Stochastic Cooperative Optimization for Multicast Scheduling in Heterogeneous and Green 5G Networks

Multicast is able to satisfy multiple identical requests by a multicast stream, which can effectively reduce network energy consumption and service delay. Combined with edge caching, multicast can fully exploit its advantages and is becoming one of the most promising technologies to realize tremendous data transmission in 5G networks. As an important theme of multicast technology, multicast scheduling has attracted extensive attention. However, most of them only consider the scheduling in a single base station and ignore the different delay requirement of services. In this paper, we consider cooperative multicast scheduling between multiple base stations in cache-enabled 5G networks, aiming to satisfy user demands while minimizing energy consumption. We propose a novel pending request queue model related to delay requirement, based on which we formulate the cooperative multicast scheduling problem. Then we transform the problem into Lyapunov stochastic optimization and propose an on-line centralized algorithm to obtain the optimal strategy. Considering some scenarios where global information is unavailable, we further propose a distributed algorithm which has close performance but much lower complexity. Extensive simulations have been conducted to verify that our algorithms have better performance than several state-of-art algorithms, including both energy consumption and service delay.