Dynamic Coding and Rate-Control for Serving Deadline-Constrained Traffic over Fading Channels

We study the problem of optimal dynamic coding and rate-control for broadcasting deadline-constrained traffic with average delivery ratio constraints over time-varying wireless channels. In particular, we propose and analyze a novel policy that utilizes a combination of pricing and finite-horizon dynamic programming strategies to jointly optimize the operation of the following two components: (i) a dynamic rate allocation policy, which manages the incoming traffic flow rates so as to maximize their weighted sum; (ii) and a dynamic coding window selection policy, which satisfies the flows' individual delivery ratio requirements. Our heuristic fluid analysis of the resulting stochastic network operation indicates that our joint policy maximizes the weighted sum of the deadline-constrained flow throughput subject to heterogeneous delivery ratio requirements imposed on them. We also apply these general results to an important cellular downlink scenario with and without network coding capabilities to study its behavior under various conditions. Our simulations reveal that the dynamic coding strategy outperforms the optimal static coding strategy by opportunistically exploiting the statistical variations in the arrival and channel processes.