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Robust And Optimal Opportunistic Scheduling For Downlink 2-Flow Network Coding With Varying Channel Quality and Rate Adaptation
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 of
each flow. However, the corresponding scheduling solution (when assuming
dynamic arrivals instead and requiring bounded delay) is still nascent.
For the 2-flow downlink scenario, we propose the first opportunistic INC +
scheduling solution that is provably optimal for time-varying channels, i.e.,
the corresponding stability region matches the optimal Shannon capacity.
Specifically, 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, which, with
the help of the new INC operation, can robustly and optimally adapt to
time-varying channel quality. We then show that the proposed algorithm can be
easily extended for rate adaptation and it again robustly achieves the optimal
throughput. A byproduct of our results is a scheduling scheme for stochastic
processing networks (SPNs) with random departure, which relaxes the assumption
of deterministic departure in the existing results. The new SPN scheduler could
thus further broaden the applications of SPN scheduling to other real-world
scenarios
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