What are the future trends and opportunities for MIMO innovation and development?

1 Antenna design

One of the main challenges for MIMO is to design and deploy multiple antennas in a limited space and with minimal interference. Antenna design involves trade-offs between size, efficiency, bandwidth, isolation, and cost. Some of the possible solutions for MIMO antenna design include using adaptive or reconfigurable antennas, integrating antennas with other components or devices, exploiting novel materials or structures, and applying advanced fabrication techniques. For example, adaptive antennas can adjust their radiation patterns or frequencies according to the channel conditions or user preferences, while integrated antennas can save space and reduce complexity by combining antennas with sensors, batteries, or circuits.

2 Signal processing

Another challenge for MIMO is to process the signals transmitted and received by multiple antennas efficiently and accurately. Signal processing involves techniques such as beamforming, precoding, decoding, equalization, and interference cancellation. Some of the possible solutions for MIMO signal processing include using artificial intelligence or machine learning, exploiting massive or full-dimension MIMO, applying compressive sensing or sparse recovery, and leveraging cooperative or distributed MIMO. For example, artificial intelligence or machine learning can help optimize the signal processing algorithms or parameters based on the data or feedback from the network, while massive or full-dimension MIMO can increase the data rate or diversity by using hundreds or thousands of antennas in a two-dimensional or three-dimensional array.

3 Network architecture

A third challenge for MIMO is to design and operate the network architecture that supports multiple antennas and users. Network architecture involves aspects such as spectrum allocation, resource management, power control, security, and quality of service. Some of the possible solutions for MIMO network architecture include using heterogeneous or multi-tier networks, exploiting cognitive or dynamic spectrum access, applying network slicing or virtualization, and leveraging cloud or edge computing. For example, heterogeneous or multi-tier networks can enhance the coverage and capacity by using different types of base stations or access points with different frequencies or functionalities, while cognitive or dynamic spectrum access can improve the spectrum efficiency by allowing MIMO devices to sense and use the available spectrum opportunistically or adaptively.

4 Emerging applications

A fourth opportunity for MIMO is to explore and develop new applications that can benefit from the advantages of multiple antennas and users. Emerging applications involve domains such as internet of things, smart cities, autonomous vehicles, augmented reality, or biomedical engineering. Some of the possible solutions for MIMO emerging applications include using millimeter-wave or terahertz MIMO, exploiting visible light or optical MIMO, applying MIMO radar or imaging, and leveraging MIMO sensing or localization. For example, millimeter-wave or terahertz MIMO can enable ultra-high-speed or ultra-low-latency wireless communication for applications such as virtual reality or remote surgery, while visible light or optical MIMO can offer secure or energy-efficient wireless communication for applications such as indoor positioning or smart lighting.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?