Adaptive Channel Model Selection for Wireless Positioning
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently reducing computational requirements for generating wireless channel profiles, particularly in 5G networks, where high accuracy and density demand significant computational resources.
Innovation Solution
The use of a non-ray tracing channel model is selected based on criteria such as environmental layout, line-of-sight detection, and desired positioning accuracy to model wireless channel profiles between user equipment and network nodes, reducing computational demands while maintaining positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a ray-tracing-based channel model is used to model wireless channel profiles, then positioning accuracy is improved, but computational requirements increase significantly
Solution Approach 1:
The system dynamically selects between ray-tracing-based and non-ray-tracing channel models based on real-time environmental conditions, UE mobility state, and positioning accuracy requirements. This dynamic adaptation allows the system to use computationally intensive ray tracing only when necessary (e.g., static environments, high accuracy required) while using lighter models for mobile scenarios or lower accuracy requirements, thus resolving the contradiction between positioning accuracy and computational load
Solution Approach 2:
The patent applies different channel modeling approaches to different spatial regions and environmental zones. Ray tracing is applied selectively in areas where high precision is critical (e.g., indoor environments, areas with complex multipath), while non-ray-tracing models are used in open or predictable environments. This localized application of modeling complexity optimizes the balance between accuracy and computation
2Speed
If high-density deployments and higher frequency bands are used in 5G networks, then data transfer speeds and coverage are improved, but computational resources required for channel profiling increase
Solution Approach 1:
The system adjusts modeling parameters such as frequency band, propagation environment type, and UE mobility state to select appropriate channel models. For high-frequency bands with dense deployments, the system uses simplified models with adjusted parameters rather than full ray tracing, maintaining acceptable accuracy while reducing computational burden
Solution Approach 2:
The system performs preliminary assessment of environmental conditions, UE mobility, and positioning requirements before selecting a channel model. This preliminary action allows the system to pre-determine the appropriate level of computational complexity needed, avoiding unnecessary ray tracing computations while ensuring adequate accuracy for the specific scenario
Data Source
AI summary
Disclosed are techniques for communication. In an aspect, an apparatus determines, based on one or more criteria, to use a non-ray tracing channel model, instead of a ray-tracing-based channel model, to model a wireless channel profile between a user equipment (UE) and one or more network nodes, and performs one or more positioning operations associated with the UE and the one or more network nodes based on the wireless channel profile between the UE and the one or more network nodes modeled by the non-ray tracing channel model.