Simulation of Neighbor Discovery Algorithm in Directional Antenna Ad Hoc Networks Based on OPNET

doi:10.16182/j.issn1004731x.joss.201805011

Abstract

Abstract: Neighbor discovery problem in directional antenna Ad Hoc networks is studied. A Q-Learning neighbor discovery algorithm is proposed, and a simulation model for directional antenna Ad Hoc networks based on OPNET software is setup. This algorithm makes a decision of transmitting and receiving mode for every neighbor scanning without the information of neighbor position through the Q-Learning mechanism. The reward value is determined according to the current scanning result, and the experiences are learned in order to improve the neighbor discovery efficiency. The simulation model based on OPNET software is constructed using three-layer modeling mechanism. Then the directional antenna is modeled by the antenna modeling editor. The simulation result based on OPNET shows that the proposed algorithm has a better efficiency of neighbor discovery compared with the scan based algorithm.

Key words: OPNET, directional antenna, Ad Hoc networks, neighbor discovery, Q-Learning

CLC Number:

Li Mo, Zhao Liang. Simulation of Neighbor Discovery Algorithm in Directional Antenna Ad Hoc Networks Based on OPNET[J]. Journal of System Simulation, 2018, 30(5): 1707-1714.

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