Deep Reinforcement Learning Based UAV Assisted SVC Video Multicast

• Published in: Ji suan ji ke xue Vol. 48; no. 9; pp. 271 - 277
• Main Author: CHENG Zhao-wei, SHEN Hang, WANG Yue, WANG Min, BAI Guang-wei
• Format: Journal Article
• Language: Chinese
• Published: Editorial office of Computer Science 01.09.2021
• Subjects: scalable video coding(svc)|multicast|deep reinforcement learning|unmanned aerial vehicles|mobile internet
• ISSN: 1002-137X
• DOI: 10.11896/jsjkx.201000078

In this paper,a flexible video multicast mechanism assisted by the UAV base station is proposed.In combination with SVC encoding,the dynamic deployment and resource allocation of UAV are considered jointly in order to maximize the overall number of enhancement layers received by users.The traditional heuristic algorithm is difficult to deal with the complexity of user movement,considering that the user movement within the range of macro station will change the network topology.To this end,the DDPG algorithm based on deep reinforcement learning is used to train the neural network to decide the optimal location and bandwidth allocation proportion of UAV.After the model converges,the learning agent can find the optimal UAV deployment and bandwidth allocation strategy in a short time.The simulation results show that the proposed scheme achieves the expected goal and is superior to the existing scheme based on Q-learning.