Abstract
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 signal-to-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.
The numerical results demonstrate that the proposed scheme substantially outperforms existing schemes in the literature.
Original language | English |
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Pages (from-to) | 2021 |
Journal | IEEE Transactions on Wireless Communications |
Volume | 18 |
Issue number | 4 |
Early online date | 31 Jan 2019 |
DOIs | |
Publication status | Early online date - 31 Jan 2019 |