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We propose to use a liquid time constant (LTC) network to predict the futureblockage status of a millimeter wave (mmWave) link using only the receivedsignal power as the input to the system. The LTC network is based on anordinary differential equation (ODE) system inspired by biology and specializedfor near-future prediction for time sequence observation as the input. Using anexperimental dataset at 60 GHz, we show that our proposed use of LTC canreliably predict the occurrence of blockage and the length of the blockagewithout the need for scenario-specific data. The results show that the proposedLTC can predict with upwards of 97.85\% accuracy without prior knowledge of theoutdoor scenario or retraining/tuning. These results highlight the promisinggains of using LTC networks to predict time series-dependent signals, which canlead to more reliable and low-latency communication.

Blockage Prediction in Directional mmWave Links Using Liquid Time Constant Network