Overview of Neighbor Discovery Algorithms in Directional Wireless Ad Hoc Networks

A systematic summary is provided for the research achievements in directional neighbor discovery algorithms within the current domain of wireless directional ad hoc networks.Initially,stemming from the crucial significance of directional ad hoc networks in wireless communication,relevant background knowledge and fundamental concepts are introduced,delineating its research prospects in the realm of wireless communication.Subsequently,based on distinct technical standards,directional neighbor discovery algorithms are categorized and compared across multiple dimensions,delving into various applicable scenarios and associated limitations.Specific classifications include deterministic and random algorithms based on scanning sequence design,synchronous and asynchronous algorithms,purely directional and omnidirectional-assisted discovery algorithms,blind and semi-blind algorithms,as well as direct and indirect neighbor discovery algorithms.Moreover,by integrating the proposed classification methodology with the practical application scenarios of algorithms,the design principles and convergence processes of significant directional neighbor discovery algorithms are elaborately elucidated,including deterministic and random neighbor discovery algorithms,asynchronous neighbor discovery algorithms,and optimization algorithms utilizing machine learning techniques.Lastly,the future research directions and application trends of directional neighbor discovery algorithms are deliberated upon.