Scheduling Request Prioritization in LTE eNBs
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Solution Overview
Problem
Conventional wireless communication systems, particularly in 3GPP LTE standards, lack the ability to prioritize scheduling requests (SRs) based on the importance of uplink data, leading to undesirably large latencies for time-sensitive data transmissions.
Innovation Solution
Implementing a method where an evolved NodeB (eNB) receives multiple SRs from user equipments (UEs), prioritizes them using multiple scoring criteria such as QoS, user role, incident type, and channel quality indicators, and transmits SR grants to UEs with high-priority SRs, ensuring timely communication of critical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional eNBs grant SRs to multiple UEs without prioritization, then all UEs can potentially transmit data, but time-sensitive and important uplink data experiences undesirably large latencies
Solution Approach 1:
The patent introduces a priority parameter for each SR that changes the granting behavior. The eNB evaluates multiple parameters including QoS class identifier, delay budget, and packet loss probability to assign priority levels. This parameter-based differentiation resolves the contradiction by enabling time-sensitive data to be prioritized without fundamentally changing the SR granting mechanism structure.
Solution Approach 2:
The patent applies different granting strategies to different UEs or different SRs based on their specific characteristics. Instead of a uniform granting approach, the eNB applies local quality differentiation by assigning different priority levels to different SRs based on their associated data characteristics, allowing time-sensitive data to receive preferential treatment while maintaining standard operation for other data.
2Productivity
If eNB prioritizes SRs based on multiple scoring criteria, then time-sensitive data transmission is improved, but the complexity of SR evaluation increases
Solution Approach 1:
The patent segments the SR evaluation process into distinct criteria: QoS class identifier evaluation, delay budget evaluation, and packet loss probability evaluation. Each criterion can be independently calculated and combined, allowing the system to achieve comprehensive evaluation while maintaining manageable complexity through modular processing of individual criteria.
Solution Approach 2:
The eNB uses feedback from QoS parameters, delay budgets, and packet loss probabilities to dynamically adjust SR granting decisions. This feedback mechanism enables the system to automatically prioritize time-sensitive data without requiring complex manual configuration, as the evaluation criteria provide continuous feedback about data urgency and requirements.
3Loss of time
If eNB uses QoS and delay budget criteria for SR prioritization, then time-sensitive data latency is reduced, but the computational overhead increases
Solution Approach 1:
The QoS parameters, including delay budgets and packet loss probabilities, are predetermined and configured before SR granting is needed. This preliminary action allows the eNB to use pre-calculated values in the prioritization process, reducing the computational overhead during actual SR granting decisions while still achieving reduced latency for time-sensitive data.
Data Source
AI summary
Embodiments include methods and apparatus for granting scheduling requests in a wireless communications system that includes an eNB, a plurality of UEs, and a public safety system. The eNB receives multiple scheduling requests from multiple UEs, where each of the scheduling requests indicates that a corresponding UE is requesting uplink data transmission resources. The eNB determines a priority value for each of the scheduling requests based on multiple scoring criteria, resulting in a plurality of priority values associated with the scheduling requests. The eNB transmits one or more scheduling request grants to a subset of the UEs, where the subset includes one or more UEs that are associated with one or more scheduling requests having relatively high priority values. In an embodiment, the multiple scoring criteria include information associated with a public safety activity (e.g., a user role, a jurisdictional coverage area, an incident type, and/or an application type).