MIMO and Array Design for 5G

Exporting Antenna Data for Channel Simulations

Channel simulations provide a means to predict how systems will perform within a realistic setting, such as a connected home, indoor office environment, or an outdoor urban or suburban scene. Realism for this type of analysis is considerably improved by including the key characteristics of a device’s antennas as predicted by XFdtd.  To facilitate this, XFdtd can export the following types of antenna data:

• 3D antenna radiation patterns, including:

  • Unique pattern for each element of MIMO antenna

  • Frequency-specific patterns

• MIMO antenna element layouts

• MIMO codebooks

• MIMO multi-port S-parameters

For MIMO systems, the 3D layouts can be exported so that the full physical definition of an antenna or array can be directly imported.  In addition, optimization scripts can create custom codebooks, and multi-port S-parameters can be used to incorporate the impact of mutual coupling on performance analysis.

MIMO and Communication System Analysis

Given the MIMO antenna design and 3D channel characteristics, Wireless InSite’s Communication Systems Analyzer allows the RF engineer to evaluate a 5G device’s operation in the intended scenario.

To start, a MIMO technique is applied to each transmitter and receiver.  This will improve a system’s performance by increasing the signal-to-interference-plus-noise ratio (SINR), providing multiple parallel data streams, or both.  Wireless InSite models the following MIMO techniques:

• Antenna diversity

• Spatial multiplexing

• Beamforming

MIMO techniques determine how data is transmitted through the 3D environment.  Once that is known, Wireless InSite determines how much data can be transmitted.  The following metrics are accessed for each data stream and point-to-point link: 

• Throughput and capacity
  
  
• Bit error rate (BER)
  
  
• Noise, interference, and SINR

This results in a powerful tool that engineers use to determine if their device will meet 5G performance requirements in a realistic operating environment.

When multi-port S-parameters are imported from measurement data or full-wave simulations, the analysis can capture the impact of mutual coupling between MIMO elements. MIMO systems rely on channels that are uncorrelated, so mutual coupling can degrade the performance of MIMO techniques like spatial multiplexing, which aims to generate orthogonal data streams. It can also degrade MIMO beamforming if codebook weights are not tuned to compensate for it, as shown in the figure to the right. During the MIMO analysis, the S-parameters are applied to capture the effect of mutual coupling in the channel matrix, and later analysis will then incorporate this effect in the predicted performance in terms of SINR and throughput.