Grouping User Equipment by Precoding Matrix Indicators for Combined Transmission
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Solution Overview
Problem
Current Multiuser Superposition Transmission (MUST) operations in wireless communication systems do not effectively utilize the preferred spatial layers of user equipment (UEs) for combined transmissions, limiting system capacity and efficiency.
Innovation Solution
A base station groups UEs based on similar precoding matrix indicators (PMIs) to determine preferred spatial layers for each UE group and schedules combined transmissions accordingly, enabling the use of preferred spatial layers for each UE in the transmission scheme.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current MUST operation is used, then system capacity can be improved through joint optimization, but the preferred spatial layers of each UE cannot be utilized
Solution Approach 1:
The invention segments UEs into different UE groups based on their PMI characteristics. Each UE group is associated with a specific PMI set, allowing the system to handle different spatial layer preferences separately. This segmentation enables the base station to optimize transmissions for each group's preferred spatial layers while maintaining overall system capacity improvements from MUST operation.
Solution Approach 2:
The invention applies local quality by assigning different transmission schemes to different UE groups based on their specific PMI characteristics. Each UE group receives transmissions optimized for its preferred spatial layers, rather than using a uniform transmission scheme for all UEs. This localized optimization allows the system to utilize the preferred spatial layers of each UE while maintaining joint optimization benefits.
2Adaptability or versatility
If UEs are grouped based on similar PMIs, then preferred spatial layers can be utilized for each UE, but transmission scheme complexity increases
Solution Approach 1:
The invention applies preliminary action by pre-defining multiple PMI sets and establishing association relationships between UE groups and these PMI sets before actual transmissions occur. The base station determines which PMI set each UE group should use in advance, based on PMI similarity. This preliminary organization simplifies the real-time transmission scheme determination, as the base station only needs to select from pre-established associations rather than computing optimal schemes from scratch for each transmission.
Solution Approach 2:
The invention manages complexity by changing the parameter organization structure - instead of handling individual UE PMIs separately, it groups PMIs into sets with similar characteristics and assigns these sets to UE groups. This parameter aggregation and categorization reduces the computational burden of determining transmission schemes, as the system works with grouped parameters rather than individual UE-specific parameters for each transmission decision.
Data Source
AI summary
The present disclosure enables a base station to group UEs based on similar PMIs for a combined transmission. The apparatus may receive a plurality of PMIs from a plurality of UEs. In one aspect, each PMI in the plurality of PMIs may be received from a different UE. The apparatus may also assign each UE of the plurality of UEs to a UE group. In another aspect, each UE group may be associated with a different PMI set in a plurality of PMI sets. The apparatus may further assign a transmission scheme to each UE group. In one configuration, the apparatus may determine one or more preferred spatial layers for each UE (e.g., based on the PMIs) assigned to a UE group, and schedule a combined transmission for the UE group based on the determined one or more spatial layers.