  Recently, low-complexity and distributed Carrier Sense Multiple Access
(CSMA)-based scheduling algorithms have attracted extensive interest due to
their throughput-optimal characteristics in general network topologies.
However, these algorithms are not well-suited for serving real-time traffic
under time-varying channel conditions for two reasons: (1) the mixing time of
the underlying CSMA Markov Chain grows with the size of the network, which, for
large networks, generates unacceptable delay for deadline-constrained traffic;
(2) since the dynamic CSMA parameters are influenced by the arrival and channel
state processes, the underlying CSMA Markov Chain may not converge to a
steady-state under strict deadline constraints and fading channel conditions.
  In this paper, we attack the problem of distributed scheduling for serving
real-time traffic over time-varying channels. Specifically, we consider
fully-connected topologies with independently fading channels (which can model
cellular networks) in which flows with short-term deadline constraints and
long-term drop rate requirements are served. To that end, we first characterize
the maximal set of satisfiable arrival processes for this system and, then,
propose a Fast-CSMA (FCSMA) policy that is shown to be optimal in supporting
any real-time traffic that is within the maximal satisfiable set. These
theoretical results are further validated through simulations to demonstrate
the relative efficiency of the FCSMA policy compared to some of the existing
CSMA-based algorithms.
