Cross-Layer Optimization of Wireless Video Multicast Systems

Abstract

Multimedia data traffic occupies more than 70% of the internet traffic and it increases even more. In addition to this, Virtual Reality (VR) data traffic is increasing very fast. To provide the good quality of the multimedia service, huge amount of resource is needed because users’ service experience usually proportional to the video rates they can receive. Moreover, the variation of the bandwidth also affects to the users’ experience. Therefore, it is necessary to apply the wireless transmission scheme that has high spectral efficiency and the video rate adaptation to provide the best quality to the users. Multicast system is one of the technologies that can improve the spectral efficiency, and DASH is one of the most popular video rate adaptation platforms. Dynamic Adaptive Streaming over HTTP (DASH) is a fast growing video streaming platform, which enables adaptive rate selection based on channel conditions. File Delivery over Unidirectional Transport (FLUTE) further enables multicasting of the DASH segments over LTE eMBMS systems. In this paper, an optimal DASH-multicasting solution is proposed to allow more DASH clients in an LTE network to receive better videos by optimizing the resource allocation, application-layer Forward Error Correction (FEC) code rate and modulation and coding scheme (MCS) selection of each multicasting group, which corresponds to a FLUTE session. Multiple FLUTE sessions are considered to deliver multiple videos, each with different video rates, for enhancing the overall utility. We have applied the convex optimization method to find the optimal resource allocation in terms of utility for multiple FLUTE sessions. We also find the optimal FEC code rates to add redundancies to protect the video segments for each FLUTE session. Moreover, an efficient MCS selection is introduced to reduce the complexity of the algorithm. Simulation results, with realistic LTE parameters, are shown to prove the proposed scheme is optimal, with more DASH clients receiving better video representations within limited resources when compared to other existing algorithms. 360-degree videos for Virtual Reality (VR) applications are getting more popular because of their diverse applications. However, VR videos usually need more bandwidth than conventional videos to provide the same quality of experience (QoE). Tiled videos can help save bandwidth by selecting lower quality encoding for the tiles with lower probability of viewing. Dynamic Adaptive Streaming over HTTP (DASH) enables the adaptive rate selection of tiles based on the channel conditions. Multicasting also can help save bandwidth, since many users share the spectrum when they request the same video contents. In this paper, we formulate the utility maximization problem to find which tiles should have which video representations to satisfy the most users in multicasting groups using limited resources. A cross-layer optimization framework, which includes user grouping, resource allocation, and the tile-based rate-selection algorithms, is proposed to maximize the total utility among all users. Saliency information extracted from the videos is used to find the tiles which most users may be interested in. Simulation results show that the proposed cross-layer optimization framework can achieve a higher utility than the broadcasting solution or existing multicast solutions.