Generalized Queue-Aware Resource Management and Scheduling for Wireless Communications

The general problem of a queue-aware radio resource management and scheduling design is investigated for wireless communications under quasi-static fading channel conditions. Based on an analysis of the source buffer queuing system, the problem is formulated as a constrained nonlinear discrete programming problem. The state transition matrix of the queuing system determined by the queue-aware scheduler is shown to have a highly dynamic structure, so that the conventional matrix analysis and optimization tools are not applicable. By reformulating the problem into a nonlinear integer programming problem on an integer convex set, a direct search approach is considered. Two types of search algorithms, gradient based and gradient-free, are investigated. An integer steepest-descent search with a sub-sequential interval search algorithm and a constrained discrete Rosenbrock search (CDRS) algorithm is proposed to solve the nonlinear integer problem. Both algorithms are shown to have low complexity and good convergence. The numerical results for a single user resource allocation are presented, which show that both algorithms outperform equal partitioning and random partitioning queue-aware scheduling. The dynamic programming (DP) solution given by the relative value iteration algorithm, which provides the true optima but has high complexity, is used as a benchmark. In the majority of the numerical examples, the performance of the CDRS algorithm is almost identical to that of the DP approach in terms of both the average queue length minimization and the average packet blocking plus packet retransmission minimization, but it is less complex, and thus has better scalability.