User adaptive QoS aware selection method for cooperative heterogeneous wireless systems: A dynamic contextual approach

• Joint network and user adaptive selection to dynamically configure the network.
• Two new notions of population payoffs: heterogeneous and homogeneous payoff.
• Formulating evolutionary game problem using new Inverse Cumulative Ranking.
• Our Region of Interest scheme reduces the complexity of evolutionary game by 58%.

This paper proposes an adaptive realistic mechanism for joint network and user selection in cooperative wireless network environments. We present a novel optimization utility to incorporate the quality-of-service (QoS) dynamics of the available networks along with heterogeneous attributes of each user. The joint network and user selection is modelled by an evolutionary game theoretical approach and replicator dynamics is solved to seek an optimal stable solution. Combining both self-control of users’ preferences and self-adjustment of networks’ parameters, our study innovates over related efforts. The simulation results demonstrate that the proposed inverse cumulative ranking scheme significantly improves the overall QoS performance and system benefits as compared to other solutions. Our results also show that by incorporating the proposed Region of Interest (RoI) scheme, the complexity of the evolutionary game with and without network re-configuration can be reduced by 23% and 58 % respectively.