Beam Allocation and Power Optimization for Energy-Efficiency in Multiuser mmWave Massive MIMO System

Abstract

This paper studies beam allocation and power optimization scheme to decrease the hardware cost and downlink power consumption of a multiuser millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system. Our target is to improve energy efficiency (EE) and decrease power consumption without obvious system performance loss. To this end, we propose a beam allocation and power optimization scheme. First, the problem of beam allocation and power optimization is formulated as a multivariate mixed-integer non-linear programming problem. Second, due to the non-convexity of this problem, we decompose it into two sub-problems which are beam allocation and power optimization. Finally, the beam allocation problem is solved by using a convex optimization technique. We solve the power optimization problem in two steps. First, the non-convex problem is converted into a convex problem by using a quadratic transformation scheme. The second step implements Lagrange dual and sub-gradient methods to solve the optimization problem. Performance analysis and simulation results show that the proposed algorithm performs almost identical to the exhaustive search (ES) method, while the greedy beam allocation and suboptimal beam allocation methods are far from the ES. Furthermore, experiment results demonstrated that our proposed algorithm outperforms the compared the greedy beam allocation method and the suboptimal beam allocation scheme in terms of average service ratio.

Joint Optimization of Massive MIMO System Resources Based on Service QoS

“…The research conducted in [8] studies the power allocation problem of massive MIMO systems and proposes a power allocation method using the asymptotic concave formation of the system sum rate, and the sum rate of the system increases with the increased number of antennas but ignores the index of spectral efficiency. The research in [9] proposes a beam allocation and power optimization scheme, which is solved by expressing the problem of beam allocation and power optimization as a multivariate mixed integer nonlinear programming problem. This scheme has certain research value but does not consider the user's QoS index.…”