Heuristic-Learning-Based Network Architecture for Device-to-Device User Access Control

D2D networks have been employed in various mobile applications. Due to the limited wireless resource, a network cannot meet the data transmission requirements of all the users, especially in a data-intensive application. In such a scenario, a few users must temporarily disconnect from a network to guarantee the normal operation of the network. In a D2D network, the user access control strategy depends on the authenticity of CSI, since a user can be allocated more wireless resource and be allowed to stay in the network with a higher probability if the user has a higher CSI value. In this article, we investigate a heuristic learning method in which each user's CSI needs to be verified, and the users advocating a larger CSI are detected to be frauds. The results indicate that a dramatic increase of network performance can be captured by the proposed algorithm.