Near-Field Precoding Codebook with Variable Distance Partitioning
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Solution Overview
Problem
The existing 5G standard's oversampling factor for antenna arrays is fixed, leading to excessively dense partitioning of near-distance basis vectors and excessively sparse partitioning of far-distance basis vectors, resulting in redundant feedback and large quantization errors in codebooks.
Innovation Solution
Introduce a variable 'distance' in the near-field codebook by dynamically configuring the coefficient based on a first function with parameters from candidate sets, ensuring accurate information feedback and positioning through non-uniform partitioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a fixed oversampling factor is used in the antenna array, then the codebook structure is simple and easy to implement, but the partitioning becomes excessively dense for near-distance basis vectors and excessively sparse for far-distance basis vectors, leading to redundant feedback and large quantization errors
Solution Approach 1:
The patent applies dynamics by making the oversampling factor variable rather than fixed. The oversampling factor is dynamically adjusted based on the distance parameter, allowing the codebook partitioning density to adapt to different transmission distances. This resolves the contradiction by enabling the system to use denser partitioning for near-distance scenarios and sparser partitioning for far-distance scenarios, thereby improving feedback precision without permanently increasing system complexity.
Solution Approach 2:
The patent changes the parameter of oversampling factor from a fixed value to a variable that depends on distance. By introducing distance as a controlling parameter, the system can optimize the oversampling factor for different transmission scenarios. This parameter change allows the codebook to achieve appropriate partitioning density for both near and far distances, eliminating redundant feedback while maintaining positioning accuracy.
2Device complexity
If the same spatial domain partitioning is used for codebooks with different distances, then the codebook design is simplified, but it results in redundant feedback for near-distance codebooks and large quantization errors for far-distance codebooks
Solution Approach 1:
The patent applies local quality by implementing different partitioning densities for different distance ranges. Instead of using a uniform partitioning approach, the system adjusts the oversampling factor locally based on the distance parameter. This allows near-distance codebooks to have denser partitioning for accurate feedback while far-distance codebooks use sparser partitioning to reduce redundancy, with each local region optimized for its specific requirements.
Solution Approach 2:
The patent segments the spatial domain partitioning into different regions based on distance. By dividing the codebook design into distance-dependent segments, the system can apply appropriate partitioning strategies for different ranges. This segmentation approach reduces information loss by ensuring each segment has the appropriate level of detail, avoiding both redundancy and quantization errors.
3Productivity
If a fixed oversampling factor is used, then the system has low complexity and fast processing, but it cannot adapt to different transmission distances, resulting in either redundant feedback or large quantization errors
Solution Approach 1:
The patent makes the oversampling factor dynamic by linking it to the distance parameter. This allows the system to adapt its processing characteristics based on transmission distance while maintaining relatively fast processing speeds. The dynamic adjustment occurs based on pre-defined distance ranges and corresponding oversampling factors, avoiding complex real-time optimization while achieving distance adaptability.
Solution Approach 2:
The patent changes the oversampling factor parameter based on distance conditions. By establishing a relationship between distance and oversampling factor, the system gains adaptability to different transmission scenarios. This parameter change enables the system to select appropriate oversampling levels for different distances, improving both feedback precision and positioning accuracy without significantly increasing processing complexity.
Data Source
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AI summary
Provided are an information transmission method, a device, and a storage medium. The information transmission method applied to a first communication node includes receiving a measurement reference signal; selecting a precoding matrix from a codebook based on the measurement reference signal, where the precoding matrix is obtained from a first preset number of first vectors, the first vectors are constructed by using at least a first function, the first function includes at least one of a first parameter or a second parameter, the first parameter belongs to a first candidate set, the second parameter belongs to a second candidate set, the difference between two adjacent elements in the first candidate set is determined by a first coefficient and the dimension of the first function, the first coefficient is a positive integer, the dimension of the first function indicates the number of elements in the first function, the first coefficient takes at least one value in response to a given value of the dimension of the first function, and the first preset number is an integer greater than or equal to 1; and reporting the selected precoding matrix to a second communication node.