18276556. USER SELECTION FOR MU-MIMO simplified abstract (Telefonaktiebolaget LM Ericsson (publ))

USER SELECTION FOR MU-MIMO

Organization Name

Telefonaktiebolaget LM Ericsson (publ)

Inventor(s)

Ulf Gustavsson of Göteborg (SE)

Amirashkan Farsaei of Eindhoven (NL)

Alex Alvarado of Den Bosch (NL)

Frans M.J. Willems of Geldrpo (NL)

USER SELECTION FOR MU-MIMO - A simplified explanation of the abstract

This abstract first appeared for US patent application 18276556 titled 'USER SELECTION FOR MU-MIMO

Simplified Explanation

The method disclosed in the patent application involves selecting users for multi-user multiple-input multiple-output (MU-MIMO) communication by iteratively determining channel correlation metrics for potential users, excluding users based on these metrics, and calculating performance metrics for the remaining users to select the best set of users.

• Channel correlation metrics include channel filter norm, channel norm, channel gain, pair-wise correlations, and channel eigenvalue for each user.
• Performance metrics are calculated for each set of potential users, and the set with the best performance metric is selected for MU-MIMO communication.

Potential Applications

The technology can be applied in wireless communication systems to optimize the selection of users for MU-MIMO communication, improving overall system performance and efficiency.

Problems Solved

This technology solves the problem of efficiently selecting users for MU-MIMO communication by considering channel correlation metrics and performance metrics in the selection process.

Benefits

The benefits of this technology include improved system performance, increased throughput, reduced interference, and enhanced user experience in multi-user communication scenarios.

Potential Commercial Applications

Potential commercial applications of this technology include wireless communication systems, 5G networks, IoT devices, and other multi-user communication systems where MU-MIMO technology can be implemented to enhance performance.

Possible Prior Art

One possible prior art for this technology could be previous methods of user selection in MU-MIMO communication systems, which may not have considered channel correlation metrics in the selection process.

How does this method compare to existing user selection techniques in MU-MIMO communication systems?

This article does not provide a direct comparison to existing user selection techniques in MU-MIMO communication systems. It would be helpful to understand the specific advantages and limitations of this method compared to traditional approaches.

What impact does the selection of users based on channel correlation metrics have on overall system performance in MU-MIMO communication?

The article does not delve into the specific impact of selecting users based on channel correlation metrics on overall system performance in MU-MIMO communication. Understanding the performance improvements resulting from this selection method would provide valuable insights into the effectiveness of the technology.

Original Abstract Submitted

A method is disclosed of selecting users for multi user multiple-input multiple-output (MU-MIMO) communication from an initial set of potential users. The method comprises repeating the following steps in successive iterations until a stopping criterion is met: determining a channel correlation metric for each user in the set of potential users, reducing the set of potential users by exclusion of a user based on the channel correlation metric, and calculating a performance metric of the set of potential users. The method also comprises selecting users corresponding to one of the sets of potential users, wherein the selection is based on a comparison of the calculated performance metrics of the sets of potential users. The channel correlation metric for a user may comprise one or more of: a channel filter norm for the user, a channel norm for the user, a channel gain for the user, pair-wise correlations between the user and one or more other users of the set of potential users, and a channel eigenvalue for the user. The performance metric may comprise