Beamforming for heterogeneous cloud radio access network

To overcome the problem that previous researches for heterogeneous cloud radio access network (H-CRAN) mainly focus on single macro cell, and only considered the intracell interference in the one macro cell, while the inter cell interferences among different macro cells are neglected, H-CRAN with multiple macro-cells was studied, and the objective was to maximize system sum-rate through jointly optimizing the beamforming vectors of macro base stations (MBS) and remote radio heads (RRH). Based on alternating optimization and Lagrangian dual method, a joint MBS and RRH beamforming algorithm was proposed. The original problem was first divided into two subproblems. Then, the two sub-problem were solved alternately to obtain the final solutions of the original problem. In addition, the closed expression solutions of the two sub-problem were derived based on Lagrangian dual method. The proposed algorithm was compared with some beamforming algorithms in the simulation. The experimental results demonstrate the proposed algorithm has a better performance in improving the sum-rate of H-CRAN. © 2019, Editorial Board of Journal on Communications. All right reserved.