View source for 18550398. BEAMFORMING FOR MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) MODES IN OPEN RADIO ACCESS NETWORK (O-RAN) SYSTEMS simplified abstract (Intel Corporation)

=BEAMFORMING FOR MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) MODES IN OPEN RADIO ACCESS NETWORK (O-RAN) SYSTEMS=


==Organization Name==

[[:Category:Intel Corporation|Intel Corporation]]


[[Category:Intel Corporation]]

==Inventor(s)==

[[:Category:Nicholas Whinnett of Bath and North East Somerset (GB)|Nicholas Whinnett of Bath and North East Somerset (GB)]][[Category:Nicholas Whinnett of Bath and North East Somerset (GB)]]

[[:Category:Dawei Ying of Hillsboro OR (US)|Dawei Ying of Hillsboro OR (US)]][[Category:Dawei Ying of Hillsboro OR (US)]]

[[:Category:Bishwarup Mondal of San Ramon CA (US)|Bishwarup Mondal of San Ramon CA (US)]][[Category:Bishwarup Mondal of San Ramon CA (US)]]

[[:Category:Jan Schreck of San Jose CA (US)|Jan Schreck of San Jose CA (US)]][[Category:Jan Schreck of San Jose CA (US)]]

[[:Category:Jaemin Han of Portland OR (US)|Jaemin Han of Portland OR (US)]][[Category:Jaemin Han of Portland OR (US)]]

[[:Category:Leifeng Ruan of Beijing (CN)|Leifeng Ruan of Beijing (CN)]][[Category:Leifeng Ruan of Beijing (CN)]]

[[:Category:Jianli Sun of Beaverton OR (US)|Jianli Sun of Beaverton OR (US)]][[Category:Jianli Sun of Beaverton OR (US)]]

==BEAMFORMING FOR MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) MODES IN OPEN RADIO ACCESS NETWORK (O-RAN) SYSTEMS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18550398 titled 'BEAMFORMING FOR MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) MODES IN OPEN RADIO ACCESS NETWORK (O-RAN) SYSTEMS

==Simplified Explanation==

The abstract describes a patent application related to beamforming in MIMO modes in O-RAN systems. The apparatus includes memory to store beamforming configuration information and processing circuitry to retrieve this information, request measurements, receive measurements, and train an AI/ML model to predict beamforming performance.

* Explanation of the patent/innovation:
* Memory stores beamforming configuration information for multiple MIMO modes
* Processing circuitry retrieves this information and requests measurements for the MIMO modes
* Received measurements are used to train an AI/ML model to predict relative beamforming performance

== Potential Applications ==
This technology could be applied in:
- 5G networks
- Wireless communication systems
- IoT devices

== Problems Solved ==
- Optimizing beamforming performance in MIMO modes
- Enhancing network efficiency and reliability
- Improving overall communication quality

== Benefits ==
- Increased data transfer speeds
- Enhanced network coverage
- Better signal quality in challenging environments

== Potential Commercial Applications ==
Optimized Beamforming Prediction Technology for Enhanced Wireless Communication Systems

== Possible Prior Art ==
Prior art related to beamforming in MIMO systems and AI/ML models for network optimization could be relevant to this patent application.

== Unanswered Questions ==

=== How does this technology compare to existing beamforming solutions in terms of performance and efficiency? ===
This article does not provide a direct comparison with existing beamforming solutions in terms of performance and efficiency. Further research or testing may be needed to evaluate the technology in relation to current solutions.

=== What are the potential limitations or challenges in implementing this technology in real-world O-RAN systems? ===
The article does not address potential limitations or challenges in implementing this technology in real-world O-RAN systems. Factors such as compatibility, scalability, and cost-effectiveness could be important considerations that are not covered in the abstract.


==Original Abstract Submitted==

Various embodiments herein are directed to beamforming associated with multiple-input multiple-output (MIMO) modes in open radio access network (O-RAN) systems. In one embodiment, an apparatus comprises: memory to store beamforming configuration information associated with a plurality MIMO modes; and processing circuitry, coupled with the memory to: retrieve the beamforming configuration information from the memory; request, based on the beamforming configuration information, measurements associated with the plurality of MIMO modes; receive the measurements associated with the plurality of MIMO modes; and based on the received measurements, train an artificial intelligence/machine learning (AI/ML) model that is to predict relative beamforming performance between the plurality of MIMO modes.



[[Category:H04B7/06]]
[[Category:H04B7/0452]]