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Performance comparison of linear and nonlinear precoding for massive MIMO

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dc.contributor.author Chili, Nompumelelo
dc.contributor.author Mukubwa, Emmanuel
dc.contributor.author Pillay, Nelendran
dc.date.accessioned 2024-05-02T06:31:53Z
dc.date.available 2024-05-02T06:31:53Z
dc.date.issued 2023
dc.identifier.uri https://doi.org/10.1109/ICECET58911.2023.10389321
dc.identifier.uri http://ir.mu.ac.ke:8080/jspui/handle/123456789/9044
dc.description.abstract Massive 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.iso en en_US
dc.publisher IEEE en_US
dc.subject Wireless communication en_US
dc.subject Multiple-input multiple-output en_US
dc.title Performance comparison of linear and nonlinear precoding for massive MIMO en_US
dc.type Presentation en_US


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