18045988. DISABLING BEAM PREDICTION OUTPUTS simplified abstract (QUALCOMM Incorporated)
Contents
- 1 DISABLING BEAM PREDICTION OUTPUTS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DISABLING BEAM PREDICTION OUTPUTS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
DISABLING BEAM PREDICTION OUTPUTS
Organization Name
Inventor(s)
Tianyang Bai of Somerville NJ (US)
Navid Abedini of Basking Ridge NJ (US)
Aria Hasanzadezonuzy of Somerville NJ (US)
Hua Wang of Basking Ridge NJ (US)
Junyi Li of Fairless Hills PA (US)
DISABLING BEAM PREDICTION OUTPUTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18045988 titled 'DISABLING BEAM PREDICTION OUTPUTS
Simplified Explanation
The present disclosure relates to wireless communication and a beam prediction model for predicting beam measurements in a network.
- User equipment (UE) receives a beam prediction model configuration from a network node.
- The UE is informed of a subset of beams to be associated with a measurement report.
- The UE transmits the measurement report to the network node, including predicted beam measurements based on the beam prediction model output.
Potential Applications
This technology could be applied in 5G and future wireless communication systems to improve beamforming and signal transmission efficiency.
Problems Solved
This technology helps in optimizing beamforming in wireless networks, leading to better signal quality and coverage.
Benefits
The benefits of this technology include enhanced network performance, increased data rates, and improved user experience in wireless communication.
Potential Commercial Applications
Potential commercial applications of this technology include telecommunications companies, network equipment manufacturers, and providers of wireless services.
Possible Prior Art
One possible prior art could be the use of machine learning models for beam prediction in wireless communication systems.
Unanswered Questions
1. How does the beam prediction model handle dynamic changes in the wireless environment? 2. What impact does the beam prediction model have on network latency and throughput?
Original Abstract Submitted
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, a configuration of a beam prediction model that is trained to predict beam measurements for a set of beams. The UE may receive, from the network node, an indication of a subset of beams, from the set of beams, that are to be associated with a measurement report. The UE may transmit, to the network node, the measurement report indicating one or more predicted beam measurements that are based at least in part on an output of the beam prediction model, the output of the beam prediction model including beam predictions associated with the set of beams, and the one or more predicted beam measurements including information associated with the subset of beams. Numerous other aspects are provided.
