A Power Control Algorithm for V2V Communication Networks Based on Dynamic Multi-Objective Optimization

Vehicular communication networks have the nature of high dynamics and consist of communication links with different or even conflicting transmission objectives and quality of service (QoS) requirements. Therefore, it is extremely challenging to make optimal transmission decisions in vehicular communication networks. In this paper, we study a sequential transmission design problem in a typical vehicle-to-vehicle (V2V) communication network and formulate the problem as a dynamic multi-objective optimization (DMO) problem with the aim to trade-off transmission objectives and guarantee QoS requirements through power control. We propose a prediction-based dynamic multi-objective optimization evolutionary algorithm (DMOEA) that facilitates the evolution of the solution population by predicting the centroid of the power allocation decision set in a new environment, so that transmission decisions can be made to adapt to the highly dynamic environment. Extensive simulation experiments demonstrate the effectiveness and advantages of the proposed algorithm.