Study of Cloud-Aided Multi-Way Multiple-Antenna Relaying with Best-User Link Selection and Joint ML Detection
In this work, we present a cloud-aided uplink framework for multi-way multiple-antenna relay systems which facilitates joint linear Maximum Likelihood (ML) symbol detection in the cloud and where users are selected to simultaneously transmit to each other aided by relays. We also investigate relay selection techniques for the proposed cloud-aided uplink framework that uses cloud-based buffers and physical-layer network coding. In particular, we develop a novel multi-way relay selection protocol based on the selection of the best link, denoted as Multi-Way Cloud-Aided Best-User-Link (MWC-Best-User-Link). We then devise the maximum minimum distance relay selection criterion along with the algorithm that is incorporated into the proposed MWC-Best-User-Link protocol. Simulations show that MWC-Best-User-Link outperforms previous works in terms of average delay, sum-rate and bit error rate.