LAUSR

One of the most critical challenges of future generation cellular networks is to meet the unprecedented cellular traffic demands from mobile applications. mmWave has large chunks of spectrum and is a promising candidate to satisfy the ever-increasing traffic demand. Unfortunately, the characteristic that mmWaves have high attenuation against physical objects and even atmosphere hinder its feasibility. High gain directional antennas are required to combat the attenuation. However, user mobility might change the signal direction, introducing physical objects in the line-of-sight of the signal. Additionally, user mobility might also make two directional signals interfere with each other. The blockage and interference incidents must be handled with care. In this paper, we propose to predict blockage and interference incidents so that countermeasures can be applied in advance. We let the cells collect the fingerprints, which are transmission parameters when blockage and interference incidents happen. The cells attempt to predict blockage and interference incidents by matching their current transmission parameters with the collected fingerprints. When a user is moving, and the cell's transmission parameters are approaching a fingerprint, the HetNet takes necessary actions to mitigate interference or avoid disconnection before it happens. Our results show that for typical indoor scenarios, most of the blockage and interference can be predicted, and taking countermeasures in advance improves overall performance.