Optimized Opportunistic Multicast Scheduling over Cellular Networks

Abstract

The design of optimal opportunistic multicast scheduling (OMS) that maximizes the throughput of cellular networks is investigated. In a cellular network, the base station (BS) transmits the same information to multiple users within a cell. Recently, Gopala et al. proposed a median-user static OMS scheme in which a BS selects and broadcasts to the best 50% users in each transmission until all users are served. This scheduling scheme has been shown to exploit both the multiuser diversity and the multicasting gain simultaneously. In this work, we examine the optimal user selection ratio in each transmission. Based on extreme value theory, we first derive the limiting distribution of the maximum decodable rate of the M-th best user and the corresponding average number of transmissions required to serve all users. Then, the optimal selection ratio is established by maximizing the average network throughput. Furthermore, a dynamic selection algorithm is proposed to adjust the user selection ratio adaptively in each transmission. It is shown by simulation results that the OMS scheme with optimized static and dynamic selected ratios outperform the conventional unicast, multicast and the median-user static OMS schemes.