Joint multicast scheduling and user association for DASH-based video streaming over heterogeneous cellular networks

Abstract

Dynamic Adaptive Streaming over HTTP (DASH) is a promising technology for cellular network operators to efficiently launch video services. With its recent standardization in LTE networks, multicast also appears as an efficient method to deliver large amount of multimedia data. In this paper, we investigate the joint optimization of multicast scheduling and user association for DASH-based video streaming over heterogeneous cellular networks (HetNets). We transform the joint optimization problem into a subgrouping problem. The idea of subgrouping is adopted to split the multicast users into subgroups based on the allocated video version and the serving base station of each user, which can be jointly optimized according to user channel conditions. The main challenge is the high complexity in selecting the optimal subgroup configuration. To tackle this challenge, we propose an exhaustive search scheme (ESS) in a reduced search space by exploiting the characteristics of multicast transmission as well as modulation and coding scheme (MCS). Moreover, we propose a genetic algorithm-based subgrouping algorithm to further reduce the complexity. Simulation results demonstrate the effectiveness of the proposed algorithms.