Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/9044
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dc.contributor.authorChili, Nompumelelo-
dc.contributor.authorMukubwa, Emmanuel-
dc.contributor.authorPillay, Nelendran-
dc.date.accessioned2024-05-02T06:31:53Z-
dc.date.available2024-05-02T06:31:53Z-
dc.date.issued2023-
dc.identifier.urihttps://doi.org/10.1109/ICECET58911.2023.10389321-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/9044-
dc.description.abstractMassive Multiple-Input Multiple-Output (MIMO) answers the exponentially increasing demand for comprehensive fixed broadband and broadcast wireless communication services. Massive MIMO is a pivotal technology in the 5G and beyond (5GaB) wireless communication systems. This paper compares linear precoding algorithms such as Minimum Mean Square Error (MMSE), Neumann Series Approximation (NSA) with nonlinear precoders such as Tomlinson-Harashima Precoder (THP), and Lattice Reduction (LR) algorithm, the Lenstra-Lenstra-Lov'asz (LLL) precoder. The comparison was conducted using Bit-Error Rate (BER) and signal-to-noise ratio (SNR) performance measures. Simulated results prove that nonlinear precoders outperform linear precoding in high SNR regions.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectWireless communicationen_US
dc.subjectMultiple-input multiple-outputen_US
dc.titlePerformance comparison of linear and nonlinear precoding for massive MIMOen_US
dc.typePresentationen_US
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