Resource Allocation for Video Streaming Using Channel Condition Prediction in 3G Networks

3G network is a widely employed technology in today’s world. 3G network efficiently supports wireless traffic in static as well as mobile topology. This network is used in transmitting various types of traffic such data, audio, video, etc. Nowadays, video transmission has become a major part of the overall traffic due to its higher demands. Video streaming is used in several applications and resource allocation for this purpose is critical as the channel conditions in 3G network are highly varying. In this paper, we propose to develop a Resource Allocation technique for Video Streaming Using Channel Condition Prediction in 3G networks. In this technique, the channel conditions are predicted and then the video services are provided. To reduce the load on the system, an optimization model is employed.