A time-scale decomposition approach for efficient wireless resource utilization with minimum performance guarantees

Wireless channels are error-prone and susceptible to several kinds of interference from different time scales, causing difficulties in the support of real-time multimedia services. This paper investigates the resource optimization and scheduling of wireless networks through a time-scale decomposition approach. We decompose the dynamics of time-varying wireless channel conditions into random processes in two different time scales and deal with the two time scales by two different algorithms: the resource optimizer optimizes the sum of utilities in the slowly changing time scale, and the slot scheduler exploits the efficiency in the highly variable time scale. Our scheme can obtain high system utilization and provide a minimum service guarantee simultaneously. Simulation results show that our scheme can improve substantially the performance and efficiency.