Bistatic RF Sensing Resource Allocation for UL/DL Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Bistatic RF sensing operations in wireless networks face challenges due to increased signaling overhead and the need for efficient resource allocation to enhance target detection and tracking, particularly in 5G wireless systems with diverse wireless nodes.
Innovation Solution
A method and apparatus for configuring bistatic RF sensing operations by receiving RF sensing information, determining target locations, and allocating RF sensing resources based on target parameters and node locations, utilizing machine learning models to fuse UL and DL RF sensing measurements for enhanced target detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bistatic RF sensing operations are implemented in wireless networks, then target detection and tracking capabilities are enhanced, but signaling overhead increases
Solution Approach 1:
The patent combines uplink and downlink RF sensing measurements into a unified bistatic sensing framework. By merging measurement data from multiple wireless nodes (gNBs and UEs) and fusing them through machine learning models, the system enhances target detection accuracy while managing signaling overhead through coordinated resource allocation.
Solution Approach 2:
The patent introduces a location server as an intermediary that coordinates bistatic sensing operations. The location server manages resource allocation, receives measurement reports from multiple nodes, and processes fused measurements to determine target locations, thereby reducing the signaling burden on individual nodes and optimizing overall system performance.
2Area of stationary object
If RF sensing resources are allocated for multiple wireless nodes, then sensing coverage is improved, but resource allocation complexity increases
Solution Approach 1:
The patent implements dynamic resource allocation for RF sensing based on real-time sensing requirements, target locations, and network conditions. The location server adjusts uplink and downlink sensing resource allocation dynamically, optimizing sensing coverage while managing complexity through adaptive decision-making rather than static configuration.
Solution Approach 2:
The patent changes resource allocation parameters (time, frequency, power) based on target location and sensing priorities. By adjusting these parameters dynamically according to measured target positions and sensing requirements, the system expands effective coverage while maintaining manageable allocation complexity through rule-based adaptation.
3Measurement precision
If machine learning models are used to fuse UL and DL measurements, then target detection performance is enhanced, but processing requirements increase
Solution Approach 1:
The patent segments the measurement fusion process into distributed preprocessing at individual nodes (feature extraction from raw measurements) and centralized processing at the location server (model-based fusion). This segmentation reduces the computational burden on any single node while achieving enhanced detection performance through collaborative processing.
Solution Approach 2:
The location server acts as an intermediary that handles the computationally intensive machine learning model execution. By centralizing the ML-based fusion process at the location server rather than distributing it across all wireless nodes, the system achieves enhanced detection performance while concentrating processing requirements in a single entity with sufficient computational resources.
Data Source
AI summary
Techniques are provided for allocating RF sensing resources for bistatic RF sensing operations in wireless networks. An example method for configuring bistatic radio frequency sensing operations according to the disclosure includes receiving radio frequency sensing information from a plurality of wireless nodes, determining a target location based at least in part on the radio frequency sensing information, determining a bistatic radio frequency sensing resource allocation based at least in part on the target location and a location of at least one of the plurality of wireless nodes, and providing radio frequency sensing resource information to the plurality of wireless nodes based on the bistatic radio frequency sensing resource allocation.