Outage Analysis and Learning-Based Relay Selection for Opportunistic Lossy Forwarding Relaying Systems

In this paper, we study an opportunistic decode-and-forward (DF) system allowing intra-link errors, referred as opportunistic lossy-forwarding (OLF) system. Multiple relays are available but only one “best relay” is selected to forward the decoded information to the destination. The forwarded information may be erroneous. The relay selection strategy is built using source coding with a helper theorem. We evaluate the outage probability of OLF relaying system, and derive an approximated theoretical outage probability bound. For practical deployment, a statistical learning algorithm for selection relay is designed. The practical performance loss is negligible compared to the optimal selection case. The OLF system outperforms the existing opportunistic DF system in terms of outage performance. Both theoretical and numerical results show that full diversity can be achieved. Finally, we investigate the position of deploying relays by minimizing the outage probability from simulation results.