# Radio Environment Map and Deep Q-Learning for 5G Dynamic Point Blanking

arXiv: https://arxiv.org/abs/2209.12034 · HTML: https://mlsanity.com/paper/2209.12034/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Sep 2022.

## Built on by (most cited first, 1 of 1)

- [VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning](https://mlsanity.com/paper/2311.18741/) (2023)

## Abstract (arXiv)

Dynamic Point Blanking (DPB) is one of the Coordinated MultiPoint (CoMP) techniques, where some Base Stations (BSs) can be temporarily muted, e.g., to improve the cell-edge users throughput. In this paper, it is proposed to obtain the muting pattern that improves cell-edge users throughput with the use of a Deep Q-Learning. The Deep Q-Learning agent is trained on location-dependent data. Simulation studies have shown that the proposed solution improves cell-edge user throughput by about 20.6%.