Capacity Based Efficient Beam-Selection Methods for mmWave 5G MIMO Communication Systems

In this work, capacity based optimal best beam set selection methods in MIMO channel condition are presented. Proposed methods are suitable for existing Verizon 5G specifications \cite{VzW} and also scalable to upcoming 3GPP NR\cite{NR} mmWave communications systems. Proposed methods are aimed at improving the performance, robustness and computational efficiency of the user equipment (UE) system where beam measurements are intended. Two methods namely, a two stage capacity maximization (CM) based method and a hybrid power and capacity maximization based method are proposed herein. Capacity based solutions are preferred over received signal strength (RSS) based methods in view of its superior performance in presence of unknown interference and noise. Hybrid method exploits the sparse channels inherent in beamformed mmWave systems. Also, it is preferable as it complies with the evolving 5G communication requirements which need estimation of additional alternative MIMO transmit and receive beam pairs apart from the serving beams to achieve higher throughput by overcoming random beam blockage and misalignment. Efficacy and performance of the proposed beam-selection methods is compared with existing RSS based method. Also computational complexity of the proposed methods are analyzed and numerical results comparing them are presented. Advantages of the capacity based methods proposed are demonstrated through analysis and simulation results.