CSI Feedback Segmentation for Uplink Payload Limits
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Solution Overview
Problem
The increasing complexity and size of channel state information (CSI) reports in wireless communication systems, particularly due to machine learning-based CSI reports, often exceed the maximum payload size for physical uplink shared channel (PUSCH) or physical uplink control channel (PUCCH) resources, leading to transmission issues.
Innovation Solution
The UE is configured to omit a portion of or all of the CSI report to reduce the total payload size by replacing complex ML-based CSI reports with less complex non-ML-based CSI reports or truncating ML-based/non-ML-based CSI reports, ensuring the transmission fits within the maximum payload limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ML-based CSI reports are used to improve channel state information accuracy, then measurement precision is improved, but payload size increases beyond maximum limits
Solution Approach 1:
The patent extracts and transmits only the most critical CSI parameters (such as CQI, PMI, RI) while omitting less essential information. This selective extraction allows the system to maintain measurement precision for key parameters while reducing the overall payload size to fit within maximum transmission limits.
Solution Approach 2:
The CSI report is segmented into multiple parts or priority levels, where high-priority parameters are transmitted first. The patent divides the comprehensive ML-based CSI report into essential and optional components, ensuring that critical channel state information is always transmitted while less critical data can be omitted when payload size becomes excessive.
2Loss of information
If comprehensive CSI reports are transmitted to maintain data integrity, then information completeness is improved, but transmission overhead increases
Solution Approach 1:
The patent applies partial action by transmitting only the necessary portion of CSI information rather than the complete report. By sending a subset of CSI parameters that are sufficient for the network to make scheduling decisions, the system maintains adequate data integrity while significantly reducing transmission overhead and energy consumption.
Solution Approach 2:
The patent changes the parameter representation by using compact encoding schemes for CSI parameters. Instead of transmitting full-precision ML-based CSI data, the system uses quantized or compressed parameter representations that maintain essential information while reducing the number of bits required for transmission.
3Adaptability or versatility
If multiple CSI reports are transmitted to support multiple antenna configurations, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal CSI reporting mechanism that can adapt to multiple antenna configurations through a single streamlined report format. Instead of creating separate complex reports for each antenna configuration, the system uses a unified reporting structure that can represent different MIMO modes and antenna setups, thereby maintaining adaptability while reducing device complexity.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first device may generate a multi-part neural network based channel state information feedback (CSF) message that comprises: a first part that indicates contents of a second part, and the second part; and transmit the multi-part neural network based CSF to a second device. Numerous other aspects are provided.