Downlink Rate Analysis of Training-Based Massive MIMO Systems With Wireless Backhaul Networks

Massive multiple-input multiple-output (MIMO) systems with wireless backhaul networks have been considered as a candidate technology for 5G. Despite their potential, these systems still require improvement in areas such as resource allocation and interference management. In this paper, we derive a closed-form lower bound ergodic downlink rate expression for training-based multicell massive MIMO systems with full duplex wireless backhaul networks. We also propose a wireless backhaul link selection method, in which only certain access points will be activated and only certain users will use wireless backhaul links. The results show that the wireless backhaul with a link selection method can improve the downlink rate compared to other methods. The downlink rate of the minimum rate users can be significantly improved by prioritizing the wireless backhaul links for the minimum rate users. Power analysis shows that there is concave relationship between access point transmit power and median downlink rate. The results also show that the optimum access point transmit power is much lower than the standard transmit power from the users and base station. Additional investigation shows that users are more likely to use backhaul links when they are located farther from the base station. We also demonstrate that as the number of spatial multiplexed users increases, the performance improvement provided by wireless backhaul system decreases