Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission. The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power. In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers. We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems. We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP). Further, one new FP-based algorithm is proposed for max-min fair power allocation. The alternating direction method of multipliers (ADMM) is used to solve specific convex subproblems in the proposed algorithms. Our ADMM reformulations lead to multiple small-sized subproblems with closed-form solutions. The proposed algorithms find global or local optimal power allocation solutions for large-scale systems but with reduced computational time compared to previous work.

Sucharita Chakraborty

Ozlem Tugfe Demir

Emil Bjornson

Pontus Giselsson

IEEE Open Journal of the Communications Society

IEEE Open J. Commun. Soc.

Efficient Downlink Power Allocation Algorithms for Cell-Free Massive MIMO Systems

Two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP) are proposed and one new FP-based algorithm is proposed for max-min fair power allocation.

Efficient Downlink Power Allocation Algorithms for Cell-Free Massive MIMO Systems

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