Carrier Aggregation Control via MIMO Layer Optimization
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Solution Overview
Problem
Base stations face a trade-off in providing carrier-aggregation service to user equipment (UEs) where maximizing carrier aggregation can result in a lower aggregate total number of MIMO layers, while minimizing carrier aggregation can limit peak data rates. The decision on the number of carriers to aggregate is challenging, especially when the UE's reported rank affects its MIMO layer support.
Innovation Solution
A method and system where the base station selects the quantity of carriers for carrier-aggregation service based on the UE's reported rank, configuring the service to maximize the aggregate total number of MIMO layers by adjusting the number of carriers inversely proportional to the rank, ensuring optimal data transmission rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the base station maximizes carrier aggregation by increasing the number of carriers, then peak data rates are improved, but the aggregate total number of MIMO layers decreases
Solution Approach 1:
The base station dynamically adjusts the number of aggregated carriers based on the UE's reported rank indicator. When the UE reports a lower rank (indicating limited MIMO layer support), the base station increases the number of aggregated carriers to compensate and maintain high peak data rates. This dynamic adaptation resolves the contradiction by making the carrier aggregation level flexible rather than fixed, allowing the system to optimize between peak data rate and MIMO layer quantity based on real-time channel conditions and UE capabilities.
Solution Approach 2:
The system changes the parameter of carrier aggregation level in response to changes in the UE's reported rank. By monitoring rank indicator reports from the UE and adjusting the number of aggregated carriers accordingly, the system transforms a static carrier aggregation configuration into a variable one that adapts to channel conditions. This parameter change strategy allows maximizing peak data rate when UE MIMO capability is limited while maintaining optimal MIMO layer utilization when capability is high.
2Quantity of substance
If the base station minimizes carrier aggregation to maintain MIMO layer support, then aggregate total number of MIMO layers is preserved, but peak data rates are limited
Solution Approach 1:
The base station dynamically adjusts the number of aggregated carriers based on the UE's reported rank indicator. When the UE reports a lower rank (indicating limited MIMO layer support), the base station increases the number of aggregated carriers to compensate and maintain high peak data rates. This dynamic adaptation resolves the contradiction by making the carrier aggregation level flexible rather than fixed, allowing the system to optimize between peak data rate and MIMO layer quantity based on real-time channel conditions and UE capabilities.
Solution Approach 2:
The system changes the parameter of carrier aggregation level in response to changes in the UE's reported rank. By monitoring rank indicator reports from the UE and adjusting the number of aggregated carriers accordingly, the system transforms a static carrier aggregation configuration into a variable one that adapts to channel conditions. This parameter change strategy allows maximizing peak data rate when UE MIMO capability is limited while maintaining optimal MIMO layer utilization when capability is high.
3Productivity
If the base station increases carrier aggregation when UE rank is low, then peak data rates are maintained, but the per-carrier MIMO layer support decreases
Solution Approach 1:
The base station dynamically adjusts the number of aggregated carriers based on the UE's reported rank indicator. When the UE reports a lower rank (indicating limited MIMO layer support), the base station increases the number of aggregated carriers to compensate and maintain high peak data rates. This dynamic adaptation resolves the contradiction by making the carrier aggregation level flexible rather than fixed, allowing the system to optimize between peak data rate and MIMO layer quantity based on real-time channel conditions and UE capabilities.
Solution Approach 2:
The system changes the parameter of carrier aggregation level in response to changes in the UE's reported rank. By monitoring rank indicator reports from the UE and adjusting the number of aggregated carriers accordingly, the system transforms a static carrier aggregation configuration into a variable one that adapts to channel conditions. This parameter change strategy allows maximizing peak data rate when UE MIMO capability is limited while maintaining optimal MIMO layer utilization when capability is high.
Data Source
AI summary
A method and system for controlling how many carriers to aggregate together for carrier-aggregation service of a UE. A base station could take into account how many MIMO layers a UE would support respectively for each of various candidate quantities of carriers, and the base station could select the candidate quantity of carriers that would result in use of a highest aggregate total number of MIMO layers. Further, the selection could involve mapping UE-reported rank to a quantity of carriers, with the rank being inversely proportional to the selected quantity of carriers. The base station could then configure carrier-aggregation service of the UE with the selected quantity of carriers.