Multi-Resolution Beam Refinement Protocol for mmW WLAN
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Solution Overview
Problem
Current beamforming techniques in WLAN systems are limited in their ability to efficiently refine beams, particularly in millimeter wave (mmW) environments, leading to suboptimal communication performance due to fixed resolution and lengthy training processes.
Innovation Solution
The Multi-Resolution Beam Refinement Protocol (MR-BRP) allows access points and stations to perform multi-resolution beamforming training by adjusting sub-beam resolution and antenna weight vectors, enabling the identification of optimal beam pairs through sector level sweeps and iterative refinement, supporting single or multiple beams, and facilitating beam tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed resolution beamforming training is used, then the training process is simple, but the beam refinement accuracy is suboptimal
Solution Approach 1:
The beamforming training process is segmented into multiple resolution levels (e.g., first resolution, second resolution, third resolution). Each level uses different antenna weight vectors with varying beam widths and angular spreads. This segmentation allows the system to progressively refine beams from coarse to fine resolution, improving accuracy without requiring a single complex high-resolution training process.
Solution Approach 2:
The system dynamically adjusts the resolution level during beamforming training. It starts with lower resolution levels using wider beams for initial sector identification, then transitions to higher resolution levels with narrower beams for precise beam refinement. This dynamic adaptation of resolution allows the system to balance between training speed and refinement accuracy.
2Measurement precision
If high resolution beamforming training is used, then the beam refinement accuracy is improved, but the training time increases
Solution Approach 1:
The training process is divided into multiple resolution levels where lower levels use fewer antenna weight vectors for quick initial alignment, and higher levels use more vectors for detailed refinement. This segmentation reduces the total training time compared to performing a single high-resolution training from scratch.
Solution Approach 2:
The system performs preliminary beam alignment using lower resolution levels before proceeding to higher resolution refinement. This preliminary action establishes a coarse beam direction that guides subsequent fine-resolution training, reducing the search space and overall training time.
3Adaptability or versatility
If multiple beams are supported, then the system versatility is improved, but the device complexity increases
Solution Approach 1:
Multiple beams are managed through segmented resolution levels, where each beam undergoes independent but structured refinement through the same multi-resolution framework. This segmentation provides a systematic approach to managing multiple beams, reducing the complexity of beam management through standardized procedures.
Solution Approach 2:
The multi-resolution beamforming training protocol serves as a universal framework that can handle multiple beams, single-user and multi-user scenarios, and different resolution requirements. This universal approach simplifies the system design by providing a single protocol that adapts to various beam management needs rather than requiring separate mechanisms for each scenario.
4Measurement precision
If sub-beam resolution is increased, then the beamforming precision is improved, but the number of antenna elements required increases
Solution Approach 1:
The system dynamically adjusts the effective resolution by selectively applying different antenna weight vectors at different stages. Instead of using a large number of antenna elements throughout, the system uses a smaller set of physical elements with dynamically switched weight vectors to achieve variable resolution, effectively reducing the required number of antenna elements.
Solution Approach 2:
The system changes the parameter of angular spread for different resolution levels. By adjusting the angular spread parameter of antenna weight vectors rather than increasing the number of antenna elements, the system achieves different sub-beam resolutions using the same physical antenna array, thereby avoiding the need for additional antenna elements.
Data Source
AI summary
Systems, methods, and instrumentalities are disclosed for multi-resolution training, for example, in millimeter wave (mmW) WLAN systems. In a Multi-Resolution Beam Refinement Protocol (MR-BRP), an access point (AP)/PBSS control point (PCP) and a station (STA) may perform multi-resolution beamforming training, for example, by changing a sub-beam resolution or by maintaining sub-beam resolution while changing a resolution of the beamforming training between levels or stages of training. Sub-beam resolution may be changed, for example, by assigning different angular spreads to or by downselecting a number of antenna elements while keeping inter-element spacing constant between levels of training. Resolution of beamforming training may be changed, for example, by downsampling sub-beams or by downsampling antenna elements while adjusting inter-element spacing. Beamforming training (e.g. refinement) levels may refine beams by changing a resolution of antenna weight vectors (AWVs). An AP/PCP and STA may search through a sector multiple times with sub-beams of different resolution to identify a correct pair of sub-beams at a desired resolution. MR-BRP may be used for single or multiple beams, for example, to generate M sub-beams (AWVs) for N beams sequentially or in parallel. MR-BRP may be used for beam tracking. Devices may save the best sub-beam at each level of MR-BRP and may revert (fall back) to a sub-beam at previous level. MR-BRP signaling may indicate MR-BRP capability, type, frame format, etc.