Channel Matrix Reduction for Precoding Control
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Solution Overview
Problem
Existing multi-antenna transmission technologies face challenges in efficiently reducing the dimensionality of channel matrices for precoding, leading to deficient performance due to the selection of strongest channels, which affects the efficiency of MU-MIMO communication.
Innovation Solution
A method and device that determine a channel matrix, combine channel vectors into linear combinations to form a reduced matrix, and calculate a precoding matrix based on this reduced matrix, using Gram matrix calculations and eigenvectors to efficiently reduce dimensionality while considering channel strengths and similarities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the dimensionality of the channel matrix is reduced by selecting the strongest available channels, then the computational complexity is reduced, but the performance of the precoding matrix becomes deficient
Solution Approach 1:
The patent transforms the channel matrix by applying linear combinations to channel vectors, changing the representation parameters while preserving essential channel characteristics. This allows dimensionality reduction without simply selecting strongest channels, thereby maintaining precoding performance while reducing computational complexity.
Solution Approach 2:
The patent introduces an intermediate transformation process using linear combinations of channel vectors as a mediator between the full channel matrix and the reduced-dimensional precoding calculation. This intermediary step preserves channel information more effectively than direct selection methods.
2Productivity
If the dimensionality of the channel matrix is reduced, then the processing efficiency is improved, but the accuracy of channel representation deteriorates
Solution Approach 1:
The patent applies parameter transformation through linear combinations of channel vectors, changing how channel information is represented in the reduced matrix. This transformation preserves essential channel characteristics while reducing dimensionality, achieving both improved processing efficiency and maintained accuracy.
Solution Approach 2:
The patent reduces the dimensionality of the channel matrix from its original high-dimensional form to a lower-dimensional representation while preserving critical channel information through carefully constructed linear combinations, effectively projecting channel characteristics into a more efficient dimensional space.
Data Source
AI summary
A channel matrix representing characteristics of a multi-path channel between a transmitter device (210) equipped with multiple transmitter antennas (211, 212, 213, 214, 215) and a receiver device (220, 230, 240) equipped with multiple receiver antennas (221, 222, 231, 232, 241, 242) is determined. The channel matrix is organized in a first number of channel vectors each associated with a different one of the multiple receiver antennas (221, 222, 231, 232, 241, 242). The channel vectors are combined to a smaller second number of linear combinations of the channel vectors and a reduced channel matrix is composed from the linear combinations of the channel vectors. A precoding matrix is determined based on the reduced channel matrix, and multi-antenna transmission by the transmitter device is controlled based on the determined precoding matrix.