Adaptive DCI RAR Aggregation Level Optimization
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Solution Overview
Problem
Existing communication standards in 4G/LTE and 5G networks face inefficiencies in resource allocation during initial access and handover, as the fixed aggregation level for PDSCH resources leads to either excessive resource usage in good RF conditions or deficient resource allocation in poor RF conditions, resulting in DCI decoding failures.
Innovation Solution
The system dynamically determines the aggregation level for PDSCH resources based on the SINR of the first random access request message from the UE, using multiple predetermined thresholds to adaptively allocate resources, thereby optimizing resource usage and improving DCI decoding success rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed aggregation level is used for msg2 DCI in the network, then the implementation is simple and consistent, but resource efficiency deteriorates in good RF conditions while decoding reliability deteriorates in poor RF conditions
Solution Approach 1:
The patent applies dynamics by transitioning from a static fixed aggregation level to a dynamic adaptive aggregation level selection mechanism. The RAN node dynamically adjusts the aggregation level based on real-time RF conditions measured from the random access request message, allowing the system to adapt to varying channel qualities and optimize both reliability and resource efficiency.
Solution Approach 2:
The patent changes the parameter of aggregation level from a fixed constant to a variable that depends on RF conditions. By measuring parameters such as SINR from the random access request message and comparing against thresholds, the system selects appropriate aggregation levels from a set of predefined options, thereby optimizing DCI transmission reliability for different channel conditions.
2Productivity
If a fixed aggregation level is used for msg2 DCI, then resource allocation is consistent, but resource efficiency worsens when RF conditions are good
Solution Approach 1:
The system changes the aggregation level parameter dynamically based on measured RF conditions. When RF conditions are good, a lower aggregation level is selected, reducing the number of CCEs allocated and improving resource efficiency. When RF conditions are poor, a higher aggregation level is selected to ensure reliable decoding.
Solution Approach 2:
The system uses feedback from the random access request message to determine the appropriate aggregation level. By measuring parameters such as SINR from the received message and comparing against predefined thresholds, the RAN node can make informed decisions about resource allocation, optimizing the balance between reliability and resource efficiency.
3Ease of operation
If a fixed aggregation level is used for msg2 DCI, then implementation is straightforward, but resource allocation becomes deficient in poor RF conditions
Solution Approach 1:
The patent implements dynamics by allowing the aggregation level to adapt to changing RF conditions. The RAN node measures the quality of the random access request message and dynamically selects the appropriate aggregation level, ensuring that DCI transmissions are reliable even in poor RF conditions while maintaining operational simplicity through automated threshold-based selection.
4Reliability
If a higher aggregation level is used to ensure DCI decoding reliability, then decoding success improves, but resource consumption increases
Solution Approach 1:
The patent changes the aggregation level parameter based on measured RF conditions from the random access request message. By comparing parameters such as SINR against predefined thresholds, the system selects the minimum necessary aggregation level to achieve reliable DCI decoding, avoiding unnecessary resource consumption while maintaining high decoding success rates.
Solution Approach 2:
The system uses feedback from the random access request message quality measurements to determine the appropriate aggregation level. This feedback mechanism allows the system to allocate resources efficiently by matching the aggregation level to the actual channel conditions, ensuring reliable decoding only when necessary.
Data Source
AI summary
An apparatus and method for optimizing an aggregation level for communicating physical downlink shared channel (PDSCH) resources in a random access network (RAN) are provided. The apparatus includes a memory storing instructions; and at least one processor configured to execute the instructions to: receive, by a radio access network (RAN) node, a random access request message from a user equipment (UE); determine, by the RAN node, a signal-to-interference-plus-noise ratio (SINR) of the first random access request message; compare the SINR with a first predetermined threshold; based on the comparing, determining an aggregation level from among a plurality of predetermined aggregation levels; and transmit a random access response message from the RAN node to the UE based on the determined aggregation level.