Self-adaptive Neighbor Discovery in Mobile Ad Hoc Networks with Directional Antennas

In Mobile Ad hoc Networks (MANETs), directional antenna is a good solution if longer transmission distance is needed. When nodes are equipped with directional antennas, however, neighbor discovery becomes challenging especially for the decentralized networks. In most existing studies on neighbor discovery with directional antennas, nodes switch their directional antennas to different sectors either randomly or in a predefined sequences, and the steering time of each sector is the same. However, they cannot guarantee the performance when the nodes are not uniformly deployed and their mobility is not pure random. For practical considerations, we propose a novel neighbor discovery algorithm which makes nodes be able to sense the topology changes around them and arrange their directional antennas accordingly. We also do simulations to compare the performances of the proposed algorithm and the traditional random algorithm. The results show that the proposed algorithm has a better performance especially in the scenario where the node density is low.