Runtime Estimation of the Number of Active Devices in IEEE 802.15.4 Slotted CSMA/CA Networks with Deferred Transmission and No Acknowledgment Using ARMA Filters

We propose a novel method for estimating the number of active devices in an IEEE 802.15.4 network. Here, we consider an IEEE 802.15.4 network with a star topology where active devices transmit data frames using slotted carrier sense multiple access with collision avoidance (CSMA/CA) medium access co...

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Veröffentlicht in:Wireless communications and mobile computing 2018-01, Vol.2018 (2018), p.1-12
Hauptverfasser: Lee, Won Hyoung, Chong, Jo Woon, Hwang, Ho Young
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Sprache:eng
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Zusammenfassung:We propose a novel method for estimating the number of active devices in an IEEE 802.15.4 network. Here, we consider an IEEE 802.15.4 network with a star topology where active devices transmit data frames using slotted carrier sense multiple access with collision avoidance (CSMA/CA) medium access control (MAC) protocol without acknowledgment. In our proposed method, a personal area network (PAN) coordinator of a network counts the number of events that a transmission occurs and the number of events that two consecutive slots are idle in a superframe duration, and the PAN coordinator broadcasts the information through a beacon frame. Each device can count the number of slots that each device is in the backoff procedure and the number of the first clear channel assessment (CCA) that each device performs whenever it performs the first CCA after the backoff procedure. Then, each device estimates the number of active devices in the network based on these counted numbers and the information from PAN coordinator with the help of an autoregressive moving average (ARMA) filter. We evaluate the performance of our proposed ARMA-based estimation method via simulations where active devices transmit data frames in IEEE 802.15.4 slotted CSMA/CA networks. Simulation results show that our proposed method gives estimation errors of the number of active devices less than 4.501% when the actual number of active devices is varying from 5 to 80. We compare our proposed method with the conventional method in terms of the average and standard deviation for the estimated number of active devices. The simulation results show that our proposed estimation method is more accurate than the conventional method.
ISSN:1530-8669
1530-8677
DOI:10.1155/2018/5420876