# Link Quality Estimation from Burstiness Distribution Metric in Industrial Wireless Sensor Networks  
[PERSON]  
1 IT Convergence Department, University of Ulsan, Daehak-ro 93, Nam-gu Ulsan 44610, Korea;  
[EMAIL_ADDRESS]  
22 October 2  
changes and radio interference. However, the proposed method did not give any metrics that apply to protocols for improving network performance. [PERSON] et al. (2015) proposed a Link Quality Estimator (LQE) node, dedicated to real-time link quality estimation using the obtained information and RSSI from received packets. They used RSSI and LQI values to infer the Packet Reception Rate (PRR) of the given links. Unfortunately, RSSI and PDR have proven to be only loosely correlated in many situations. The hardware-based estimators do not require computation resources because they use built-in hardware metrics. However, they do not have precise measurements, as found and recorded in previous studies. The PRR and the Required Number of Packets (RNP) are some examples of software-based estimators based on the upper layer calculated information. RNP is calculated based on the transmitted packets from senders and is more reactive when compared with PRR. Thus, as long as the traffic is created by the sender, RNP can assess the quality of the link. However, if packets are successfully received after being retransmitted many times, RNP can underestimate the quality of the link. Some RNP-based estimators are Window Mean with Exponentially Weighted Moving Average (WMEWMA), Expected Transmission Count (ETX), and Four-Bit (FB). WMEWMA uses the EWMA filter as the key estimation technique; the PRR is calculated and then smoothed to the previously calculated PRR, which gives a more reliable yet sufficiently agile approximation compared to the PRR ([PERSON] and [PERSON], 2016). The average-based LQEs show poor reactivity. In order to overcome that, the authors ([PERSON] and [PERSON], 2016) proposed the Kalman Filter-based Link Quality Estimator (KLE). ETX ([PERSON] and [PERSON], 2016) considers link asymmetry by calculating the PRR of the backward link and the forward link. However, [PERSON] and [PERSON] (2016) found that in congested networks, passive monitoring ETX overloaded, since a large number of nodes did not receive packets to calculate ETX. FB ([PERSON] and [PERSON], 2016) link estimation is designed with four bits of information. FB integrates RNP and WMEWMA with an EWMA filter to approximate the number of retransmissions. The authors in ([PERSON] and [PERSON], 2016) performed a simulation to compare five LQEs: PRR, RNP, WMEWMA, ETX, and FB in smart-grid environments. The simulation result showed that ETX and FB showed better performance since ETX and FB considered the link asymmetry. However, ETX and FB did not consider burstiness in the links during their measurements. In this study, we examined the effect of the link quality on designing a MAC protocol for industrial wireless sensor networks. Then, we proposed a link quality estimation mechanism that is based on counting the number of consecutively lost packets on each link at the receiving end, as calculated by the receiver node. The number of consecutively lost packets then gave the distribution of burstiness for each link in the networks. In our proposal, link quality measurement was executed during network formation; however, its result could be utilized during network working. Furthermore, based on the new link quality estimator, we proposed a metric called the burstiness distribution metric, which is used for estimating the number of transmissions in order to obtain target PRR that can be used to find the shortest transmission path in routing protocol. The metric can also be used for designing a MAC protocol for the industrial wireless sensor network or applying soft-sensor techniques ([PERSON] and [PERSON], 2016; [PERSON], 2016) to give real-time estimation for the link quality measurement. The rest of the paper is organized as follows. In Section 2, we described the system model and gave a link burstiness research overview.