Abstract
To acquire higher network capacity, the cell selection problem is formulated based on the partially observable Markov decision process (POMDP). It observes/predicts unavailable cell loading information from those non-serving base stations and takes actions for maintaining active base station set and handover target selection. Various utility functions are designed to consider different factors in the proposed POMDP-based cell selection (POCS) schemes, including system capacity, handover time, and mobility of mobile station. With the considerations of cell load as a hidden Markov model and predicted mobility in the reward function, simulation results show that the proposed POCS schemes can outperform conventional received signal strength based and load balancing methods.
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