17817304. CHANNEL STATE FEEDBACK WITH DICTIONARY LEARNING simplified abstract (QUALCOMM Incorporated)
Contents
CHANNEL STATE FEEDBACK WITH DICTIONARY LEARNING
Organization Name
Inventor(s)
Hamed Pezeshki of San Diego CA (US)
Arash Behboodi of Amsterdam (NL)
Taesang Yoo of San Diego CA (US)
Mahmoud Taherzadeh Boroujeni of San Diego CA (US)
CHANNEL STATE FEEDBACK WITH DICTIONARY LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17817304 titled 'CHANNEL STATE FEEDBACK WITH DICTIONARY LEARNING
Simplified Explanation
The abstract of this patent application describes a wireless communication system where a user equipment (UE) can report channel state information (CSI) using a learned dictionary of sparse vectors. The UE determines this learned dictionary either by receiving a shared dictionary from a similar and nearby UE or by training it based on logged CSI measurements. The UE then indicates the learned dictionary to a serving base station and reports a sparse vector representing the CSI based on the learned dictionary.
- The UE in a wireless communication system can report CSI using a learned dictionary of sparse vectors.
- The learned dictionary can be obtained from a similar and nearby UE or trained based on logged CSI measurements.
- The UE indicates the learned dictionary to a serving base station.
- The UE measures CSI for multiple channels and reports a sparse vector representing the CSI using the learned dictionary.
Potential applications of this technology:
- Wireless communication systems that require efficient reporting of channel state information.
- Systems where user equipment needs to adapt its transmission based on channel conditions.
- Networks that rely on accurate and timely CSI feedback for optimization and resource allocation.
Problems solved by this technology:
- Efficient utilization of wireless communication resources by reporting sparse vectors instead of full CSI.
- Improved accuracy of CSI reporting by using a learned dictionary tailored to the specific UE.
- Reduced overhead in training and transmitting CSI information.
Benefits of this technology:
- Enhanced performance and reliability of wireless communication systems.
- Improved spectral efficiency by optimizing resource allocation based on accurate CSI feedback.
- Reduced signaling overhead and bandwidth consumption by reporting sparse vectors instead of full CSI.
Original Abstract Submitted
In a wireless communication system, a user equipment (UE) may report channel state information (CSI) using a learned dictionary defining a set of sparse vectors. The UE determines a learned dictionary for CSI reporting. For example, the UE receives a shared dictionary from a similar and nearby UE or the UE trains the learned dictionary based on logged CSI measurements. The UE indicates the learned dictionary to a serving base station. The UE measures CSI for a plurality of channels. The UE reports a sparse vector representing the CSI based on the learned dictionary to the serving base station.
