Abstract
This paper has proposed a user-density-based coverage optimization technique for ultra-dense cellular networks. Antenna tilting is a promising coverage optimization technique to be used in 5G networks, that significantly improve the signal to interference plus noise ratio (SINR) by choosing the appropriate angle of tilt. In this paper, the cellular coverage has been optimized for scattered user densities/user hotspots using an adaptive antenna tilting mechanism that steers the beams towards the temporal hot spot in the coverage area. The proposed method has the competence to improve the desired SINR level and coverage area for a group of users rather than a single user. In this work, a reinforcement learning (RL) algorithm has been implemented to optimize the tilt angle. The performance of the proposed technique has been evaluated in the simulation platform considering a three-sectored multicellular mobile network where the groups of user clusters are distributed randomly. The result confirms the improvement in RSS and SINR values in the group of users having high density with maximum user satisfaction.
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