Two-timescale joint power control and beamforming design with applications to cell-free massive MIMO
In this study we derive novel optimal algorithms for joint power control and beamforming design in modern large-scale MIMO systems, such as those based on the cell-free massive MIMO and XL-MIMO concepts. In particular, motivated by the need for scalable system architectures, we formulate and solve n...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
04.12.2023
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Subjects | |
Online Access | Get full text |
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Summary: | In this study we derive novel optimal algorithms for joint power control and
beamforming design in modern large-scale MIMO systems, such as those based on
the cell-free massive MIMO and XL-MIMO concepts. In particular, motivated by
the need for scalable system architectures, we formulate and solve nontrivial
two-timescale extensions of the classical uplink power minimization and max-min
fair resource allocation problems. In our formulations, we let the beamformers
be functions mapping partial instantaneous channel state information (CSI) to
beamforming weights, and jointly optimize these functions and the power control
coefficients based on long-term statistical CSI. This long-term approach
mitigates the severe scalability issues of competing short-term iterative
algorithms in the literature, where a central controller endowed with global
instantaneous CSI must solve a complex optimization problem for every channel
realization, hence imposing very demanding requirements in terms of
computational complexity and signaling overhead. Moreover, our approach
outperforms the available long-term approaches, which do not jointly optimize
powers and beamformers. The obtained optimal long-term algorithms are then
illustrated and compared against existing short-term and long-term algorithms
via numerical simulations in a cell-free massive MIMO setup with different
levels of cooperation. |
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DOI: | 10.48550/arxiv.2312.02080 |