On the detection and solution of coverage holes in 5G networks through relay user equipment: a combined DBSCAN and deep-Q network approach

This paper proposes a model to detect and solve coverage holes in 5G Radio Access Network (RAN) deployments operating with millimeter waves. The proposed model utilizes a DBSCAN-based detector to identify coverage constrained areas and then proposes the use of Relay User Equipment (RUE) capabilities to extend the RAN coverage. To optimize the activation and deactivation of RUEs, a Deep-Q-Network-based algorithm is proposed, aiming to improve spectral efficiency and decrease the outage probability experienced by network users. The obtained results demonstrate the effectiveness of the model in accurately detecting coverage constrained areas and efficiently solving these issues by means of an effective RUE activation, leading to significant improvements in network performance while minimizing the time that RUEs remain in active mode, which implies potential benefits for MNOs and UE holders and significant energy savings.
This paper is part of ARTIST project (ref. PID2020- 115104RB-I00) funded by MCIN/AEI/10.13039/ 501100011033. The work is also funded by the Spanish Ministry of Science and Innovation under grant ref. PRE2018-084691. The work of Irene Vilà has also been funded by European Union-NextGenerationEU, Spanish Ministry of Universities and the Plan for Recovery, Transformation and Resilience, through the call for Margarita Salas Grants of the Universitat Politècnica de Catalunya (ref. 2022UPC-MSC- 94079)
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