MIMO Rank Self-Adaptation for High-Speed User Equipment
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Solution Overview
Problem
The existing rank self-adaptation methods in MIMO systems are inadequate for quickly changing channel ranks, particularly in high-speed user equipment scenarios, leading to reduced spatial advantages and throughput performance.
Innovation Solution
A method and apparatus for rank self-adaptation that involves a base station receiving ranks from user equipment through a rank receiving window, determining the current rank based on specific distribution states, and adjusting the number of independent channels for downstream data transmission accordingly, using thresholds and user equipment position measurements to handle varying channel conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the network side controls the number of independent channels based on the newly reported rank at the UE side, then the implementation is simple and effective for slowly changing ranks, but when ranks change quickly (e.g., high-speed UE), the difference between the newly reported rank and the current actual MIMO channel rank may be greater, causing spatial advantages to be greatly discounted
Solution Approach 1:
The base station predicts the current rank based on historical rank information and channel state before the UE reports the new rank. This preliminary action allows the system to prepare the appropriate number of independent channels in advance, reducing the lag when ranks change quickly due to high-speed movement.
Solution Approach 2:
The system uses the newly reported rank from the UE as feedback to update and refine the predicted rank for future predictions. This feedback mechanism allows the base station to continuously improve its rank prediction accuracy while maintaining simple processing, resolving the contradiction between simplicity and accuracy for high-speed scenarios.
2Reliability
If the UE feeds back ranks frequently to track rapid channel changes, then the accuracy of rank adaptation improves for high-speed UE, but the signaling overhead and processing complexity increase
Solution Approach 1:
Instead of using every newly reported rank immediately, the system selectively uses only those ranks that are deemed reliable based on prediction consistency. This partial action approach avoids processing all feedback information, reducing complexity while maintaining accurate tracking for rapid channel changes.
Solution Approach 2:
The predicted rank acts as an intermediary between the newly reported rank and the actual rank control decision. This intermediary filters and validates the feedback information, reducing the processing burden while ensuring accurate rank tracking even when channels change rapidly.
3Reliability
If the system uses the smallest rank in the rank receiving window, then it ensures conservative resource allocation, but it fails to utilize the spatial advantages of MIMO when channels are favorable
Solution Approach 1:
The system dynamically changes the rank selection criterion based on channel conditions. When channels are stable, it uses the smallest rank for conservatism; when channels are favorable and stable, it uses the predicted rank which can be higher, thus maximizing throughput while maintaining reliability through adaptive parameter selection.
Solution Approach 2:
The rank selection transitions from a static approach (always using the smallest rank) to a dynamic approach where the selected rank adapts to current channel conditions and prediction confidence. This allows the system to exploit favorable MIMO spatial advantages when conditions permit while maintaining stability when uncertain.
Data Source
AI summary
The present invention discloses a method and apparatus for rank self-adaptation. The method comprises: a base station receiving ranks reported by a user equipment via a rank receiving window, determining a rank at the current moment based on a distribution state of each rank in the rank receiving window at the current moment, and determining the number of independent channels used for sending downstream data to the user equipment based on the rank at the current moment. The present invention can reasonably forecast change of ranks of MIMO channels so as to better use MIMO channel resources to perform data transmission and improve the throughput rate of the MIMO channels.