Matching Theory

In this paper, a novel resource allocation design is investigated for non-orthogonal multiple access (NOMA) enhanced heterogeneous networks (HetNets), where small cell base stations (SBSs) are capable of communicating with multiple small cell users (SCUs) via the NOMA protocol. With the aim of maximizing the sum rate of SCUs while taking the fairness issue into consideration, a joint problem of spectrum allocation and power control is formulated. Particularly, the spectrum allocation problem is modeled as a many-to-one matching game with peer effects. We propose a novel algorithm where the SBSs and resource blocks (RBs) interact to decide their desired allocation. More importantly, we introduce the concept of 'experimentation' into the matching game for further improving the SCUs' sum rate. The proposed algorithm is proved to converge to a two-sided exchange-stable matching. The power control of each SBS is formulated as a non-convex problem, where the sequential convex programming is adopted to iteratively update the power allocation result by solving the approximate convex problem. The obtained solution is proved to satisfy the Karush-Kuhn-Tucker (KKT) conditions. We unveil that: 1) The proposed algorithm closely approaches the optimal solution within a limited number of iterations; 2) The 'experimentation' action is capable of further enhancing the performance of the matching algorithm; and 3) The developed NOMA-enhanced HetNets achieve a higher SCUs' sum rate compared to the conventional OMA-based HetNets.

As both the scale of mobile networks and the population of mobile users keep increasing, the applications of mobile social big data have emerged where mobile social users can use their mobile devices to exchange and share contents with each other. The security resource is needed to protect mobile social big data during the delivery. However, due to the limited security resource, how to allocate the security resource becomes a new challenge. Therefore, in this paper a model for a joint matching-coalitional game based security-aware resource allocation scheme to deliver mobile social big data, is presented. In this scheme, firstly a coalition game model is introduced for base stations (BSs) to form groups to provide both wireless and security resource, where the resource efficiency can be improved. Next, a joint matching-coalition algorithm is presented to obtain the stable security-aware resource allocation. At last, the simulation experiments prove that the presented scheme outperforms other existing schemes by providing higher efficiency and resource utilization for both wireless and security resources.