Optimal Transmit Power and Channel-Information Bit Allocation With Zeroforcing Beamforming in MIMO-NOMA and MIMO-OMA Downlinks

In downlink, a base station (BS) with multiple transmit antennas applies zeroforcing beamforming to transmit to single-antenna mobile users in a cell. We propose the schemes that optimize transmit power and the number of bits for channel direction information (CDI) for all users to achieve the max-m...

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Bibliographic Details
Published in:IEEE transactions on communications 2023-04, Vol.71 (4), p.1-1
Main Authors: Mamat, Kritsada, Santipach, Wiroonsak
Format: Article
Language:English
Subjects:
Antennas
Array signal processing
Beamforming
CSI quantization
Downlink
Downlinking
geometric program
max-min fairness
MIMO
MIMO communication
NOMA
Nonorthogonal multiple access
OMA
Optimization
Quantization (signal)
Resource management
Signal to noise ratio
transmit power allocation
Transmitting antennas
zeroforcing beamforming
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Summary:In downlink, a base station (BS) with multiple transmit antennas applies zeroforcing beamforming to transmit to single-antenna mobile users in a cell. We propose the schemes that optimize transmit power and the number of bits for channel direction information (CDI) for all users to achieve the max-min signal-to-interference plus noise ratio (SINR) fairness. The optimal allocation can be obtained by a geometric program for both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA). For NOMA, 2 users with highly correlated channels are paired and share the same transmit beamforming. In some small total-CDI rate regimes, we show that NOMA can outperform OMA by as much as 3 dB. The performance gain over OMA increases when the correlation-coefficient threshold for user pairing is set higher. To reduce computational complexity, we propose to allocate transmit power and CDI rate to groups of multiple users instead of individual users. The user grouping scheme is based on K-means over the user SINR. We also propose a progressive filling scheme that performs close to the optimum, but can reduce the computation time by almost 3 orders of magnitude in some numerical examples.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2023.3240392