Adaptive modulation for finite horizon multicasting of erasure-coded data

We design an adaptive modulation scheme to support opportunistic multicast scheduling in wireless networks. Whereas prior work optimizes capacity, we investigate the finite horizon problem where (once or repeatedly) a fixed number of packets has to be transmitted to a set of wireless receivers in the shortest amount of time - a common problem, e.g., for software updates or video multicast. In the finite horizon problem, the optimum coding and modulation schemes critically depend on the recent reception history of the receivers and require a fine balance between maximizing overall throughput and equalizing individual receiver throughput. We formulate a dynamic programming algorithm that optimally solves this scheduling problem. We then develop two low complexity heuristics that perform very close to the optimal solution and are suitable for practical online scheduling in base stations. We further analyze the performance of our algorithms by means of simulation in a wide range of wireless scenarios. They substantially outperform existing solutions based on throughput maximization or favoring the user with the worst channel, and we obtain a 35% performance improvement over the former and a 100% improvement over the latter in a scenario with Rayleigh fading.