LTE Resource Scheduling Using Interference Factor Mapping
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Solution Overview
Problem
Current LTE scheduling methods do not adequately account for user equipment (UE) interference, leading to suboptimal service efficiency and throughput, especially at the cell edge, due to the lack of consideration for interference in priority calculations.
Innovation Solution
A method and apparatus that calculate an interference factor for each UE using an interference factor mapping rule, which is then used to adjust the priority for resource allocation, thereby minimizing interference impact and improving service efficiency and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional scheduling priority calculation is used (based on channel quality, historical throughput, service attribute), then the scheduling complexity is low and the system is simple to operate, but the service efficiency for UEs at cell edge deteriorates due to insufficient consideration of interference
Solution Approach 1:
The priority calculation is segmented into multiple components: traditional priority factors (channel quality, historical throughput, service attribute) and a new interference factor. The interference factor is further segmented by calculating separate interference values from different directions (cell-specific reference signals from neighboring cells) and combining them. This segmentation allows the system to incorporate interference considerations without completely redesigning the scheduling algorithm, thus improving service efficiency while controlling complexity.
Solution Approach 2:
The interference factor is calculated in advance before the final priority determination. The base station pre-calculates interference values from neighboring cells using cell-specific reference signals, stores these interference factors, and then combines them with traditional priority factors when scheduling decisions are made. This preliminary calculation approach allows the system to account for interference without adding significant computational burden during the actual scheduling process.
2Productivity
If interference factor calculation is added to priority calculation, then the service efficiency for UEs at cell edge is improved, but the calculation complexity and processing overhead increase
Solution Approach 1:
The system uses existing cell-specific reference signals that are already transmitted for other purposes (channel estimation, interference measurement) to calculate the interference factor. Instead of introducing new dedicated reference signals or measurements, the solution leverages existing signaling resources to gather interference information, thereby improving throughput without significantly increasing processing overhead or system complexity.
Solution Approach 2:
The cell-specific reference signals serve multiple functions: they are used for traditional channel quality estimation and now also for interference factor calculation. By making these reference signals multi-functional, the system avoids the need for additional dedicated interference measurement resources, thus improving throughput while keeping the calculation complexity and processing overhead manageable.
3Reliability
If interference factor is considered in scheduling, then the user experience is improved, but the scheduling algorithm complexity increases
Solution Approach 1:
The interference factor is dynamically adjusted based on current channel conditions and interference measurements. Rather than using fixed interference compensation values, the system continuously updates interference factors using recent cell-specific reference signal measurements, allowing the scheduling algorithm to adapt to changing conditions. This dynamic approach improves user experience by ensuring accurate interference compensation while managing algorithm complexity through efficient update mechanisms.
Data Source
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AI summary
Disclosed are a method and an apparatus for scheduling resources. The method includes that: an interference factor of each User Equipment (UE) in a scheduling queue of a current subframe is calculated by using an interference factor mapping rule; a priority corresponding to each UE in the scheduling queue of the current subframe is calculated by using the interference factor of each UE; and resources are allocated for each UE according to the priority corresponding to each UE in the scheduling queue of the current subframe.