On the Uplink Max-Min SINR of Cell-Free Massive MIMO Systems

TY - JOUR

T1 - On the Uplink Max-Min SINR of Cell-Free Massive MIMO Systems

AU - Bashar, Manijeh

AU - Cumanan, Kanapathippillai

AU - Burr, Alister Graham

AU - Debbah, Merouane

AU - Ngo, Hien Quoc

N1 - © 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

PY - 2019/1/31

Y1 - 2019/1/31

N2 - A cell-free Massive multiple-input multiple-output (MIMO) system is considered using a max-min approach to maximize the minimum user rate with per-user power constraints. First, an approximated uplink user rate is derived based on channel statistics. Then, the original max-min signalto- interference-plus-noise ratio (SINR) problem is formulated for optimization of receiver filter coefficients at a central processing unit (CPU), and user power allocation. To solve this max-min non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas geometric programming (GP) is used to solve the user power allocation problem. Based on these two sub-problems, an iterative algorithm is proposed, in which both problems are alternately solved while one of the design variables is fixed. This iterative algorithm obtains a globally optimum solution, whose optimality is proved through establishing an uplink-downlink duality. Moreover, we present a novel sub-optimal scheme which provides a GP formulation to efficiently and globally maximize the minimum uplink user rate. The numerical results demonstrate that the proposed scheme substantially outperforms existing schemes in the literature.

AB - A cell-free Massive multiple-input multiple-output (MIMO) system is considered using a max-min approach to maximize the minimum user rate with per-user power constraints. First, an approximated uplink user rate is derived based on channel statistics. Then, the original max-min signalto- interference-plus-noise ratio (SINR) problem is formulated for optimization of receiver filter coefficients at a central processing unit (CPU), and user power allocation. To solve this max-min non-convex problem, we decouple the original problem into two sub-problems, namely, receiver filter coefficient design and power allocation. The receiver filter coefficient design is formulated as a generalized eigenvalue problem whereas geometric programming (GP) is used to solve the user power allocation problem. Based on these two sub-problems, an iterative algorithm is proposed, in which both problems are alternately solved while one of the design variables is fixed. This iterative algorithm obtains a globally optimum solution, whose optimality is proved through establishing an uplink-downlink duality. Moreover, we present a novel sub-optimal scheme which provides a GP formulation to efficiently and globally maximize the minimum uplink user rate. The numerical results demonstrate that the proposed scheme substantially outperforms existing schemes in the literature.

KW - Cell-free Massive MIMO

KW - max-min resource allocation

KW - geometric programming

KW - uplink-downlink duality

KW - convex optimization

KW - generalized eigenvalue problem

U2 - 10.1109/TWC.2019.2892463

DO - 10.1109/TWC.2019.2892463

M3 - Article

SN - 1536-1276

VL - 18

SP - 2021

EP - 2036

JO - IEEE Transactions on Wireless Communications

JF - IEEE Transactions on Wireless Communications

IS - 4

ER -