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Performance Analysis of Low- Complexity Precoding Scheme In MU - Massive MIMO for 5G and Beyond Networks

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dc.contributor.author Admassu, Amanuel
dc.contributor.author Anlay, Kinde
dc.contributor.author Gebru, Solomon
dc.date.accessioned 2022-04-01T12:44:11Z
dc.date.available 2022-04-01T12:44:11Z
dc.date.issued 2022-01-16
dc.identifier.uri https://repository.ju.edu.et//handle/123456789/6887
dc.description.abstract Maximum ratio combining (MRC), maximum ratio transmission (MRT) and zero forcing (ZF) are well known precoders which have been researched out in recent studies. In this thesis, the performances of maximum ratio combining (MRC) and zero forcing (ZF) at uplink and maximum ratio transmission (MRT) and zero forcing ( ZF) at downlink MU - Massive MIMO system have been analyzed and compared. This work focuses on a single-cell with multiple base station antenna serving multiple user equipments. The achievable sumrate and all the required metrics in uplink and downlink system using low complex linear precoding scheme under different scenario have been derived . In this work two regimes are considered for SNR and it has been mathematically proved and simulated using Matlab2018. These two regimes are high SNR and low SNR. Also low complex linear precoders have been proposed. The proposed idea is to predict and use the precoder which results better performance in terms of achievable rate, spectral efficiency and energy efficiency for a given channel. In the downlink scenario we applied normalization method for equal allocation of power for both MRT and ZF precoders. For low SNR, MRC and MRT perform better than zero forcing. For high SNR, zero forcing (ZF) performs better than MRC and MRT. From the result executed MRT have better performance than ZF when the number of user is lesser under vector normalization. Similarly, under low SNR, ZF precoders have lesser performance than MRT precoding scheme in matrix normalization. Generally , the performance of the precoders will begin to grow up as the number of BS antenna is folded. In uplink case an achievable rate for zero forcing and MRC grows by 31.12 % and 33.4 % respectively for low power. Similarly, achievable rate for zero forcing and MRC grows by 11.48 % and 36.4 % respectively for high uplink power.In downlink case an achievable rate under vector normalization for zero forcing and MRT grows by 28.8 % and 27.1 % respectively for low BS transmitter power.Similarly, achievable rate for zero forcing and MRT grows by 11.8 % and 7.32 % respectively for high BS transmitter power en_US
dc.language.iso en_US en_US
dc.subject Achievable sum-rate en_US
dc.subject MRC en_US
dc.subject MRT en_US
dc.subject MU-Massive MIMO en_US
dc.subject ZF en_US
dc.title Performance Analysis of Low- Complexity Precoding Scheme In MU - Massive MIMO for 5G and Beyond Networks en_US
dc.type Thesis en_US


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