Joint Power Allocation and User Association Optimization for Massive MIMO Systems

• Published in: IEEE transactions on wireless communications Vol. 15; no. 9; pp. 6384 - 6399
• Main Authors: Trinh Van Chien, Bjornson, Emil, Larsson, Erik G.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-09-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Channel estimation; Codes; Fading channels; linear program; load balancing; Massive MIMO; MIMO; Minimization; power allocation; Precoding; Resource management; user association; Wireless communication
• ISSN: 1536-1276; 1558-2248; 1558-2248
• DOI: 10.1109/TWC.2016.2583436

This paper investigates the joint power allocation and user association problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink (DL) systems. The target is to minimize the total transmit power consumption when each user is served by an optimized subset of the base stations (BSs), using non-coherent joint transmission. We first derive a lower bound on the ergodic spectral efficiency (SE), which is applicable for any channel distribution and precoding scheme. Closed-form expressions are obtained for Rayleigh fading channels with either maximum ratio transmission (MRT) or zero forcing (ZF) precoding. From these bounds, we further formulate the DL power minimization problems with fixed SE constraints for the users. These problems are proved to be solvable as linear programs, giving the optimal power allocation and BS-user association with low complexity. Furthermore, we formulate a max-min fairness problem that maximizes the worst SE among the users, and we show that it can be solved as a quasi-linear program. Simulations manifest that the proposed methods provide good SE for the users using less transmit power than in small-scale systems and the optimal user association can effectively balance the load between BSs when needed. Even though our framework allows the joint transmission from multiple BSs, there is an overwhelming probability that only one BS is associated with each user at the optimal solution.