Autors: Samal, S.R., Dandanov, N. G., Bandopadhaya, S., Poulkov, V. K.
Title: Adaptive Antenna Tilt for Cellular Coverage Optimization in Suburban Scenario
Keywords: Self-organizing networks (SON); Coverage optimization; Antenna tilt angle; Reinforcement learning; Cell edge users

Abstract: Radio coverage optimization is a critical issue for mobile network operators (MNO) in the deployment of future generation cellular networks, especially on users at cell edge. The key factor that influences the coverage in mobile networks is mostly related to the configuration of the antennas and especially the angle of antenna tilt. The received signal power in a cell can be increased with proper antenna tilt, causing a significant improvement in signal-to-interference-plus-noise ratio (SINR) at the cell edge. This also leads to reduction in interference towards other cells. In this paper, a method for coverage optimization using base station antenna electrical tilt in mobile networks for suburban scenario is proposed. The main focus is on the downlink power setting by using electrical antenna tilt in the mobile network. This proposed solution uses reinforcement learning technique and the simulation results shows that the proposed algorithm can used to improve overall..

References

    Issue

    in Proceedings of International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making, Odisha, India, 19-20 December 2019; Biologically Inspired Techniques in Many-Criteria Decision Making, Learning and Analytics in Intelligent Systems, vol. 10, pp. 240-249, 2020, Switzerland, Springer, DOI 10.1007/978-3-030-39033-4_22

    Copyright Springer Nature Switzerland AG

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Web of Science