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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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Published in: | IEEE transactions on communications 2023-04, Vol.71 (4), p.1-1 |
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description | 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. |
doi_str_mv | 10.1109/TCOMM.2023.3240392 |
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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.</description><identifier>ISSN: 0090-6778</identifier><identifier>EISSN: 1558-0857</identifier><identifier>DOI: 10.1109/TCOMM.2023.3240392</identifier><identifier>CODEN: IECMBT</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>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</subject><ispartof>IEEE transactions on communications, 2023-04, Vol.71 (4), p.1-1</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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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.</description><subject>Antennas</subject><subject>Array signal processing</subject><subject>Beamforming</subject><subject>CSI quantization</subject><subject>Downlink</subject><subject>Downlinking</subject><subject>geometric program</subject><subject>max-min fairness</subject><subject>MIMO</subject><subject>MIMO communication</subject><subject>NOMA</subject><subject>Nonorthogonal multiple access</subject><subject>OMA</subject><subject>Optimization</subject><subject>Quantization (signal)</subject><subject>Resource management</subject><subject>Signal to noise ratio</subject><subject>transmit power allocation</subject><subject>Transmitting antennas</subject><subject>zeroforcing beamforming</subject><issn>0090-6778</issn><issn>1558-0857</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpNkMtOwzAQRS0EEqXwA4hFJNYpYzt-ZNmWV6WGsChCYhOZxKEpiV2cVBUbvh2nYcFqfKVzZ-SD0CWGCcYQ36zmaZJMCBA6oSQCGpMjNMKMyRAkE8doBBBDyIWQp-isbTcA4Ck6Qj_ptqsaVQcrp0zbVF3wbPfaBcoUwXytjNF1uDCldY3qKmuCmSemdW3zIb5W3Tp40856Iq_MRzDTqunp_l2ZIFkkafiUJtPDwkPqw63dm7oyn-05OilV3eqLvzlGL_d3q_ljuEwfFvPpMsxJJLqwVJKzUopCaMkLCkIB5blmmivhP6hiLTEpMNOMR7FiUNL3ONecSwFFkReMjtH1sHfr7NdOt122sTtn_MmMSKAQMYG5p8hA5c62rdNltnVejvvOMGS95-zgOes9Z3-efelqKFVa638FILGMKf0F0x55aA</recordid><startdate>20230401</startdate><enddate>20230401</enddate><creator>Mamat, Kritsada</creator><creator>Santipach, Wiroonsak</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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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 |
title | Optimal Transmit Power and Channel-Information Bit Allocation With Zeroforcing Beamforming in MIMO-NOMA and MIMO-OMA Downlinks |
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