Certain investigations on antenna and beam selection in massive mimo systems

Abstract

In the forthcoming fifth generation wireless communication systems the combination of massive multiple-input-multiple-output and millimeter Wave has gained popularity because of its capability in increasing the system sum rate. The exploitation of mmWave massive MIMO systems with larger number of base station antennas endure high energy consumption and hardware cost mostly by the radio frequency chains involved along with the advantage of huge bandwidth capacity. When the number of antennas is large as in a Massive MIMO system the circuit power consumption would be increased by the number of antennas. So when the number of antennas increases antenna selection can be used to choose the RF chain configuration in order to enhance the spectral efficiency and reduce the hardware complexity involved. The antenna selection scheme reduces the number of active RF chains involved and increases the energy efficiency with effective reduction in the cost of base station. The proposed work on antenna selection focuses on an efficient antenna selection strategy for a distributed massive MIMO system in downlink. The objective of the proposed antenna selection algorithm is to accomplish the ergodic achievable rate as much as possible with antenna selection in a constrained capacity limited system. The proposed transmit antenna selection overcome these factors and considers trade off between complexity and system performance in a constrained capacity limited system. In order to obtain higher spectral efficiency, beam selection instead of antenna selection using a beam forming network is desired. Beam selection is better than antenna selection in correlated Rayleigh fading channels with limited angle spread. Beam selection outperforms antenna selection since in beam selection approach all the antennas are used at the same time even with one RF chain, whereas in antenna selection only one antenna is used at a time. The proposed work on beam selection is an efficient fairness aware beam allocation strategy which is based on the user