Throughput versus Fairness: Channel-Aware Scheduling in Multiple Antenna Downlink

Abstract

Channel aware and opportunistic scheduling algorithms exploit the channel knowledge and fading to increase the average throughput. Alternatively, each user could be served equally in order to maximize fairness. Obviously, there is a tradeoff between average throughput and fairness in the system. In this paper, we study four representative schedulers, namely the maximum throughput scheduler (MTS), the proportional fair scheduler (PFS), the (relative) opportunistic round robin scheduler (ORS), and the round robin scheduler (RRS) for a space-time coded multiple antenna downlink system. The system applies TDMA based scheduling and exploits the multiple antennas in terms of spatial diversity. We show that the average sum rate performance and the average worst-case delay depend strongly on the user distribution within the cell. MTS gains from asymmetrical distributed users whereas the other three schedulers suffer. On the other hand, the average fairness of MTS and PFS decreases with asymmetrical user distribution. The key contribution of this paper is to put these tradeoffs and observations on a solid theoretical basis. Both the PFS and the ORS provide a reasonable performance in terms of throughput and fairness. However, PFS outperforms ORS for symmetrical user distributions, whereas ORS outperforms PFS for asymmetrical user distribution.