MU-MIMO User Pairing via Channel Correlation Tables
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Solution Overview
Problem
Existing MU-MIMO user pairing methods suffer from interference errors, low pairing capacity, and high complexity, particularly exacerbated by the introduction of Massive MIMO technology, which leads to inefficient resource allocation and increased bit error rates.
Innovation Solution
A method and device for processing user pairing that generates a channel matrix from reported signals, creates a space division information table to assess correlations between UEs, and determines paired users based on correlation thresholds and priorities, optimizing pairing to reduce interference and enhance capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If PMI-based interference calculation is used for MU-MIMO user pairing, then the pairing process can be implemented, but quantization errors occur between precoding matrix and actual channel matrix leading to interference calculation errors
Solution Approach 1:
The patent introduces an intermediate channel quality indicator (CQI) as a mediator between the channel matrix and interference calculation. Instead of directly using PMI-based precoding matrices which suffer from quantization errors, the method uses CQI values that more accurately reflect actual channel conditions to guide user pairing decisions, thereby reducing interference calculation errors while maintaining implementation feasibility
Solution Approach 2:
The patent replaces the traditional PMI-based mechanical precoding matrix selection mechanism with a CQI-based channel quality assessment mechanism. This substitution eliminates the quantization error inherent in discrete PMI codebooks by using continuous channel quality measurements to evaluate and pair users, improving measurement precision without sacrificing ease of operation
2Ease of operation
If singular value decomposition is performed on channel matrices of all users to calculate null space, then user pairing can be achieved, but calculated amount becomes large and complexity increases when there are more space division users
Solution Approach 1:
The patent extracts only the essential channel quality information (CQI values) from the full channel matrices, discarding the redundant dimensional data that would require complex singular value decomposition. By taking out only the critical pairing-related metrics, the method maintains user pairing capability while dramatically reducing calculation complexity, especially when dealing with large numbers of space division users
Solution Approach 2:
Instead of performing complete singular value decomposition on all channel matrices (excessive action), the patent applies partial action by only calculating and comparing CQI values for user pairing decisions. This partial computation approach achieves sufficient pairing accuracy without the full mathematical complexity, balancing ease of operation with reduced device complexity
3Ease of operation
If first paired users are selected by using singular value decomposition method, then pairing can be performed, but interference between users is only considered without consideration of Channel Quality Indicators (CQIs) of other paired users resulting in poor capacity
Solution Approach 1:
The patent implements feedback by continuously considering CQI values of all users throughout the pairing process, not just the first paired users. Each user's CQI is evaluated in the context of potential pairings, and this feedback information guides the selection to maximize overall system capacity. This iterative feedback mechanism ensures that capacity is optimized across all paired users rather than just the initial selections
Solution Approach 2:
The patent makes the CQI-based pairing criterion universal by applying the same channel quality assessment to all users regardless of pairing order. This universal approach allows the system to evaluate and optimize pairings based on overall channel conditions and user requirements, improving system capacity by considering the multi-functional impact of each pairing decision on the entire network rather than just individual user pairs
Data Source
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AI summary
The embodiments of disclosure disclose a method and device for processing user pairing, and a base station. The method includes that: a signal reported by a User Equipment (UE) for generating a channel matrix H is received; the channel matrix H of the UE is generated according to the received signal; a space division information table for identifying correlation between UEs is generated according to the generated channel matrix H; and paired users are determined according to the generated space division information table. The disclosure solves problems of interference error, low pairing capacity and high complexity when the user pairing is performed by using Multiple User-Multiple Input Multiple Output (MU-MIMO) in the related art, thereby simplifying the user pairing and improving MU-MIMO system capacity.