This presentation and paper demonstrate a new predictive capability for simulating massive MIMO antennas and beamforming in dense urban propagation environments.
In anticipation of rapid growth in wireless device and mobile data demand, multiple input, multiple output (MIMO) is one of the key technologies being researched for 5G; however, traditional methods for channel modeling present shortfalls, either in their ability to model the details required for MIMO systems, or in the level of computation that they must perform to handle the increasing numbers of antennas and channels.
To overcome these shortfalls, we present an innovative and optimized approach for efficiently simulating the detailed multipath of large numbers of MIMO channels using ray-tracing, while overcoming the limitations and computational complexity of traditional ray-tracing methods. In this study we use the new Wireless InSite® MIMO capability to predict the complex channel matrix for mobile devices within a small cell. We then apply beamforming techniques to predict and display the actual physical beams to each device, and evaluate signal power and interference, including the impacts when pilot contamination is present.
This study was presented at EDI CON 2016 in Boston, MA.
Animations: Beamforming in Motion
As part of the EDICON presentation, we applied Maximum Ratio Transmission (MRT) and Zero Forcing (ZF) beamforming algorithms to the H-matrices generated from Wireless InSite's MIMO capability in order to visualize beamforming in motion. These animations show the beam formed from a massive MIMO base station (green dot) to a mobile device moving along a route (large red dot), in the presence of 15 other stationary devices (red circles). MRT maximizes the beam to the intended device, while ZF beamforming attempts to also minimize the interference to the other devices.
Maximum Ratio Transmission Beamforming
Zero Forcing Beamforming