Multimedia traffic is predicted to account for 82% of the total data traffic by the year 2020. With the increasing popularity of video streaming applications like YouTube, Netflix, Amazon Prime Video, popular video content is often required to be delivered to a large number of users simultaneously. Multicast transmission can be used for catering to such applications efficiently. The common content can be transmitted to the users on the same resources resulting in considerable resource conservation. This paper proposes various schemes for efficient grouping and resource allocation for multicast transmission in LTE. The optimal grouping and resource allocation problems are shown to be NP-hard and so, we propose heuristic algorithms for both these problems. We also formulate a Simulated Annealing based algorithm to approximate the optimal resource allocation for our problem. The LP-relaxation based resource allocation proposed by us results in allocations very close to the estimated optimal.
翻译:预计到2020年多媒体通信量将占数据流量总量的82%,随着YouTube、Netflix、亚马逊原始视频等视频流应用越来越受欢迎,通常需要同时向大量用户提供流行视频内容。多播传输可以高效地用于满足这些应用。共同内容可以在同一资源上传送给用户,从而节省大量资源。本文件提出了多种计划,为LTE的多播传播高效分组和资源分配。最佳组合和资源分配问题被证明是硬性NP,因此,我们为这两个问题提出了超自然算法。我们还制定了一种模拟的安妮算法,以近似我们问题的最佳资源分配。我们提议的基于LP的放松资源分配导致分配非常接近估计的最佳分配。