A Simple Cooperative Diversity Method Based on Deep-Learning-Aided Relay Selection

Opportunistic relay selection (ORS) has been recognized as a simple but efficient method for mobile nodes to achieve cooperative diversity in slow fading channels. However, the wrong of best arising from outdated channel state information (CSI) fast time-varying channels substantially degrades its performance. With proliferation high-mobility applications and adoption higher frequency bands 5G beyond systems, problem CSI will become more serious. Therefore, design novel that is applicable not only also increasingly importance. To this end, we develop analyze deep-learning-aided coined predictive (PRS) article. It can remarkably improve quality through prediction while retaining simplicity ORS by selecting single opportunistic so avoid complexity multi-relay coordination synchronization. Information-theoretic analysis numerical results terms outage probability capacity reveal PRS achieves full gain wireless environments outperforms existing schemes