Precoding Matrix Determination Using IDFT and DFT Vector Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In massive MIMO technology, the increasing number of antenna ports complicates the method for determining a precoding matrix, leading to higher calculation complexity and power consumption for receive end devices, particularly terminal devices in downlink transmission.
Innovation Solution
The method involves using a reference signal to measure channel state information (CSI) related to a Kronecker product of inverse discrete Fourier transform (IDFT) and discrete Fourier transform (DFT) vectors, allowing the terminal device to process and feedback CSI efficiently, reducing the complexity of determining the precoding matrix and improving data transmission reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the quantity of antenna ports is increased to improve signal quality and spatial multiplexing, then the precoding matrix determination complexity increases
Solution Approach 1:
The patent segments the precoding matrix into two components: a wideband precoding matrix determined through codebook traversal and a subband precoding matrix determined through simplified feedback. This segmentation allows the system to handle large antenna ports by dividing the complex determination process into manageable parts, reducing the overall complexity while maintaining signal quality.
Solution Approach 2:
The patent performs preliminary determination of the wideband precoding matrix using codebook traversal before subband processing. By pre-determining the wideband component, the system reduces the complexity of subsequent subband operations, as the terminal device only needs to provide simplified feedback rather than performing full precoding matrix determination for each subband.
2Productivity
If the quantity of antenna ports is increased to improve spectrum utilization, then power consumption of the terminal device increases
Solution Approach 1:
By segmenting the precoding matrix into wideband and subband components, the patent reduces the computational burden on the terminal device. The wideband precoding matrix is determined through codebook traversal, while the subband precoding matrix uses simplified feedback mechanisms, thereby reducing overall power consumption while maintaining high spectrum utilization.
Solution Approach 2:
The patent performs preliminary determination of the wideband precoding matrix before subband processing. This preliminary action reduces the real-time computational requirements at the terminal device, lowering power consumption during actual data transmission while still enabling high spectrum utilization through massive MIMO.
3Measurement precision
If two-level feedback is used to determine precoding matrix, then measurement complexity at the terminal device increases
Solution Approach 1:
The patent segments the feedback process into two levels: wideband feedback for the wideband precoding matrix and subband feedback for the subband precoding matrix. This segmentation allows the terminal device to provide feedback in a structured manner, reducing measurement complexity while maintaining channel state information accuracy through the combination of both feedback levels.
Data Source
AI summary
A communication method, including: receiving a reference signal, where the reference signal is used for channel measurement; sending CSI, where the CSI is used to indicate one or more measured values, and the measured values are used to determine a precoding matrix, or the measured values are a precoding matrix. The measured value is related to a first group of base vectors and a second group of base vectors, or the measured value is related to a Kronecker product of the first group of base vectors and the second group of base vectors; the first group of base vectors includes an inverse discrete Fourier transform OFT vector or a Kronecker product of two IDFT vectors, and the second group of base vectors include a discrete Fourier transform DFT vector.