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Optimization efficiency of 5G MIMO cooperative spectrum sharing NOMA networks

Non-orthogonal multiple access (NOMA) may improve spectrum efficiency (SE) in 5G and other future networks. Cognitive radio (CR) and multiple accesses might be beneficial for SE. A new era of productive communication with the combination of NOMA's network-oriented multi-access capabilities and...

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Bibliographic Details
Main Authors: Babikir, Mohamed Hassan, Hamid, Khalid, Abdu, Ghada AM, Elsayed, Imadeldin, Saeed, Rashid A, Khalifa, Othman Omran
Format: Proceeding Paper
Language:English
English
Published: IEEE 2024
Subjects:
T Technology (General)
T10.5 Communication of technical information
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://irep.iium.edu.my/114446/1/114446_Optimization%20efficiency%20of%205G%20MIMO.pdf
http://irep.iium.edu.my/114446/7/114446_Optimization%20efficiency%20of%205G%20MIMO_SCOPUS.pdf
http://irep.iium.edu.my/114446/
https://ieeexplore.ieee.org/document/10652572
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Summary:Non-orthogonal multiple access (NOMA) may improve spectrum efficiency (SE) in 5G and other future networks. Cognitive radio (CR) and multiple accesses might be beneficial for SE. A new era of productive communication with the combination of NOMA's network-oriented multi-access capabilities and the CR network (CRN) was anticipated. This research enhances the SE of the NOMA power domain (PD) in the downlink (DL) by utilizing cooperative cognitive radio networks (CCRNs). If the primary user (PU) is unable to receive data on the dedicated channel due to noise or interference, this strategy is expected to prove beneficial. Two network topologies with 100 MHz bandwidths and quadrature phase shift keying (QPSK) were proposed. Also used are 8×8, 16×16, and 32×32 Multiple Input Multiple Output (MIMO) topologies, which differ in transmit powers, user distances, and power location coefficients. Channel instability and successive interference cancellation (SIC) are also considered in performance studies. Fading channels are Rayleigh-fading, with frequency selectivity. MATLAB calculates the model's SE. SE performance is 35%, 44%, and 73% better for 8×8, 16×16, and 32×32 MIMO NOMA, while CCRN 8×8, 16×16, and 32×32 MIMO NOMA enhances SE performance by 50%, 65%, and 80%, respectively, when compared with the standard NOMA model. Using MIMO technology boosts SE significantly.

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