Beam Pattern Sampling Grids for Accurate 5G Positioning and Sensing
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Solution Overview
Problem
Existing wireless communication systems, particularly in 5G networks, face challenges in efficiently obtaining and representing beam patterns for improved positioning and sensing, especially in environments with varying beam gains, which affects the accuracy and efficiency of location determination for mobile devices.
Innovation Solution
A beam pattern processing device configures a sampling method defining a sampling grid, segmenting regions based on beam gain variations, and associating different sampling direction densities to improve the representation of beam shapes, allowing for more accurate beam gain measurements in arbitrary directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a uniform sampling grid is used for beam pattern measurement, then the measurement process is simple, but the representation accuracy of beam patterns with varying gains is insufficient
Solution Approach 1:
The sampling grid is segmented into multiple regions based on beam gain variations. Different regions are assigned different sampling densities, with higher sampling rates in regions where beam gain changes rapidly and lower sampling rates in regions with gradual variations. This segmentation approach maintains measurement simplicity while significantly improving beam pattern representation accuracy.
Solution Approach 2:
The patent applies local quality by assigning different sampling densities to different regions of the beam pattern. Regions with high beam gain variations receive denser sampling, while regions with stable gains use sparser sampling. This localized adaptation of sampling quality optimizes the overall measurement accuracy without uniformly increasing complexity across the entire measurement process.
2Measurement precision
If higher sampling density is used throughout the beam pattern, then the representation accuracy improves, but the signaling overhead and processing complexity increase
Solution Approach 1:
The beam pattern measurement space is divided into multiple regions with different sampling requirements. By segmenting the measurement domain, the system applies high sampling density only where necessary (in regions with rapid gain variations) and low sampling density in other regions, thereby reducing overall signaling overhead and processing complexity while maintaining accuracy where it matters most.
Solution Approach 2:
The patent dynamically adjusts the sampling density parameter based on the local characteristics of the beam pattern. Regions with high curvature or rapid gain changes are assigned higher sampling densities, while regions with gradual variations use lower densities. This parameter adaptation reduces the total number of measurements required, lowering signaling overhead and processing complexity without sacrificing critical measurement accuracy.
Data Source
AI summary
A beam pattern processing device includes: one or more memories; a transceiver; and one or more processors, communicatively coupled to the one or more memories and the transceiver. The one or more processors are configured to: configure a beam pattern information to include a sampling method of a plurality of sampling methods defining a sampling grid; send a request, including the beam pattern information, for a sampled beam pattern of the network device; and receive the sampled beam pattern obtained based on the beam pattern information.