UE Channel Coding Learning Based on Capability Classification
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently performing channel coding, particularly in reducing learning time and resource wastage, and determining the necessity of learning based on terminal capability in wireless communication systems.
Innovation Solution
The method involves user equipment (UE) performing learning for encoding and decoding schemes based on received channel state information and resource information, allowing it to transmit and receive signals effectively, with different types of UE using neural networks and fixed schemes depending on their capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all user equipment performs learning for channel coding, then communication reliability improves, but device complexity and resource consumption increase
Solution Approach 1:
The patent applies local quality by differentiating channel coding learning based on UE capability. Only UEs with sufficient processing capabilities (third type UEs) perform learning, while first type UEs use fixed schemes and second type UEs have neural networks without learning. This selective approach maintains reliability where needed while reducing overall system complexity.
Solution Approach 2:
The patent implements dynamics by allowing UEs to dynamically select their operating mode based on capability and conditions. The system transitions from static fixed schemes to dynamic learning-based schemes adaptively, enabling UEs to switch between fixed encoding/decoding and learned schemes based on their processing capabilities and channel conditions.
2Reliability
If user equipment performs learning for channel coding, then coding performance improves, but learning time increases
Solution Approach 1:
The patent applies preliminary action by performing channel coding learning in advance during idle periods or when resources are available. UEs pre-train their neural networks and store learned encoding/decoding schemes, so that when actual data transmission occurs, the learning is already complete and no time is lost during critical communication moments.
Solution Approach 2:
The patent implements periodic action by scheduling learning operations at specific intervals or under specific conditions rather than continuously. UEs perform learning periodically when channel conditions change significantly or when resources become available, balancing the need for updated coding schemes with the constraint of limited processing time.
3Adaptability or versatility
If user equipment performs learning for channel coding, then adaptability to channel conditions improves, but resource consumption increases
Solution Approach 1:
The patent applies local quality by enabling adaptability only for UEs that can benefit from it based on their capability classification. Third type UEs with sufficient resources perform learning to adapt to channel conditions, while first type UEs use fixed schemes that consume less energy. This creates local optimization where adaptability is applied only where the energy cost is justified by the performance benefit.
Solution Approach 2:
The patent implements parameter changes by adjusting the learning behavior parameter based on UE capability and channel conditions. The system dynamically controls whether learning is performed, what type of learning is performed, and how frequently, changing these parameters adaptively to balance energy consumption against the need for channel adaptability.
Data Source
AI summary
The present disclosure discloses methods for operation of user equipment and a base station in a wireless communication system, and an apparatus for supporting same. According to an embodiment applicable to the present disclosure, the method for operation of user equipment may comprise the steps of: performing learning on at least one of an encoding method and a decoding method for data transmission; and transmitting a signal on the basis of the learned at least one encoding method and decoding method.