Carrier Aggregated Traffic Distribution for Network Resource Dimensioning
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Solution Overview
Problem
Current network resource management policies face challenges in balancing cost reduction with quality of service (QoS) considerations, leading to potential degradation in user experience, and inefficient resource allocation, especially when dealing with carrier aggregation and non-aggregation devices under varying network conditions.
Innovation Solution
The solution involves distributing carrier aggregated traffic amongst multiple cells, initializing scheduler weights for each cell based on traffic classes, calculating average throughput for both aggregated and non-aggregated components, and redistributing traffic proportionally to each cell's throughput relative to the total throughput, ensuring fair resource allocation between carrier aggregation and non-aggregation devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network resources are conservatively allocated to ensure high QoS without fine-grain considerations, then quality of service is improved, but resource waste and unnecessary investment increase
Solution Approach 1:
The patent implements fine-grain QoS considerations by differentiating resource allocation at the individual user equipment level. Each UE is assigned specific QoS parameters and resource blocks based on its service requirements, rather than applying uniform conservative allocation across all users. This localized quality approach ensures that only the necessary resources are allocated to each user, preventing both QoS degradation and resource waste.
Solution Approach 2:
The system dynamically adjusts QoS parameters such as priority levels, resource block allocations, and modulation schemes based on real-time network conditions and user requirements. By changing these parameters adaptively rather than maintaining fixed conservative values, the system optimizes the balance between QoS reliability and resource efficiency for each user equipment.
2Productivity
If carrier aggregation is implemented to increase throughput, then data rate is improved, but complexity of resource management increases
Solution Approach 1:
The patent segments carrier aggregation resource management into distinct components: separate resource block allocations for each component carrier, individual QoS parameter sets for each carrier, and dedicated scheduling decisions per carrier. This segmentation allows the system to manage complex CA resources through modular, independent control units rather than attempting to manage all carriers as a single complex entity.
Solution Approach 2:
The system employs dynamic resource allocation where carrier assignments, resource block distributions, and QoS parameters are continuously adjusted based on real-time channel conditions, user mobility, and network load. This dynamic approach enables the system to adapt to changing conditions automatically, reducing the perceived complexity through adaptive behavior rather than static complex management structures.
3Loss of energy
If cost reduction policies are implemented by deemphasizing QoS parameters, then operational cost is reduced, but user quality of experience degrades
Solution Approach 1:
The patent applies local quality by tailoring QoS parameter allocation to individual user equipment and their specific service requirements. Rather than uniformly deemphasizing QoS across all users to reduce costs, the system identifies which users and services require high QoS and allocates resources accordingly. This selective approach maintains QoE for critical services while reducing resource allocation for less demanding users, achieving cost reduction without universal QoS degradation.
Solution Approach 2:
The system implements partial QoS enforcement by applying full QoS guarantees only to specific traffic types or user categories that require them, while using relaxed allocation for other users. This partial action approach ensures that cost reduction policies do not uniformly degrade all user experiences, but rather optimize resource usage by applying appropriate QoS levels selectively based on service requirements.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, calculating a throughput of each cell of a plurality of cells of a communication network, calculating a total throughput of the plurality of cells, and distributing, in accordance with a first distribution, carrier aggregated traffic amongst the plurality of cells, wherein each cell obtains a respective portion of the carrier aggregated traffic as part of the first distribution in accordance with the throughput of the cell and the total throughput. Other embodiments are disclosed.