Stochastic Optimization for Variable Rate Applications With Time-Varying Statistics
A scheme to provide Quality of Service for buffered variable rate applications is presented that is largely indiscriminate to channel distributions, indeed will track changing statistics, and is effectively spectrum optimal. The solution is based on the framework of Full Recourse Optimization with Expected Constraints where the optimal solution is learned through updates of the Lagrange multiplier. The convergence speed and nearness to optimality are found, and the buffer stability probabilities are met. Analysis and simulations are provided to validate the scheme's performance.