Performance Evaluation of Precoding Techniques for 5G Massive MIMO Downlink System

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Addis Ababa University


Massive multiple-input-multiple-output (MIMO) systems use a few hundred antennas to simultaneously serve many wireless broadband terminals, using sophisticated coding at the transmitter and substantial signal processing at the receiver, the MIMO channel can be provisioned for higher data rates, resistance to multipath fading, lower delays, and support for multiple users. In multi-user MIMO, a multi-antenna transmitter communicates simultaneously with multiple receivers (each having one or multiple antennas). This is known as space-division multiple access (SDMA) and here Precoding algorithms will be very essential for supporting multi-stream (or multi-layer) transmission in multi-antenna wireless communications, since the research aim is to find the key options to increase the performance of the upcoming 5G wireless system, this research work will focus on one of this options which are downlink distribution Precoding techniques for massive MIMO system, by assuming that both the base station and the user terminals are equipped with an antenna array. Precoding algorithms for SDMA systems can be sub-divided into linear and nonlinear Precoding types. The capacity-achieving algorithms are nonlinear, but linear Precoding approaches usually achieve reasonable performance with much lower complexity. This research work will present a comparative study of different linear Precoding techniques for massive MIMO wireless systems. The performance of the Precoding scheme is evaluated and compared with an iterative Precoding scheme designed to provide a maximum achievable rate gain by exploiting the expanded spatial degrees of freedom.



5G wireless networks, massive MIMO, linear Precoding