Beam Training and Data Transmission Alternation for mmWave Alignment
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Solution Overview
Problem
The challenge in wireless communication systems is to efficiently determine an optimal beam for high-throughput communication, particularly in mmWave frequency bands, where signal attenuation is significant, and beam training must be repeated due to variable environmental conditions, requiring accurate and efficient beam alignment.
Innovation Solution
A wireless communication apparatus and method that utilize an antenna array, a transceiver, and a controller to estimate channels using training beams and calculate data beams based on objective functions, allowing for dynamic beam adjustment during beam training and data transmission phases, enabling efficient beamforming and alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beam training is repeated frequently to adapt to variable wireless communication environments, then beam alignment accuracy is improved, but communication overhead and time consumption increase
Solution Approach 1:
The system performs preliminary channel estimation using training beams before actual data transmission. The controller calculates optimal data beams in advance during beam training phases, preparing beamforming weights beforehand so that when data transmission occurs, the beams are already optimized, eliminating the need for frequent re-training.
Solution Approach 2:
The system maintains continuous beam alignment by alternating between beam training phases and data transmission phases. During data transmission phases, the previously calculated data beams continue to be used, maintaining useful communication action without interruption, while beam training phases periodically update the beam alignment to adapt to environment changes.
2Measurement precision
If traditional exhaustive beam training methods are used to ensure accurate beam alignment, then beam alignment accuracy is improved, but system complexity and training overhead increase
Solution Approach 1:
The system replaces mechanical exhaustive beam sweeping with a mathematical calculation-based approach. Instead of physically testing every possible beam direction, the controller uses channel estimation results from training beams to calculate optimal data beamforming weights through objective functions, substituting mechanical search with computational optimization.
Solution Approach 2:
The system changes the parameter space by working in the beamforming weight domain rather than the physical beam direction domain. By transforming the problem from searching through discrete beam directions to optimizing continuous beamforming weights based on channel state information, the system reduces the effective search space and complexity.
3Measurement precision
If more training beams are used to improve channel estimation accuracy, then channel estimation precision is improved, but training phase duration and overhead increase
Solution Approach 1:
The system extracts only the essential channel state information needed for data beam calculation from the training beam measurements. Instead of using all training beam data extensively, the controller extracts key channel parameters and uses them to calculate data beams, reducing the processing burden and allowing faster transition to data transmission while maintaining estimation accuracy.
Data Source
AI summary
A wireless communication method is provided in which beam training phases alternate with data transmission phases. The method includes estimating a first channel based on a signal received using one or more first training beams in a first beam training phase, and calculating, based on the estimated first channel and a first objective function corresponding to the estimated first channel, a first data beam for a first data transmission phase from the one or more first training beams in the first beam training phase, the first data transmission phase following the first beam training phase.