A Device-to-Device direct discovery algorithm to mitigate the collision caused by hidden users

Abstract

Device-to-Device (D2D) discovery is an essential constituent in D2D communications as a future generation of wireless communication networks. Direct discovery enables users to discover their neighbors to exchange traffic without the cellular-networks assistance in order to enhance spectral efficiency and throughput. Despite its role to reduce signaling load, few works pay sufficient attention to direct discovery. According to the latest density of users detected by User Equipments (UEs) and their neighbors, this study suggests an adaptable, neighborhood-aware D2D direct discovery technique. To distinguish concealed UEs from other UEs, this technique employs a novel classification method. It also uses its neighborhood-aware capability to avoid severe collisions among all users, including hidden users. The performance of the proposed algorithm is compared with the recent adaptive algorithms and the algorithm recommended by the 3GPP standard. We evaluate algorithms in metrics such as discovery delay and the number of beacons required to terminate the discovery process. The simulation results show that the number of beacons, collision, and discovery delay considerably decrease via the proposed algorithm.