Multi-Cell CSI Prediction for Beamforming Without SCell SRS
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently compressing channel state information (CSI) of a primary cell (PCell) with low complexity and accurately predicting channel information of a secondary cell (SCell) without sufficient SRS resources or support for uplink carrier aggregation, leading to delayed SRS update cycles and inefficient beamforming.
Innovation Solution
A method and apparatus for compressing CSI of a PCell using low-resolution feedback and recovering SRS channel information to predict CSI for both PCell and SCell, enabling integrated channel prediction and beamforming weight generation for both cells, even in scenarios where UL SRS antenna switching is not supported.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If SRS resources are divided between carriers to support uplink carrier aggregation, then channel information of multiple cells can be obtained, but SRS update cycle is delayed and resource efficiency decreases
Solution Approach 1:
The patent applies universality by enabling SRS resources configured for PCell to serve dual purposes: both for obtaining PCell channel information and for predicting SCell channel information. This multi-functionality eliminates the need for separate SRS resources for each cell, resolving the contradiction between obtaining multi-cell channel information and maintaining SRS update efficiency.
Solution Approach 2:
The patent uses copying by creating virtual SCell channel information from PCell channel information through prediction algorithms. Instead of requiring actual SRS transmissions on SCell, the system copies and adapts PCell channel characteristics to generate SCell channel estimates, thereby avoiding resource division delays while still obtaining necessary SCell channel information.
2Device complexity
If UE does not support uplink carrier aggregation or SRS carrier antenna switching function, then device complexity is reduced, but channel information of SCell cannot be obtained
Solution Approach 1:
The patent introduces an intermediary approach by using PCell channel information as a mediator to obtain SCell channel information. Instead of requiring direct SRS transmissions from SCell (which would demand advanced UE capabilities), the system uses PCell measurements as an intermediary source to infer SCell channel characteristics through prediction, thereby supporting UEs with simpler capabilities.
Solution Approach 2:
The patent applies preliminary action by obtaining and processing PCell channel information in advance to prepare for SCell channel prediction. The system performs channel estimation on PCell first, then uses this pre-obtained information as a basis for predicting SCell channel conditions, enabling SCell operation without requiring the UE to have advanced uplink carrier aggregation or antenna switching capabilities.
3Quantity of substance
If low resolution CSI feedback is used for PCell, then feedback overhead is reduced, but compression accuracy decreases
Solution Approach 1:
The patent applies parameter changes by transforming the representation of channel information from high-dimensional precise measurements to low-dimensional compressed parameters. By changing the parameter representation (using codebook indices and precoding matrices instead of full channel matrices), the system achieves both reduced feedback overhead and maintained compression accuracy, as the essential channel characteristics are preserved in the compressed form.
Data Source
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AI summary
The present disclosure relates to a 5G or 6G communication system for supporting higher data transmission rates. According to various embodiments of the disclosure, the present invention comprises the steps of: compressing channel information about a primary cell on the basis of channel status information (CSI) feedback received from a terminal; performing CSI recovery on compressed channel information about the secondary cell on the basis of the compressed channel information; performing the CSI recovery, and then acquiring predicted CSI of each of the primary cell and the secondary cell; generating a beamforming weight for the primary cell on the basis of the predicted CSI of the primary cell; and generating a beamforming weight for the secondary cell on the basis of the predicted CSI of the secondary cell.