In recent years, multiple-input multiple-output (MIMO) channel models for crowded areas, such as indoor offices, shops, and outdoor hotspot environments, have become a topic of significant interest. In such crowded environments, propagation paths are frequently shadowed by moving objects, such as pedestrians or vehicles. These shadowing effects can cause time variations in the delay and angle-of-arrival (AoA) characteristics of a channel. In this paper, we propose a method for modeling the shadowing effects of pedestrians in a cluster-based channel model. The proposed method uses cluster power variations to model the time-varying channel properties. We also propose a novel method for estimating the cluster power variation properties from measured data. In order to validate our proposed method, channel sounding in the 3GHz band is conducted in a cafeteria during lunchtime. The results for the K parameter, delay spreads, and AoA azimuth spreads are compared for the measured data and the channel data generated using the proposed method. The results indicate that the time-varying delay-AoA characteristics can be effectively modeled using our proposed method.