Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the flourish of mobile video services, large amount of data requests from video subscribers and the necessity of assuring good user quality of experience (QoE) inevitably result in high energy consumption for network operators, giving rise to environmental as ll as financial problems. The conflict beten providing a satisfied user experience and reducing energy consumption makes it a tough job to bridge the gap beten them. Nevertheless, the “marginal effect” beten user experience and por consumption implies that a joint optimization of user experience and energy saving is possible and it will make great sense for network operators in order to maintain higher profits. , a joint optimization Resource Block (RB) and por allocation problem is formulated with three objectives, i.e., minimizing total por consumption, maximizing overall user experience and maximizing QoE fairness. To combat the contradiction of these objectives, Lexicographic method and Tchebycheff method are adopted in this paper. Hover, finding the optimal solution of the transformed single optimization problem is NP-hard due to the mixed combinatorial and nonconvex property. Therefore, an effective method is proposed, integrating evolutionary genetic algorithm (GA) and Lagrange dual method to find near optimal RB and por allocation solution. The effectiveness of the proposed scheme is validated by experiment simulations.
['Qiping Pi', 'Ying Wang', 'Ruijin Sun']
I am writing a research paper on a idea QoE-based energy saving resource allocation for video streaming in wireless networks
[{"from": "human", "value": "I am writing a research paper on a idea QoE-based energy saving resource allocation for video streaming in wireless networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the flourish of mobile video services, large amount of data requests from video subscribers and the necessity of assuring good user quality of experience (QoE) inevitably result in high energy consumption for network operators, giving rise to environmental as ll as financial problems. The conflict beten providing a satisfied user experience and reducing energy consumption makes it a tough job to bridge the gap beten them. Nevertheless, the \u201cmarginal effect\u201d beten user experience and por consumption implies that a joint optimization of user experience and energy saving is possible and it will make great sense for network operators in order to maintain higher profits. , a joint optimization Resource Block (RB) and por allocation problem is formulated with three objectives, i.e., minimizing total por consumption, maximizing overall user experience and maximizing QoE fairness. To combat the contradiction of these objectives, Lexicographic method and Tchebycheff method are adopted in this paper. Hover, finding the optimal solution of the transformed single optimization problem is NP-hard due to the mixed combinatorial and nonconvex property. Therefore, an effective method is proposed, integrating evolutionary genetic algorithm (GA) and Lagrange dual method to find near optimal RB and por allocation solution. The effectiveness of the proposed scheme is validated by experiment simulations."}]