Blockage Prediction in Directional mmWave Links Using Liquid Time Constant Network
This work addresses the need for reliable and low-latency communication in mmWave networks, though it appears incremental as it applies an existing LTC method to a new application.
The paper tackles the problem of predicting future blockages in directional millimeter wave links by using a liquid time constant network with only received signal power as input, achieving over 97.85% accuracy without scenario-specific data or retraining.
We propose to use a liquid time constant (LTC) network to predict the future blockage status of a millimeter wave (mmWave) link using only the received signal power as the input to the system. The LTC network is based on an ordinary differential equation (ODE) system inspired by biology and specialized for near-future prediction for time sequence observation as the input. Using an experimental dataset at 60 GHz, we show that our proposed use of LTC can reliably predict the occurrence of blockage and the length of the blockage without the need for scenario-specific data. The results show that the proposed LTC can predict with upwards of 97.85\% accuracy without prior knowledge of the outdoor scenario or retraining/tuning. These results highlight the promising gains of using LTC networks to predict time series-dependent signals, which can lead to more reliable and low-latency communication.