Application-Aware Game Theoretic Pricing Algorithm for Cellular Machine-to-Machine Communications

Machine-to-machine (M2M) communications has emerged as a key enabler of the internet of things (IoT) paradigm. One of the key objectives of 5G is to provide improved support for M2M or IoT applications with diverse service and traffic characteristics. In this paper, we present an application aware game theoretic resource allocation algorithm to solve the capacity maximization problem in the uplink of a two-tier OFDMA based network with coexisting machine type communications devices (MTCDs) and conventional human type communications user equipments (HTC UEs). To mitigate the interference caused on the macro tier by the MTCDs deployed in the femtocells, we introduce an application aware pricing scheme based on the traffic characteristics of the M2M applications which discourages the exhibition of selfish or greedy behaviour. Finally, the simulation results showed that the proposed algorithm outperforms the existing algorithms in terms of overall achievable capacity, fairness and convergence speed as more users are added to the network.