Joint Resource Allocation and Power optimization for Energy-Efficiency in Multiuser mmWave Massive MIMO System

In the upcoming fifth-generation (5G) wireless communication system, the massive MIMO and mmWave technologies will play a key role to improve the system performance. With the rapid development of the network communications, optimizing radio resources of wireless communication has been one of the challenging issues in 5G networks. In order to effectively improve network performance, an efficient resource allocation and power optimization algorithm is necessary. In this paper, we study joint resource allocation and power optimization (JRAPO) problem in multiuser mmWave massive MIMO system, which target at increasing energy efficiency (EE) and decreasing power consumption of systems. First, the problem of JRAPO is formulated as a multivariate mixed integer nonlinear programming problem. Second, because the non-convexity of this problem, we transformed it into a convex optimization problem by relaxing the resource block (RB) allocation indicator. Finally, we used Lagrangian dual decomposition algorithm and water-filling scheme to resolve this joint optimization problem. Simulation results demonstrated the effectiveness of the proposed algorithm.