Structural Results on the Optimal Transmission Scheduling Policies and Costs for Correlated Sources and Channels

The problem of transmission adaptation over a correlated time-varying wireless channel is formulated as a Constrained Markov Decision Process. The model includes a transmission buffer and finite state Markov model for time-varying radio channel and incoming traffic. This crosslayer optimization problem is formulated as to minimize the transmission cost (e.g. power or bit-error-rate) under the constraint on a buffer cost such as the transmission delay. Under the assumptions on submodularity and convexity of the cost function it is shown that the optimal randomized policy is monotonically increasing with the increase of the buffer state.