Adaptive Beamforming Using Covariance Matrix Estimation
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Solution Overview
Problem
Current beam training methods in millimeter wave communication systems incur significant latency due to the multistage hierarchical approach, which increases the duration of beam sweeps proportionally with the number of clusters, exceeding delay budgets and degrading system performance.
Innovation Solution
The proposed solution involves reducing latency by adaptively configuring beam weights using a subset of transmit (TX) beams, where a user equipment (UE) measures signal strength values from pilot signals transmitted by a network entity, calculates an accumulated signal strength value, and estimates a channel covariance matrix to determine optimal beamforming vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multistage hierarchical beam training approach is used, then beam selection accuracy is improved, but beam sweep duration increases proportionally with the number of clusters, exceeding delay budgets
Solution Approach 1:
The patent segments the beam training process into two phases: a first phase using a first set of beams and a second phase using a second set of beams. This segmentation allows the system to perform beam training more efficiently by dividing the complex multistage hierarchical approach into manageable parts, reducing the overall beam sweep duration while maintaining beam selection accuracy.
Solution Approach 2:
The patent employs partial action by using a subset of beams (second set of beams) for the second phase of training after the first phase. Instead of exhaustively searching all possible beams through complete multistage hierarchical procedures, the system performs partial beam training that is sufficient to achieve the required accuracy within the delay budget constraints.
2Reliability
If all TX beams are used for beam training, then communication quality is improved, but system complexity and training time increase
Solution Approach 1:
The patent segments the TX beams into a first set of beams and a second set of beams, using different subsets for different phases of training. This segmentation reduces the complexity of managing and processing all beams simultaneously while maintaining communication quality through the coordinated use of both beam sets across multiple training phases.
Solution Approach 2:
The patent dynamically adapts the beam sets used for training based on the training phase and channel conditions. The system transitions from using the first set of beams to using the second set of beams, and can adjust the composition of these sets based on accumulated signal strength values and channel covariance matrix estimates, optimizing the balance between training quality and system complexity.
3Loss of time
If beam weights are adaptively configured using a subset of beams, then latency is reduced with linear growth in antenna dimensionality, but the number of beams to process is reduced
Solution Approach 1:
The patent changes the parameter of beam set composition based on antenna dimensionality and training phase. As the number of antenna elements increases, the system adapts by using appropriately sized subsets of beams for training, ensuring that the number of beams to process grows linearly rather than quadratically with antenna dimensionality, thus controlling latency while managing processing requirements.
Data Source
AI summary
Systems, methods, and apparatuses, including computer programs encoded on computer storage media, are directed to configuration of a beamforming vector using an estimated covariance matrix, which may reduce latency commensurate with a beam training procedure. An apparatus may receive, from another apparatus, information indicating a configured subset of a set of TX beams at the other apparatus. The other apparatus may transmit pilot signals via the configured subset of the set of TX beams. The apparatus may transmit, to the other apparatus, information associated with the set of beam pairs of the apparatus and the other apparatus. The apparatus may estimate a channel covariance matrix using the accumulated signal strength value, and may calculate a beamforming vector from the channel covariance matrix. The apparatus and the other apparatus may perform a beam training procedure using respective beamforming vectors.