Traffic aided opportunistic scheduling for wireless networks: Algorithms and performance bounds

In multiuser wireless networks, opportunistic scheduling can improve the system throughput and thus reduce the total completion time. In this paper, we explore the possibility of reducing the completion time further by incorporating traffic information into opportunistic scheduling. More specifically, we first establish convexity properties for opportunistic scheduling with file size information. Then, we develop new traffic aided opportunistic scheduling (TAOS) schemes by making use of file size information and channel variation in a unified manner. We also derive lower bounds and upper bounds on the total completion time, which serve as benchmarks for examining the performance of the TAOS schemes. Our results show that the proposed TAOS schemes can yield significant reduction in the total completion time. The impact of fading, file size distributions, and random arrivals and departures, on the system performance, is also investigated. In particular, in the presence of user dynamics, the proposed TAOS schemes perform well when the arrival rate is reasonably high.