Exploiting social reciprocity for auction-based spectrum allocation in femtocell networks

With the explosive demand for wireless communications, users are always experiencing poor quality-of-services. Spectrum auction is a promising approach to allocate spectrum resources in wireless networks. Most of the previous works ignored social characteristics of users in wireless networks which influence the allocation of spectrum resources. In this article, we study the spectrum auction problem in a femtocell network and jointly exploit the social reciprocity of users for optimizing the allocation of spectrum resources. We propose an auction incentive framework combined with social reciprocity in the femtocell network. Such a matter is formulated as an integer programming optimization problem, and a modified quantum genetic algorithm is developed to solve the optimization problem. Besides we propose a payment rule satisfying truthfulness and individual rationality properties. Simulation results show that our algorithm can achieve the optimal solution to the optimization problem.