Channel Gain Prediction for Cooperative Multi-Agent Systems

摘要: In a cooperative multi-agent system (MAS), agents communicate with each other using the wireless medium. As agents move in the environment in order to fulfill the MAS'higher level task, their location changes and so does the wireless communication channel they experience. To enable a successful coordination, it is paramount for the agents to retain connectivity among themselves. In order to achieve this, the availability of explicit channel knowledge for the MAS'future configuration is needed. Since the agents determine their location from sensors, any expected residual location uncertainty for the MAS'future configuration will have an implication on the channel knowledge. For this reason, a computationally attractive yet accurate method to predict the wireless ad-hoc communication channel for any configuration and location uncertainty of the agents is needed. In this thesis, we employ Gaussian processes (GPs …