Massive MIMO Transmission in Fronthaul-Constrained Cloud Radio Access Networks

Abstract

To satisfy the ever-increasing capacity demand and quality of service (QoS) requirements of users, massive MIMO (multiple-input multipleoutput) has been attracted as a promising technique in next generation wireless networks. Employing large-scale antennas, however, at remote radio heads (RRHs) generates heavy traffic to be carried through fronthaul links in cloud radio access networks (C-RANs). In this dissertation, we investigate C-RAN architecture, fronthauling methods, and multiple-input multiple-output (MIMO) transmission strategies to overcome explosive fronthaul traffic while maintaining the potential of C-RAN and massive MIMO to the fullest. Firstly, we proposed a partially-centralized C-RAN (PC-RAN) architecture where precoder, data symbol, and channel state information (CSI) are separately transported in fronthaul links. With the proposed PC-RAN, fronthaul traffic can be remarkably reduced with no or marginal performance degradation, compared with the conventional fully-centralized C-RAN (FC-RAN). Secondly, we mathematically evaluated the performance of zero-forcing based large-scale MIMO. We derive wireless performance and fronthaul traffic taking account of cooperative processing among RRHs in C-RAN environments. Through extensive simulations, we confirmed the accuracy of our analytical model and provided intuition on trade-off between wireless performance and fronthaul traffic volume. Thirdly, we investigated a joint beamforming and resource allocation problem of a single RRH for a constrained fronthaul capacity. We provide a heuristic algorithm to decide beamforming configuration and bandwidth allocation for each beamforming technique. The simulation results show that the proposed algorithm further improves the wireless sum-rates and achieves near optimal performance in our proposed partially-centralized C-RANs. Lastly, we investigated the performance of ZF and MRT with two fronthauling methods in fronthaul-constrained C-RANs. We provide an algorithm to decide the optimal fronthauling method and beamforming strategy to maximize the wireless sum-rate under a limited capacity of fronthaul link. Numerical results confirm that the sumrate gain is greater when both fronthauling solutions are available.