  We consider the channel access problem in a multi-channel opportunistic
communication system with imperfect channel sensing, where the state of each
channel evolves as a non independent and identically distributed Markov
process. This problem can be cast into a restless multi-armed bandit (RMAB)
problem that is intractable for its exponential computation complexity. A
natural alternative is to consider the easily implementable myopic policy that
maximizes the immediate reward but ignores the impact of the current strategy
on the future reward. In particular, we develop three axioms characterizing a
family of generic and practically important functions termed as $g$-regular
functions which includes a wide spectrum of utility functions in engineering.
By pursuing a mathematical analysis based on the axioms, we establish a set of
closed-form structural conditions for the optimality of myopic policy.
