MU-MIMO User Selection via Channel Correlation Matrices
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Solution Overview
Problem
Existing user selection techniques in MU-MIMO WLAN systems face challenges in accurately estimating SINR due to inter-user interference, leading to inaccurate MCS selection and reduced system throughput.
Innovation Solution
The proposed solution involves calculating inter-user interference per subcarrier using V-matrices from CSI feedback and applying the RBIR-ESM technique to estimate effective SNR values, enabling accurate user selection and MCS prediction through the Received Bit Information Rate (RBIR) method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If exhaustive searching algorithm is used to select user groups maximizing system capacity, then system throughput is optimized, but computational complexity increases non-linearly with the number of users
Solution Approach 1:
The patent segments the user selection process into two stages: first calculating channel correlation matrices for all user pairs, then using these pre-computed correlations to guide group selection. This segmentation reduces the computational burden of exhaustive searching by breaking down the complex optimization problem into manageable steps, maintaining system throughput while reducing processing requirements.
Solution Approach 2:
The patent performs preliminary calculations of channel correlation matrices and effective SINR values for all potential user combinations before final group selection. By pre-computing these correlation metrics, the system avoids repeated complex calculations during the user selection process, thereby reducing real-time computational complexity while preserving optimization accuracy.
2Ease of manufacture
If PER-based rate adaptation technique is used for MCS selection, then implementation is simple, but accuracy in reflecting inter-user interference is poor leading to packet errors
Solution Approach 1:
The patent introduces channel correlation matrices as an intermediary mechanism that captures inter-user interference effects. Instead of directly using simple PER statistics, the system uses these correlation matrices to compute effective SINR values that accurately reflect multi-user interference conditions, thereby improving measurement precision while maintaining practical implementability.
Solution Approach 2:
The patent replaces the mechanical PER-based rate adaptation approach with a more sophisticated effective SINR calculation method that incorporates channel correlation information. This substitution enables accurate interference estimation without requiring complex real-time measurements, achieving both precision and practicality.
3Measurement precision
If channel correlation calculation is performed for all user combinations, then user grouping accuracy is improved, but computational volume increases
Solution Approach 1:
The patent merges the calculation of channel correlation matrices with the user grouping process itself. By computing correlations for all user pairs and storing them in matrices that can be directly used for grouping decisions, the system eliminates redundant calculations and integrates multiple operations into a unified process, reducing overall computational volume while maintaining grouping accuracy.
Data Source
AI summary
A wireless communication device for facilitating wireless communication is provided. The device transmits a training frame, and receives a plurality of feedback frames including channel quality information from a plurality of stations in response to the training frame. The device determines a plurality of groups based on the channel quality information in the plurality of feedback frames. Each of the plurality of groups is associated with a respective one of the plurality of stations and includes an associated station as a primary station and at least one secondary station. The device determines channel capacities of the plurality of groups and selects a group of the plurality of groups based on the channel capacities of the plurality of groups. The device determines users of the selected group as MU-MIMO users and transmits a MU PPDU in MU-MIMO for the users of the selected group.