Energy-Efficient Optimization for Multi-cell Distributed Massive MIMO URLLC Systems

One of the most critical services in the fifth generation (5G) mobile communication is ultra-reliable and low-latency communication (URLLC). In this paper, we investigate the energy efficiency (EE) maximization problem of URLLC for the multi-cell distributed massive MIMO (DM-MIMO) system through a joint optimization of beamforming and remote radio unit (RRU) selection. The formulated problem is a mixed integer nonlinear program (MINLP) and then we solve it by applying efficient approaches, including the Dinkelbach method, semidefinite relaxation (SDR), reweighted l1-norm and auxiliary variable approximation. By combining these measures in one iteration, an energy-efficient optimization algorithm is proposed to find the suboptimal solution of the problem. Simulation results show that the proposed algorithm converges fast and significantly improves the EE of the multi-cell DM-MIMO URLLC system.