  Distributed Opportunistic Scheduling (DOS) techniques have been recently
proposed to improve the throughput performance of wireless networks. With DOS,
each station contends for the channel with a certain access probability. If a
contention is successful, the station measures the channel conditions and
transmits in case the channel quality is above a certain threshold. Otherwise,
the station does not use the transmission opportunity, allowing all stations to
recontend. A key challenge with DOS is to design a distributed algorithm that
optimally adjusts the access probability and the threshold of each station. To
address this challenge, in this paper we first compute the configuration of
these two parameters that jointly optimizes throughput performance in terms of
proportional fairness. Then, we propose an adaptive algorithm based on control
theory that converges to the desired point of operation. Finally, we conduct a
control theoretic analysis of the algorithm to find a setting for its
parameters that provides a good tradeoff between stability and speed of
convergence. Simulation results validate the design of the proposed mechanism
and confirm its advantages over previous proposals.
