A resource allocation scheme using adaptive-network-based fuzzy control for mobile multimedia networks

Sophisticated and robust resource management is an essential issue in future wireless systems which will provide a variety of application services. In this paper, we employ an adaptive-network-based fuzzy inference system (ANFIS) to control the, resource allocation for mobile multimedia networks. ANFIS, possessing the advantages of expert knowledge of fuzzy logic system and learning capability of neural networks, can provide, a systematic approach to finding appropriate parameters for the Sugeno fuzzy model. The fuzzy resource allocation controller (FRAC) is designed in a two-layer architecture and selects property the capacity requirement of new call request, the capacity reservation for future handoffs, and the air interface performance as input linguistic variables. Therefore, the statistical multiplexing gain of mobile multimedia networks can be maximized in the FRAC. Simulation results indicate that the proposed FRAC Call keep the handoff call blocking rate low without jeopardizing the new call blocking rate. Also, the FRAC can indeed guarantee quality of service (QoS) contracts and achieve higher system performance according to network dynamics, compared with the guard channel scheme and Expected Max strategy [7].