Enhancement of wireless bandwidth utilization through user´s QoE

Quality of Experience (QoE) measures a user´s satisfaction with a service delivery. However QoE is a very subjective measure and is context dependent, making it difficult for a service provider to estimate and optimize user´s QoE. In this paper, we look at how the provider can maximize QoE by optimizing wireless bandwidth allocation, especially for mobile cloud applications. The multi-stimuli version of the “IQX” hypothesis is used to model the QoE of a user, and this model is used in formulation of a nonlinear optimization problem, which is solved using NSGA-II. Simulations using realistic parameters based on 802.11n demonstrate a reduction in the required bandwidth by as much as 33% (i.e., more users can be accommodated by the system), while maintaining the same level of QoE. Our evolutionary-algorithm-based approach is able to discover the optimal bandwidth allocation. The problem of equalizing user QoE is explored and a tradeoff between QoE and fairness is studied, while being characterized using a Pareto front.