Performance Analysis of Linear Precoding for Multiuser Multiple-Input and Multiple-Output Broadcast Channels

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Addis Ababa University


Multiuser Multiple Input and Multiple Output is an antenna technology for wireless communication in which number of users or wireless terminals each with one or more number of antennas communicate with each other. Precoding in multiuser MIMO systems is important to minimize or mitigate the multiuser interference. As a consequence, the design of suitable precoding algorithms with a low computational complexity and a good overall performance is a challenging scenario when system dimensions are high. A linear precoding technique such as regularized channel inversion (minimum mean square error), channel inversion (zero forcing), and Block diagonalization techniques for multi-user multiple input multiple-output broadcast channels are able to eliminate the multiuser interference per antenna or sum power constraint. After conducting this thesis an enhanced performance is measured from this thesis. In case, analysis of the MU-MIMO with fewer number of antennas may reduce the cost of antenna and some complexities in large antenna system. Different researches are conducted in multiuser MIMO with single antenna receivers and conducted mostly in Rayleigh channel conditions. Besides, the performance of multiuser MIMO linear precoding under different channel conditions together with two or more antenna receivers have been investigated in this work. In this research, the performance of linear precoding in multiuser MIMO under Rayleigh, Rician and Deterministic channel conditions are illustrated in different performance metrics like data rate, channel capacity and spectral efficiencies. The performance of linear precoding under multiuser MIMO with two antenna users have a great performance due to the combined effect of the antennas. In addition, the Rican channels achieves minimum bit error rate than Rayleigh and deterministic channels. Furthermore, this study has advantage of detail comparative analysis when the users are more, and this analysis have a direct impact when the congested number of users are involved.



MU-MIMO, broadcast channel, multiuser Interference, linear precoding