Compressed Beamforming Feedback Precomputation
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Solution Overview
Problem
Current wireless local area network (WLAN) systems face inefficiencies in computing beamforming feedback, particularly in determining column sorting orders and scaling factors during modified QR decomposition, which delays and increases the computational complexity of generating compressed beamforming feedback.
Innovation Solution
A method is introduced where column sorting orders and scaling factors are precomputed based on an intermediate matrix derived from the channel matrix, using norms and inner products, before performing modified QR decomposition, thereby separating these computations from the QR decomposition process and reducing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If column sorting orders and scaling factors are computed during modified QR decomposition, then accurate compressed beamforming feedback is generated, but computational complexity increases and processing time delays
Solution Approach 1:
The patent precomputes column sorting orders and scaling factors based on the channel matrix H before performing modified QR decomposition. Specifically, it computes B=HHH, then determines column sorting orders and scaling factors from B in advance, which are then used as inputs to the QR decomposition process. This preliminary computation separates the complexity from the time-critical QR decomposition path, reducing processing time while maintaining feedback accuracy.
2Measurement precision
If column sorting orders and scaling factors are computed during modified QR decomposition, then accurate compressed beamforming feedback is generated, but processing time increases
Solution Approach 1:
The patent performs preliminary computation of column sorting orders and scaling factors from the channel matrix H before the modified QR decomposition. By computing B=HHH first and extracting sorting orders and scaling factors from B, the system prepares all necessary parameters in advance, making the subsequent QR decomposition faster and reducing overall processing time while preserving feedback accuracy.
3Productivity
If full modified QR decomposition is performed without precomputation, then compressed beamforming feedback is generated, but hardware requirements and power consumption increase
Solution Approach 1:
The patent segments the beamforming feedback computation into distinct phases: precomputation phase (computing B=HHH and extracting column sorting orders and scaling factors) and QR decomposition phase. This segmentation allows the system to perform computationally intensive operations in the precomputation phase using available hardware, then execute the simplified QR decomposition with precomputed parameters, reducing real-time hardware requirements and power consumption.
Data Source
AI summary
A method for providing a compressed beamforming feedback of a communication channel includes receiving, at a first communication device, a plurality of training signals from a second communication device via the communication channel, determining a channel matrix corresponding to the communication channel based on the plurality of training signals, precomputing a sequence of column sorting orders and/or a sequence of scaling factors based on a first intermediate matrix derived from the channel matrix in advance of performing a modified QR decomposition, performing the modified QR decomposition to derive the compressed beamforming feedback based on the first intermediate matrix with the precomputed column sorting orders and/or scaling factors as an input, and transmitting the compressed beamforming feedback from the first communication device to the second communication device to enable the second communication device to steer at least one subsequent transmission to the first communication device based on the compressed beamforming feedback.