Integrated Sensing Communication Channel Modeling Forward Backward Scattering
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Solution Overview
Problem
There is a lack of effective channel modeling research in integrated sensing and communication systems, which is crucial for the development of 6G wireless communication systems that require precise sensing and wide coverage communication, especially with the overlap of frequency bands used by traditional sensing and communication systems.
Innovation Solution
A novel integrated sensing and communication channel modeling method combining forward scattering and backward scattering is proposed, which involves determining antenna configurations, sensing channel impulse responses, geometric random modeling of scattering paths, and weighting the line-of-sight, forward scattering, and backward scattering components to obtain a complete communication channel impulse response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional sensing and communication systems use separate frequency bands, then system independence is maintained, but frequency band overlap occurs in 6G systems requiring integrated sensing and communication
Solution Approach 1:
The patent segments the communication channel into multiple scattering components (forward scattering, backward scattering, and non-scattering paths) to accurately model the integrated sensing and communication channel. This segmentation allows each component to be characterized separately using sensed channel parameters, improving overall channel information accuracy while utilizing overlapping frequency bands.
Solution Approach 2:
The patent introduces sensing channel parameters as an intermediary to bridge the gap between sensing and communication systems. By using sensed channel impulse responses and extracted parameters (delay, Doppler, angle of arrival) as intermediaries, the system achieves accurate communication channel modeling despite frequency band overlap and integration challenges.
2Measurement precision
If channel modeling relies solely on geometric random modeling, then modeling simplicity is maintained, but channel accuracy is insufficient for integrated sensing and communication
Solution Approach 1:
The patent merges geometric random modeling with sensing channel information to create a hybrid channel modeling approach. By combining the simplicity of geometric random modeling with the accuracy of sensed channel parameters, the system achieves high channel modeling accuracy without excessive complexity. The sensed parameters guide the geometric random generation of scattering paths.
Solution Approach 2:
The patent performs preliminary sensing to obtain channel impulse responses and extract parameters (delay, Doppler frequency, angle of arrival) before conducting communication channel modeling. This preliminary action provides accurate initial information that guides subsequent geometric random modeling, ensuring high accuracy while maintaining reasonable complexity through structured parameter usage.
3Measurement precision
If only backward scattering is used for channel modeling, then sensing simplicity is maintained, but communication coverage and accuracy are limited
Solution Approach 1:
The patent segments the channel into backward scattering paths and forward scattering paths, using each for their respective advantages. Backward scattering provides accurate angle of arrival information for positioning, while forward scattering extends coverage. This segmentation allows the system to achieve high accuracy and wide coverage without excessive sensing complexity by utilizing both scattering mechanisms.
Solution Approach 2:
The patent makes the sensing system multi-functional by using it for both backward scattering (positioning and channel estimation) and forward scattering (coverage extension). The same sensing infrastructure serves multiple purposes: obtaining channel parameters for accuracy and enabling forward scattering paths for extended coverage, thereby achieving both high precision and system versatility.
4Productivity
If sensing and communication use separate processing algorithms, then system independence is maintained, but resource efficiency decreases
Solution Approach 1:
The patent creates a unified processing framework where the same channel modeling algorithm serves both sensing and communication functions. The geometric random modeling approach, guided by sensed parameters, generates channel models that are simultaneously used for sensing performance evaluation and communication system design, achieving resource efficiency without significantly increasing processing complexity through shared computational structures.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enhances channel accuracy by utilizing sensed channel parameters to model communication channels, dividing non-line-of-sight paths into forward and backward scattering components, and weighting them based on probabilities, thereby improving channel certainty and communication quality.
Implementation Method 1
a geometric random modeling is performed on forward scattering paths at a non-line-of-sight in a communication channel
Implementation Method 2
a backward scattering path component at the non-line-of-sight and a line-of-sight component in the communication channel are geometrically modeled
Data Source
AI summary
Disclosed is a novel integrated sensing and communication channel modeling method combining forward scattering and backward scattering. The method includes the following steps: setting application scenarios and antenna parameters; estimating channel state information through a mono-static sensing means, and determining positions of a communication terminal and positions and motion information of scatterers that are backward scattered in environment; dividing non-line-of-sight paths of the communication channel into forward scattering paths and backward scattering paths based on whether the scatterers can be sensed by a sensing channel, generating forward scattering paths by adopting a geometric random modeling method and generating the backward scattering paths by adopting a geometric modeling method based on obtained sensing information parameters; weighted-summing the line-of-sight, the forward scattering paths, and the backward scattering paths according to probabilities to obtain a complete communication channel impulse response. The present disclosure proposes a relatively comprehensive integrated sensing and communication channel modeling method for the first time, and the simulation results of the channel model are in good agreement with measurement data and have high accuracy.