Bidirectional Perception Signaling for Multipath Beam Learning
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Solution Overview
Problem
Existing wireless communication systems, particularly in the context of 5G, face challenges in optimizing beam management and positioning accuracy due to the complexity of multipath channels and interference, which are not adequately addressed by non-perception-based adaptive beam weight learning approaches.
Innovation Solution
Implementing perception-based adaptive beam weight learning procedures, where user equipment (UE) and base stations utilize perception-based sensing operations to determine optimal beamforming strategies, enhancing communication performance by adjusting beam weights based on spatial regions of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If non-perception-based adaptive beam weight learning approaches are used, then device complexity is reduced, but wireless communication performance deteriorates due to inadequate handling of multipath channels and interference
Solution Approach 1:
The system performs perception-based sensing operations in advance to identify spatial regions of interest, multipath components, and interference sources before beamforming. This preliminary environmental understanding enables the base station and UE to pre-calculate optimal beam weights that account for multipath channels and interference, thereby improving communication reliability without adding complex real-time processing during data transmission.
2Measurement precision
If perception-based adaptive beam weight learning is implemented, then positioning accuracy is improved, but measurement and detection difficulty increases due to complex spatial region analysis
Solution Approach 1:
The system implements bidirectional feedback mechanisms where the base station transmits sensing reference signals and receives measurements from the UE, while the UE also provides feedback about detected spatial regions and multipath characteristics. This feedback loop enables iterative refinement of beam weights and spatial region identification, improving positioning accuracy by continuously adapting to the wireless environment without requiring overly complex one-shot detection.
3Reliability
If bidirectional perception-based approaches are used, then beam management performance is improved, but signaling overhead increases due to dual-directional indications
Solution Approach 1:
The patent combines uplink and downlink perception-based sensing operations into a unified beam management framework. The base station performs downlink sensing while the UE performs uplink sensing, and both sets of measurements are merged to determine optimal bidirectional beam weights. This merging approach improves beam management performance by utilizing all available spatial information while reducing redundant signaling compared to completely separate uplink and downlink procedures.
Data Source
AI summary
Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) determines that a perception-based approach to adaptive beam weight learning would provide improved performance of wireless communication with a base station over a wireless communication medium relative to non-perception-based approaches to adaptive beam weight learning, and transmits, to a network node, an indication for the base station to perform perception-based adaptive beam weight learning procedures for the wireless communication with the base station over the wireless communication medium.