On Mobility-Aware and Channel-Randomness-Adaptive Optimal Neighbor Discovery for Vehicular Networks

Neighbor information perception with high accuracy and low overhead is quite essential for vehicular networks, which is accomplished by the neighbor discovery scheme. Following the scheme, nodes exchange short discovery messages for advertising their existence and sensing neighboring vehicles. To combat high vehicle mobility and severe channel fading, the discovery message is always exchanged frequently in vehicular networks. This, however, introduces superabundant communication overhead. In this article, a novel neighbor discovery method with mobility awareness and channel randomness adaptability is proposed for investigating the aforementioned issue. First, a closed-form expression is derived, which captures the quantitive relation of the neighbor discovery performance to the vehicle mobility and channel randomness. Guided by our theoretical analysis, the optimal neighbor discovery scheme is developed to adjust the discovery frequency adaptively based on mobility and channel. Thus, an optimal tradeoff between the discovery accuracy and overhead is achieved in vehicular networks. Simulation results coincide with our analysis results, which further demonstrates that the proposed discovery scheme outperforms the periodic and existing adaptive methods in terms of discovery accuracy and overhead.