Beamspace Selection in Multi-User Massive MIMO

Abstract

In this paper, we propose new Discrete Fourier Transform (DFT)-based beamspace selection algorithms for Massive Multiple Input, Multiple Output (MIMO) receiver operating in realistic multi-user (MU) scenarios. In practical uplink scenarios, there is a power ratio between signals received from different users that complicates performance analysis in MU cases. Our algorithms are inspired by a proportional fair approach to allocating spatial resources for target users. Thus, we analyze performance in terms of coverage (for low-power users) and capacity (for high-power users) and consider the implementation complexity to highlight feasible algorithms. Simulations with realistic non-line-of-sight scenarios generated by the QuaDRiGa 2.0 demonstrate our methods outperform other DFT-based alternatives, such as the beamspace selection based on the projection power maximization.INDEX TERMS 5G, multi-user massive MIMO, beamspace selection, angular domain processing.

New Results on Single User Massive MIMO

“…A S wireless technologies evolve beyond 5G [1]- [3], there is a growing need to attain peak data rates of about gigabits per second per user, which is required for high definition video, remote surgery, autonomous vehicles, gaming and so on, while at the same time consuming minimum transmit power. This can only be achieved by using multiple antennas at the transmitter and receiver [4]- [8], small constellations like quadrature shift keying (QPSK) and powerful error correcting codes like turbo or low density parity check (LDPC) codes. Having a large number of antennas in the mobile handset is feasible in mm-wave frequencies [9]- [12] (30 − 300 GHz) due to the small antenna size.…”