Three‐dimensional scan‐based algorithm for directional neighbor discovery in ad hoc networks

Abstract

In recent years, neighbor discovery techniques using directional antennas have attracted widespread attention. Most currently available directional neighbor discovery techniques are designed based on two-dimensional (2D) space. Although these algorithms can accomplish the discovery between nodes, the algorithm portability is poor for three-dimensional (3D) platforms, and the application scenarios are limited since new communication scenarios such as unmanned aerial vehicle (UAV) groups and maritime fleets emerge where information needs to be delivered in real time and nodes are located in 3D space. This paper proposes a new deterministic directional neighbor discovery algorithm in 3D space named 3D scan-based algorithm (3D-SBA) to meet the needs of the line-of-sight (LOS) scenes. Four existing neighbor discovery algorithms, namely, SBA-based random mode selection (SBA-R), quorum, complete random algorithm (CRA), and SBA-based leader election algorithm (LE), have been extended to our proposed 3D algorithm model for simulation and comparative analysis with 3D-SBA. The simulation results show that the 3D-SBA algorithm consumes 51.15%, 180.20%, 9.48%, and 17.49% of the time slots compared with the four existing algorithms mentioned above. However, the quorum algorithm has a very high node collision rate, up to 92.11%.Ultimately, the 3D-SBA algorithm has the best performance considering the conflicts and the density of network nodes.