Abstract
We present a Distributional Reinforcement Learning (DRL) empowered downlink power control algorithm for voice over LTE (VoLTE). We mainly focus on closed-loop power control with small cells serving an indoor environment. We model the power control problem using DRL to efficiently manage the uncertainty in the function approximation process used to evaluate the power control decisions. The proposed DRL-based power control algorithm greatly improves the performance w.r.t. Fixed Power Allocation and Deep Q-Networks-based approaches in terms of voice calls retainability.
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Koulali, S., Derfouf, M., Koulali, MA., Barboucha, M. (2023). Distributional Reinforcement Learning for VoLTE Closed Loop Power Control in Indoor Small Cells. In: Sabir, E., Elbiaze, H., Falcone, F., Ajib, W., Sadik, M. (eds) Ubiquitous Networking. UNet 2022. Lecture Notes in Computer Science, vol 13853. Springer, Cham. https://doi.org/10.1007/978-3-031-29419-8_15
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DOI: https://doi.org/10.1007/978-3-031-29419-8_15
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