Dynamic PRB Allocation Scaling for Fairness in Cellular Networks
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Solution Overview
Problem
In cellular wireless networks, the dynamic allocation of air interface resources can lead to unfairness among UEs when one UE has a significantly lower PRB/data ratio compared to others, as the limited resources are not distributed proportionally to the queued data, resulting in potential inefficiencies and unfairness.
Innovation Solution
A base station detects and addresses this imbalance by selecting UEs with higher-order modulation and coding schemes and reducing their PRB allocation, applying a scaling factor to adjust the PRB/data ratio, thereby ensuring more equitable resource distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the base station dynamically allocates PRBs to UEs based on channel conditions and data queue sizes, then the overall network throughput is improved, but unfairness arises among UEs with disproportionate PRB/data ratios
Solution Approach 1:
The base station implements a feedback mechanism by monitoring the PRB/data ratio for each UE and comparing it against a threshold. When unfairness is detected (ratio exceeds threshold), the system adjusts the MCS order for the affected UE in subsequent allocations. This closed-loop feedback ensures that UEs with disproportionately high PRB allocations receive lower-order MCS, thereby reducing their effective throughput and restoring fairness among UEs while maintaining high overall network utilization.
Solution Approach 2:
The system dynamically changes the MCS parameter (modulation and coding scheme order) based on the detected PRB/data ratio. When a UE is identified as having unfair resource allocation, the base station reduces the MCS order for that UE. This parameter change effectively reduces the data rate for the over-allocated UE, balancing the resource distribution across multiple UEs without requiring physical resource redistribution.
2Productivity
If the base station uses higher-order MCS to increase data rate per PRB, then spectral efficiency is improved, but resource allocation fairness deteriorates when combined with dynamic PRB allocation
Solution Approach 1:
The system dynamically adjusts the MCS order on a per-UE basis rather than using a fixed or uniform MCS allocation. The MCS order becomes a dynamic parameter that changes based on real-time assessment of PRB/data ratios. This dynamic approach allows the system to maximize spectral efficiency for UEs with fair allocations while penalizing UEs with disproportionate allocations, thereby resolving the contradiction between spectral efficiency and fairness.
Solution Approach 2:
The base station applies different MCS orders to different UEs based on their individual PRB/data ratios. Instead of using a uniform MCS for all UEs, the system tailors the MCS order locally to each UE's resource allocation situation. This local differentiation allows high-order MCS to be used where appropriate (maintaining spectral efficiency) while applying lower-order MCS to UEs with unfair allocations (restoring fairness).
Data Source
AI summary
A method and system to help control air interface resource allocation. A base station monitors for each served UE a ratio of physical resource block (PRB) allocation to queued data, as a PRB/data ratio. The base station then detects that the PRB/data ratio of a first served UE has been threshold lower than the PRB/data ratio of each of a plurality of second served UEs, and the base station responsively selects at least one of the second UEs based on its modulation and coding scheme (MCS) being relatively high, and the base station limits PRB allocation to the selected UE to help reduce its PRB/data ratio and to thereby help achieve a level of fairness in PRB allocation.