Wireless link prediction and triggering using modified OrnsteinUhlenbeck jump diffusion process
Through time domain observation, typical wireless signal strength values seems to exhibit some forms of mean-reverting and discontinuous jumps behaviour. Motivated by this fact, we propose a wireless link prediction and triggering (LPT) technique using a modified mean-reverting OrnsteinUhlenbeck (OU) jump diffusion process. The proposed technique which we refer as OU-LPT is an integral component of wireless mesh network monitoring system developed by ICT FP7 CARrier grade wireless MEsh Network project. In particular, we demonstrate how this technique can be applied in the context of wireless mesh networks to support link switching or handover in the event of predicted link degradation or failure. The proposed technique has also been implemented and evaluated in a real-time experimental testbed. The results show that OU-LPT technique can significantly enhance the reliability of wireless links by reducing the rate of false triggers compared to a conventional linear prediction technique and therefore offers a new direction on how wireless link prediction, triggering and switching process can be conducted in the future.
link prediction wireless mesh networks monitoring system link triggering data analysis