Apple inc. (20240179734). METHODS AND ENHANCEMENTS FOR INTER-CELL INTERFERENCE MITIGATION simplified abstract

METHODS AND ENHANCEMENTS FOR INTER-CELL INTERFERENCE MITIGATION

Organization Name

apple inc.

Inventor(s)

Yushu Zhang of Beijing (CN)

Manasa Raghavan of Sunnyvale CA (US)

Dawei Zhang of Saratoga CA (US)

Haitong Sun of Cupertino CA (US)

Huaning Niu of San Jose CA (US)

Jie Cui of San Jose CA (US)

Qiming Li of Beijing (CN)

Rajarajan Balraj of Nuremberg (DE)

Xiang Chen of Campbell CA (US)

Yang Tang of San Jose CA (US)

METHODS AND ENHANCEMENTS FOR INTER-CELL INTERFERENCE MITIGATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240179734 titled 'METHODS AND ENHANCEMENTS FOR INTER-CELL INTERFERENCE MITIGATION

Simplified Explanation

The patent application discusses techniques for inter-cell interference mitigation, focusing on a user equipment (UE) receiving a network assistance indication related to an interfering signal that disrupts a physical downlink shared channel (PDSCH) transmission. The UE then estimates interference and noise covariance based on this indication and mitigates the interfering signal using the estimated values.

• User equipment (UE) configured to receive a network assistance indication for an interfering signal.
• Interfering signal disrupts a physical downlink shared channel (PDSCH) transmission.
• UE determines interference and noise covariance estimation mechanism based on the network assistance indication.
• UE performs interference and noise covariance estimation using the mechanism.
• Mitigation of the interfering signal is carried out by the UE based on the estimated interference and noise covariance.

Potential Applications

This technology can be applied in:

• Wireless communication systems
• Cellular networks
• Internet of Things (IoT) devices

Problems Solved

The technology helps in:

• Reducing inter-cell interference
• Improving signal quality
• Enhancing overall network performance

Benefits

The benefits of this technology include:

• Enhanced data transmission reliability
• Better user experience in crowded network environments
• Increased network capacity and efficiency

Potential Commercial Applications

This technology can be utilized in various commercial applications such as:

• Telecommunications companies
• Network equipment manufacturers
• IoT device manufacturers

Possible Prior Art

One possible prior art related to this technology is the use of beamforming techniques to mitigate interference in wireless communication systems.

How does this technology impact battery life in user equipment?

The article does not address the potential impact of this technology on the battery life of user equipment. Implementing interference mitigation mechanisms may require additional processing power, which could affect battery consumption.

What are the scalability considerations for deploying this technology in large-scale networks?

The scalability of implementing this technology in large-scale networks is not discussed in the article. Deploying interference mitigation techniques across a vast network may pose challenges in terms of coordination and resource allocation.

Original Abstract Submitted

techniques discussed herein can facilitate inter-cell interference mitigation. one example aspect is a user equipment (ue), configured to receive a network assistance indication associated with an interfering signal, where the interfering signal interferes with a physical downlink shared channel (pdsch) transmission. a time resource allocation of the interfering signal is different than a time resource allocation of the pdsch transmission. the ue is further configured to determine an interference and noise covariance estimation mechanism based on the network assistance indication then perform interference and noise covariance estimation based on the noise covariance estimation mechanism. the ue is further configured to perform mitigation of the interfering signal using a mitigation mechanism based on the interference and noise covariance estimation.