TY - GEN
T1 - A UAV-Assisted Handover Scheme for Coverage Maximization against 5G Coverage Holes
AU - Jung, Hyeonah
AU - Rastogi, Eshita
AU - Jeong, Jaehoon Paul
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The Handover (HO) problem is widely explored by the research industry. In the dense traffic, the vehicles move at a lower speed, which means the vehicles will spend more time in the coverage holes. The absence of a communication link from the Next Generation NodeB (gNB) will degrade the Quality of Service (QoS) requirement of users. This motivates us to propose Unmanned Aerial Vehicles (UAVs) (e.g., drones) as temporary base stations to serve the traffic of User Equipments (UEs) in peak hour conditions. To overcome the HO delay, we propose a machine learning-based proactive HO scheme. In this paper, we train a Long Short-Term Memory (LSTM) model using Reference Signal Received Power (RSRP) values to predict and optimize HO decisions. Experimental results show that a UAV-assisted HO strategy can significantly enhance network performance in terms of the reduction of both Ping-Pong Rate and End-to-End Delay as performance metrics.
AB - The Handover (HO) problem is widely explored by the research industry. In the dense traffic, the vehicles move at a lower speed, which means the vehicles will spend more time in the coverage holes. The absence of a communication link from the Next Generation NodeB (gNB) will degrade the Quality of Service (QoS) requirement of users. This motivates us to propose Unmanned Aerial Vehicles (UAVs) (e.g., drones) as temporary base stations to serve the traffic of User Equipments (UEs) in peak hour conditions. To overcome the HO delay, we propose a machine learning-based proactive HO scheme. In this paper, we train a Long Short-Term Memory (LSTM) model using Reference Signal Received Power (RSRP) values to predict and optimize HO decisions. Experimental results show that a UAV-assisted HO strategy can significantly enhance network performance in terms of the reduction of both Ping-Pong Rate and End-to-End Delay as performance metrics.
UR - https://www.scopus.com/pages/publications/85184604083
U2 - 10.1109/ICTC58733.2023.10392886
DO - 10.1109/ICTC58733.2023.10392886
M3 - Conference contribution
AN - SCOPUS:85184604083
T3 - International Conference on ICT Convergence
SP - 497
EP - 502
BT - ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence
PB - IEEE Computer Society
T2 - 14th International Conference on Information and Communication Technology Convergence, ICTC 2023
Y2 - 11 October 2023 through 13 October 2023
ER -
