Adaptive Whitening Transform for Interference Mitigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In wireless communication systems, especially in 5G NR, the whitening transform estimated from pilots may be incorrect when slot-based scheduling is not used by serving and neighboring base stations, leading to inadequate interference mitigation and reduced signal decoding performance due to differing interference affecting pilots and data.
Innovation Solution
A user equipment (UE) applies a modified whitening transform based on determining whether the interference affecting the pilot is the same as or different from the interference affecting the data, using a threshold power comparison to decide between the original or modified whitening transform to accurately account for interference differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If slot-based scheduling is not used by serving and neighboring base stations, then scheduling flexibility is improved, but interference mitigation accuracy deteriorates because the whitening transform estimated from pilots becomes incorrect
Solution Approach 1:
The system dynamically adapts the whitening transform based on scheduling configuration detection. When non-slot-based scheduling is detected, the system switches from using pilot-based whitening transform to using data-based interference estimation, making the interference mitigation process adaptive to different scheduling modes rather than static
Solution Approach 2:
The system changes the parameter used for interference mitigation based on scheduling mode. In slot-based scheduling, the whitening transform matrix is used; in non-slot-based scheduling, the system switches to using interference covariance matrix estimated directly from data symbols, changing the fundamental parameter approach for interference cancellation
2Productivity
If whitening transform is estimated from pilots and applied to data, then processing efficiency is improved, but decoding performance deteriorates when pilot and data have different interference characteristics
Solution Approach 1:
The system dynamically selects between two processing approaches: using pilot-based whitening transform when slot-based scheduling is detected (maintaining efficiency), or switching to data-based interference estimation when non-slot-based scheduling is detected (maintaining reliability). This dynamic selection resolves the contradiction between efficiency and reliability
Solution Approach 2:
The system uses feedback from detecting the scheduling configuration to determine the appropriate interference mitigation approach. By monitoring whether slot-based or non-slot-based scheduling is in use, the system adjusts its processing method accordingly, ensuring both efficiency and reliability are maintained under different operating conditions
Data Source
AI summary
Aspects are provided which allow a UE to apply a modified interference cleaning data to account for differences in interference between at least one pilot resource and at least one data resource, thereby improving data decoding performance of the UE. The UE receives at least one pilot resource and at least one data resources from a base station and identifies interference cleaning data based on the pilot resource. The UE then determines whether a first interference affecting the pilot resource is the same as a second interference affecting the data resource. When the first interference is the same as the second interference, the UE applies the interference cleaning data to the data resource. Otherwise, when the first interference is different than the second interference, the apparatus applies a modified interference cleaning data to the data resource.