Handover management for mmWave networks with proactive performance prediction using camera images and deep reinforcement learning
Y Koda, K Nakashima, K Yamamoto… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
For millimeter-wave networks, this paper presents a paradigm shift for leveraging time-
consecutive camera images in handover decision problems. While making handover …
consecutive camera images in handover decision problems. While making handover …
Reinforcement learning based predictive handover for pedestrian-aware mmWave networks
This paper discusses the optimal decision-making for predictive handover in millimeter-
wave (mmWave) communication networks using information of pedestrian movement. In …
wave (mmWave) communication networks using information of pedestrian movement. In …
Multi-agent deep reinforcement learning for distributed handover management in dense mmWave networks
The dense deployment of millimeter wave small cells combined with directional
beamforming is a promising solution to enhance the network capacity of the current …
beamforming is a promising solution to enhance the network capacity of the current …
Proactive handover based on human blockage prediction using RGB-D cameras for mmWave communications
Y Oguma, T Nishio, K Yamamoto… - IEICE Transactions on …, 2016 - search.ieice.org
To substantially alleviate the human blockage problem in mmWave communications, this
paper proposes a proactive handover system based on human blockage prediction using …
paper proposes a proactive handover system based on human blockage prediction using …
Deep reinforcement learning based handover management for millimeter wave communication
The Millimeter Wave (mm-wave) band has a broad-spectrum capable of transmitting multi-
gigabit per-second date-rate. However, the band suffers seriously from obstruction and high …
gigabit per-second date-rate. However, the band suffers seriously from obstruction and high …
Learning-based load balancing handover in mobile millimeter wave networks
S Khosravi, HS Ghadikolaei… - GLOBECOM 2020-2020 …, 2020 - ieeexplore.ieee.org
Millimeter-wave (mmWave) communication is a promising solution to the high data rate
demands in the upcoming 5G and beyond communication networks. When it comes to …
demands in the upcoming 5G and beyond communication networks. When it comes to …
Proactive received power prediction using machine learning and depth images for mmWave networks
T Nishio, H Okamoto, K Nakashima… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
This study demonstrates the feasibility of proactive received power prediction by leveraging
spatiotemporal visual sensing information towards reliable millimeter-wave (mmWave) …
spatiotemporal visual sensing information towards reliable millimeter-wave (mmWave) …
Prediction-based conditional handover for 5G mm-wave networks: A deep-learning approach
Conditional handover (CHO) is one of several promising mobility enhancements in 5G
networks. By making preparation decisions earlier than in LTE HO, CHO can provide an …
networks. By making preparation decisions earlier than in LTE HO, CHO can provide an …
Intelligent handover decision scheme using double deep reinforcement learning
Handovers (HOs) have been envisioned to be more challenging in 5G networks due to the
inclusion of millimetre wave (mm-wave) frequencies, resulting in more intense base station …
inclusion of millimetre wave (mm-wave) frequencies, resulting in more intense base station …
Learning-based handover in mobile millimeter-wave networks
S Khosravi, H Shokri-Ghadikolaei… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Millimeter-wave (mmWave) communication is considered as a key enabler of ultra-high data
rates in the future cellular and wireless networks. The need for directional communication …
rates in the future cellular and wireless networks. The need for directional communication …
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