QoE Optimization With User Intent in Software-Defined Heterogeneous Wireless Network

Due to the Quality-of-Experience (QoE) degradation caused by the mismatch of supply and demand rate in heterogeneous wireless network (HWN), we introduce the idea of intent driven network (IDN) to associate the user intent (UI) with the network QoE strategy under a software-defined framework. We specifically construct a UI-aware QoE model to quantify the effect of dynamic request rate on actual QoE. Based on this model, we formulate a QoE maximization problem to adaptively match supply-demand rates. As a multivariable combinatorial optimization problem, we firstly present a robust algorithm based on simulated-annealing (SA) to obtain the approximate optimal solution as much as possible. Moreover, we present a genetic algorithm (GA) on the basis of the initial SA algorithm to improve the search accuracy of each step for more practical application. Compared with three schemes without UI interference, our approaches raise average QoE by at least 42.1%.