,et al.  Smart grid neighborhood area networks: a survey , 2014, IEEE Network.

[17]  Hsiao-Hwa Chen,et al.  Dynamic Spectrum Sharing for the Coexistence of Smart Utility Networks and WLANs in Smart Grid Communications , 2017, IEEE Network.

[18]  Hsiao-Hwa Chen,et al.  A packet collision model for PER analysis in smart utility networks , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[19]  Jianlin Guo,et al.  Self-transmission control in IoT over heterogeneous wireless networks , 2017, 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN).

[20]  Hsiao-Hwa Chen,et al.  A Segmented Packet Collision Model for Smart Utility Networks Under WLAN Interferences , 2016, IEEE Transactions on Wireless Communications.

[21]  Long Bao Le,et al.  Throughput analysis for coexisting IEEE 802.15.4 and 802.11 networks under unsaturated traffic , 2016, EURASIP J. Wirel. Commun. Netw..

[22]  Md. Iftekhar Hussain,et al.  A comparison of 802.11ah and 802.15.4 for IoT , 2016, ICT Express.

[23]  Mahesh Sooriyabandara,et al.  Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities , 2011, IEEE Communications Surveys & Tutorials.

[24]  Kang G. Shin,et al.  Enabling coexistence of heterogeneous wireless systems: case for ZigBee and WiFi , 2011, MobiHoc '11.

[25]  Dong Yang,et al.  Coexistence of IEEE802.15.4 based networks: A survey , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[26]  Periklis Chatzimisios,et al.  Chapter 26 – A Survey on Smart Grid Communications: From an Architecture Overview to Standardization Activities , 2013 .