Proactive SR Grant Scheduling for Faster RRC Setup
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Solution Overview
Problem
Existing radio resource control (RRC) setups in communication systems experience significant delays due to inefficient allocation of resources and HARQ acknowledgement processes, leading to performance degradation and resource wastage.
Innovation Solution
Implementing a proactive grant mechanism that schedules uplink modulation and coding scheme (MCS) and resource blocks (RBs) based on learned uplink channel signal interference and noise ratio (SINR) characteristics, reducing RRC connection setup time by proactively allocating resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the DU waits for SR opportunity to allocate resources to UE, then resource allocation follows standard procedure, but RRC setup time increases significantly
Solution Approach 1:
The base station proactively allocates uplink resources and sends scheduling request grants to the UE before the UE actually needs to transmit RRC setup complete messages. This preliminary resource allocation eliminates the waiting time for SR opportunities and reduces RRC setup time significantly.
2Reliability
If multiple RLC level retransmissions occur to transmit complete upper layer packet, then message delivery reliability is maintained, but transmission time and resource consumption increase
Solution Approach 1:
The base station performs preliminary channel quality assessment and proactively allocates sufficient uplink resources with appropriate MCS before the UE needs to transmit. This ensures that the UE can transmit the complete RRC setup complete message in one attempt without requiring RLC retransmissions, thus maintaining reliability while reducing transmission time.
Solution Approach 2:
The system uses HARQ feedback mechanisms to confirm successful reception of RRC messages. The base station monitors HARQ acknowledgments and can trigger proactive resource allocation when it detects that the UE has successfully received downlink RRC messages, ensuring reliable delivery while minimizing retransmissions.
3Loss of time
If proactive grant is scheduled based on learned UL channel SINR characteristics, then RRC connection setup time is reduced, but scheduling complexity increases
Solution Approach 1:
The base station utilizes feedback from uplink channel measurements and HARQ acknowledgments to learn UL channel SINR characteristics. This learned information is then used to make intelligent proactive resource allocation decisions, reducing RRC setup time while keeping the scheduling complexity manageable through data-driven decisions.
Solution Approach 2:
The system dynamically adjusts scheduling parameters such as MCS and resource block allocation based on learned channel conditions. By changing these parameters proactively based on historical SINR data, the system reduces setup time without requiring complex real-time scheduling calculations.
4Reliability
If standard SR-based resource allocation is used, then resource allocation follows established protocol, but network performance degrades due to delays
Solution Approach 1:
The base station implements proactive resource allocation by sending scheduling request grants before the UE needs to transmit RRC setup complete messages. This preliminary action maintains protocol compliance while significantly improving network performance by reducing connection setup time and eliminating unnecessary delays.
Data Source
AI summary
The present disclosure provides a system and a method for managing radio resource control (RRC) setup time with a scheduling request grant. The system allocates the required resources for message transmission from a user equipment (UE) (302) and sends a grant proactively, without waiting for a scheduling request (SR) from the UE (302) and allocates resources. The proactive grant with the SR reduces the delay associated with the RRC connection setup time. Further, the system allocates resource blocks (RBs) based on a learned uplink (UL) channel signal interference and noise ratio (SINR) characteristics.