Popular Matching Games for Correlation-Aware Resource Allocation in the Internet of Things

In this paper, the problem of cell association is studied in an Internet of things (IoT) system in which a set of devices deployed in a given area report physical events to a set of small base stations (SBSs) via uplink communication links. In this model, the key goal is to minimize the number of devices that report the same information to a given SBS by taking into account the spatial correlation between the IoT devices. In particular, the problem of correlation-aware cell association is formulated as a popular matching game in which the IoT devices are assigned to the SBSs to maximize the amount of information that is reported to the SBSs. To this end, the number of devices matched to every SBS must be maximized. For the formulated problem, a distributed two- level matching algorithm is proposed and the algorithm is proved to converge to a popular outcome. In that state, all the SBSs and devices prefer the matching that results from the proposed algorithm to any other possible matching. Simulation results show that the proposed algorithm allows the SBSs to collect up to 40\% more useful information compared to max sum-rate association algorithm.