Exploiting User Demand Diversity in Heterogeneous Wireless Networks

摘要: Radio resource management (RRM) is crucial for improving utilization in heterogeneous wireless networks. Existing work attempts to exploit the network diversity gain throughput improvement users, which, however, neglects impact of user demand on RRM. Armed with idea that ultimate goal communications serve users personalized demand, we introduce another dimension potential performance gain, gain. This derives from elaborate matching between and radio resource, which can not be directly attained existing throughput-centric optimization due users' blindness maximizing throughput. Aiming at obtaining this propose demand-centric optimization, where seek maximize quality experience (QoE), instead shift enables us a novel game formulation, QoE game. We derive condition existence equilibrium, validate distributed equilibrium learning algorithm. Finally, cloud assisted framework proposed accommodate algorithm significantly reduced cost. Simulation results effectiveness system efficiency fairness.