Enabling Multicarrier Relay Selection by Sensing Fusion and Cascaded ANN for Intelligent Vehicular Communications

Cooperative relaying has been adopted as one of the most important techniques to enhance the energy efficiency and coverage. Multi-carrier relay selection is an efficient method to allocate spatial/spectral resources in cooperative relay networks and provides diversity gain. However, the implementation of multi-carrier relay selection is not straightforward, and could render the high system complexity (for centralized implementation schemes) or long processing delay (for distributed implementation schemes). These issues hinder the promotion and implementation of multi-carrier relay selection for intelligent vehicular communications. To mitigate aforementioned issues, we propose an enabling technique of multi-carrier relay selection based on sensing fusion (SF) and cascaded artificial neural networks (CANNs) for intelligent vehicular communications. We employ two well-known multi-carrier relay selection schemes, i.e. bulk and per-subcarrier relay selection, to verify the effectiveness of the CANN based enabling technique. With the powerful processing ability with intelligent vehicles, the numerical results illustrate a promising vision of applying CANNs to enable multi-carrier relay selection for fast deployment in intelligent vehicular communication networks.

Automated summary

This study introduces an enabling technique of multi-carrier relay selection based on sensing fusion and cascaded artificial neural networks to address the challenges in implementing multi-carrier relay selection. Experimental results demonstrate the promising vision of deploying multi-carrier relay selection rapidly with the powerful processing ability of intelligent vehicles.