Spatial and Temporal Contextual Multi-Armed Bandit Handovers in Ultra-Dense mmWave Cellular Networks

Abstract

Although millimeter wave (mmWave) is a promising technology in 5G communication, its severe path attenuation and susceptibility to line-of-sight (LOS) blockage result in much more unpredictable outages than traditional technologies. This special propagation property raises a significant challenge to the mobility management in mmWave cellular networks. Since conventional handover policies purely rely on the measurement of signal strength, they would cause a large number of unnecessary handovers due to the frequent short-term LOS blockage by obstacles, imposing high signaling and energy overhead. In this paper, we propose two novel handover mechanisms to reduce unnecessary handovers by carefully deciding the next base station (BS) a user should handover to, so that the new user-BS connection after the handover can last as long as possible. Without prior knowledge of user’s mobility and environment, the proposed handover mechanisms exploit the empirical distribution of user’s post-handover trajectory and LOS blockage, learned online through a multi-armed bandit (MAB) framework. Depending on the contexts extracted from RSS information, two different MAB problems for handover are formulated, which focus on spatial and space-time contexts, respectively, The results of numerical simulations demonstrate that the proposed contextual handover mechanisms significantly outperform existing counterparts on reducing handovers in all simulated scenarios.