This paper considers the downlink traffic from a base station to two different clients. When assuming infinite backlog, it is known that inter-session network coding (INC) can significantly increase the throughput. However, the corresponding scheduling solution (when assuming dynamic arrivals instead and requiring bounded delay) is still nascent. For the two-flow downlink scenario, we propose the first opportunistic INC + scheduling solution that is provably optimal for timevarying channels, i.e., the corresponding stability region matches the optimal Shannon capacity. In particular, we first introduce a new binary INC operation, which is distinctly different from the traditional wisdom of XORing two overheard packets. We then develop a queue-length-based scheduling scheme and prove that it, with the help of the new INC operation, achieves the optimal stability region with time-varying channel quality. The proposed algorithm is later generalized to include the capability of rate adaptation. Simulation results show that it again achieves the optimal throughput with rate adaptation. A byproduct of our results is a scheduling scheme for stochastic processing networks with random departure, which relaxes the assumption of deterministic departure in the existing results. Index Terms-Network coding, rate adaptation, network scheduling, stochastic processing networks, time varying channels, buffer management.
While Kuo and Wang REF proposed an opportunistic scheduling solution that is provably optimal for time varying channels, using the corresponding stability region to match the optimal Shannon capacity.
Robust and Optimal Opportunistic Scheduling for Downlink Two-Flow Network Coding With Varying Channel Quality and Rate Adaptation
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Computer Science Mathematics