CSI Feedback with Orthogonal Component Extraction
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Solution Overview
Problem
Existing massive MIMO systems face challenges in reducing Channel State Information (CSI) feedback overhead while maintaining accurate CSI acquisition, which affects system performance and increases processing complexity at user equipment (UE).
Innovation Solution
The proposed solution involves a method for CSI feedback with low overhead, where a first device extracts orthogonal components from a reference signal, transforms and quantizes these components, and transmits the quantized parameters to a second device. The second device then uses a deep neural network to recover the CSI from the one-bit quantized feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CSI feedback methods are used in massive MIMO systems, then accurate CSI acquisition is achieved, but CSI feedback overhead and processing complexity increase significantly
Solution Approach 1:
The patent extracts only the essential channel characteristics by decomposing the channel into orthogonal components (e.g., angle of arrival/departure, delay spread) rather than feedback the complete CSI matrix. This extraction approach reduces the amount of data to be fed back while preserving the most critical information for beamforming and scheduling decisions
Solution Approach 2:
The patent transforms the CSI representation from traditional complex channel coefficients to a different parameter domain (e.g., angular parameters, delay parameters) that can be more efficiently quantized and fed back. This parameter transformation enables lower precision quantization while maintaining acceptable CSI accuracy
2Loss of information
If traditional CSI feedback methods are used, then complete channel information is obtained, but feedback overhead increases
Solution Approach 1:
The patent extracts only the essential channel characteristics by decomposing the channel into orthogonal components (e.g., angle of arrival/departure, delay spread) rather than feedback the complete CSI matrix. This extraction approach reduces the amount of data to be fed back while preserving the most critical information for beamforming and scheduling decisions
Solution Approach 2:
The patent segments the channel information into distinct orthogonal components (spatial parameters, delay parameters, Doppler parameters) that can be independently processed and quantized. This segmentation allows each component to be optimized separately for feedback efficiency
3Measurement precision
If high precision CSI feedback is transmitted, then accurate channel state information is achieved, but processing latency increases
Solution Approach 1:
The patent transforms the CSI representation from traditional complex channel coefficients to a different parameter domain (e.g., angular parameters, delay parameters) that can be more efficiently quantized and fed back. This parameter transformation enables lower precision quantization while maintaining acceptable CSI accuracy, thereby reducing feedback overhead and processing time
Data Source
AI summary
Example embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of a Channel State Information (CSI) feedback with low overhead. The method comprises in response to receiving, from a second device, a reference signal on a channel between the first device and the second device, obtaining a first component and a second component from the reference signal, the first component and the second component being orthogonal to each other; determining a first transformed component and a second transformed component for characterizing the channel by performing a transformation on the first component and the second component; generating a set of parameters associated with characteristics of the channel by quantizing the first transformed component and the second transformed component; and transmitting the set of parameters to the second device. The proposed CSI feedback can even be flexibly combined with existing overhead reduction schemes such as the beamformed CSI-RS and CSI compression, which further reduces the CSI overhead. Furthermore, the proposed scheme ensures very fast processing at UE and reduces the latency.