QoE-aware resource allocation for adaptive device-to-device video streaming PROJECT TITLE :QoE-aware resource allocation for adaptive device-to-device video streamingABSTRACT:The continuing advances within the storage and transmission abilities of user equipment have created it doable to share videos through device-to-device Communications, that could be an economical way to reinforce the capability of cellular network to provide wireless video services. In adaptive D2D video streaming, user expertise is greatly influenced by the quality and fluency of the video, that is stricken by the D2D link???s quality. Additionally, the standard of D2D links relies on the resource allocation scheme for D2D pairs. To improve the quality of experience in D2D video streaming, we propose a QoE-aware resource allocation theme for adaptive D2D video streaming. The QoE-aware resource allocation scheme has the ability to cater to the user expertise in adaptive video steaming while considering the co-channel interference derived from frequency reuse in D2D Communications. Specifically, a dynamic network scheduling problem is formulated and solved, with the target of maximizing the video quality whereas maintaining the long-term stable performance of fluency throughout video playback. In depth numerical results demonstrate that the proposed QoE-aware resource allocation scheme outperforms the QoE-oblivious resource allocation scheme. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest A Novel Dynamic-Weighted Probabilistic Support Vector Regression-Based Ensemble for Prognostics of Time Series Data Highly Sensitive Tactile Sensing Array Realized Using a Novel Fabrication Process With Membrane Filters
