Performance of Enhanced Massive Multiuser MIMO Systems Using Transmit Beamforming and Transmit Antenna Selection Techniques

Abstract

In this paper, the performances of massive multiuser multiple input multiple output (MMU MIMO) system with different transmit beamforming (BF) techniques and different suboptimal transmit antenna selection (TAS) algorithms over Rayleigh fading channels are investigated. Three linear transmit BF types are considered, namely, maximum ratio transmission (MRT BF), zero forcing (ZF BF) and minimum mean square error (MMSE BF). Two TAS algorithms are considered, that are pairwise error probability minimization (PM) and the capacity maximization (CM). TAS techniques are used in order to reduce the number of radio frequency (RF) chains, system complexity, and cost. This makes MMU MIMO more applicable in beyond 4G communication systems. The simulation results show that TAS algorithms are capable of decreasing the complexity of the system while maintaining the same performance of the MMU MIMO system, complex TAS techniques are not needed at large number of RF chains, and the performance improvement due to the increase of this number is limited to a certain threshold. It also demonstrated that the MMSE BF and ZF BF bit error rate performance values are better than MRT BF values for both CM and PM TAS algorithms, but it is limited to the large number of users. On the other hand, the MRT BF technique performance is good at small Eb/N0 values for both PM and CM TAS but it is relatively less affected by increasing the number of users.