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A Gradual Resource Allocation Technique for Massive MIMO-NOMA

Abstract : In this paper, a new perspective for channel allocation and user pairing is proposed for a crowded downlink system using massive multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), and Zero-forcing (ZF) beamforming. The proposed user clustering technique allocates users to subbands and beams by a gradual relaxation of the correlation constraints in such a way to enhance the conditioning of the channel matrix. Channel measurements are performed in this context to validate the proposed technique in an experimental setup. Results show an important gain in performance in terms of both throughput and fairness with respect to orthogonal multiple access and to two state-of-the-art NOMA clustering methods.
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Contributor : Eric Simon Connect in order to contact the contributor
Submitted on : Monday, December 20, 2021 - 4:00:15 PM
Last modification on : Tuesday, April 26, 2022 - 4:06:04 PM


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Eric Simon, Joumana Farah, Pierre Laly, Gauthier Delbarre. A Gradual Resource Allocation Technique for Massive MIMO-NOMA. IEEE Antennas and Wireless Propagation Letters, Institute of Electrical and Electronics Engineers, 2022, 21 (3), pp.476-480. ⟨10.1109/LAWP.2021.3135981⟩. ⟨hal-03497334⟩



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