LeZi-update: an information-theoretic approach to track mobile users in PCS networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Mobility prediction and routing in ad hoc wireless networks
International Journal of Network Management
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Real-Time Mobility Tracking Algorithms for Cellular Networks Based on Kalman Filtering
IEEE Transactions on Mobile Computing
A virtual circle-based clustering algorithm with mobility prediction in large-scale MANETs
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
Link quality prediction in mesh networks
Computer Communications
Journal of Network and Computer Applications
Data-driven link quality prediction using link features
ACM Transactions on Sensor Networks (TOSN)
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As mobile devices are getting more ubiquitous, the paradigm of wireless mobile ad hoc networks (MANETs) is gaining popularity. However, MANETs impose new challenges because of their self-organizing, mobile and error-prone nature. Mobility prediction can mitigate the problems emerging from node mobility.In this paper, we propose an approach called XCoPred to predict link quality variations based on pattern matching which can be exploited for mobility prediction. XCoPred doesn't require the use of any external hardware or reference point. Each MANET node monitors the Signal to Noise Ratio (SNR) of its links to obtain a time series of SNR measurements. When a prediction is required, the node tries to detect patterns similar to the current situation in the history of the SNR values of its links by applying the normalized cross-correlation function. The found matches are then used as the base of the prediction. Simulations have shown that fairly accurate predictions around $2~dB$ of absolute average prediction error can be achieved with XCoPred in case of appropriate parameter settings and scenarios showing clear node mobility patterns.