Base Station Data Packet Delay Adjustment
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Solution Overview
Problem
Wireless networks face challenges in optimizing data packet delivery to ensure quality of service, particularly in managing queuing times and outgoing rates to multiple user equipment, which can lead to suboptimal user experience due to inefficiencies in scheduling and resource allocation.
Innovation Solution
A method and system that estimate parameters such as round trip times and queuing times to determine whether to adjust the arrival timing of data packets at the base station, ensuring that the outgoing rate meets minimum requirements and optimizing queuing times to improve service quality, involving a delay evaluator and delayer module to manage packet delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data packets are delayed to arrive at the base station, then the outgoing rate can be optimized and queuing time managed, but the arrival time of data packets is changed which may affect real-time service requirements
Solution Approach 1:
The system estimates the service parameter (outgoing rate) in advance before packet arrival at the base station. Based on this pre estimation, the system determines whether to delay packets proactively, rather than reacting after congestion occurs. This allows the system to prepare for optimal resource allocation before the actual data transmission begins.
Solution Approach 2:
The system continuously monitors the actual outgoing rate and compares it with the estimated value. When the actual rate deviates from the estimate, the system adjusts the delay decision accordingly. This feedback mechanism ensures that the outgoing rate optimization is based on real-time conditions rather than predictions alone.
2Productivity
If the base station services multiple user equipments simultaneously, then network resource utilization increases, but the outgoing rate to each individual user equipment may not meet minimum requirements
Solution Approach 1:
The system estimates service parameters individually for each user equipment rather than treating all users uniformly. By calculating the outgoing rate specific to each UE's conditions (channel quality, data priority, current load), the system can guarantee minimum rates for critical users while still allowing high-rate users to benefit from multiplexing.
Solution Approach 2:
The system applies selective delay only to packets from user equipments where the estimated outgoing rate falls below the minimum requirement. Packets from users with sufficient estimated rates are transmitted without delay. This partial action approach ensures that resource allocation is optimized only where needed, rather than uniformly treating all traffic.
3Productivity
If packet delay decision is made based on estimated service parameters, then resource allocation is optimized, but the estimation accuracy affects the reliability of the optimization
Solution Approach 1:
The system updates the service parameter estimation dynamically based on actual network conditions. Rather than using static predictions, the estimation adapts to changing channel conditions, user activity patterns, and base station load. This dynamic adjustment improves the accuracy of resource allocation decisions over time.
Solution Approach 2:
The system uses the actual outgoing rate data itself to improve the estimation accuracy. By monitoring the real performance and comparing it with predictions, the system automatically refines its estimation model. This self-correction mechanism reduces the impact of initial estimation errors and improves overall allocation reliability.
Data Source
AI summary
Examples of methods, systems, and computer program products relating to supervising data in a wireless network are disclosed. At least part of a system may be located between a packet data network and a base station, and/or may be at least logically separate from the base station. The system may be capable of evaluating the service provided by the base station, and may be capable of determining whether or not any action should consequently be performed. Examples of an action may include an action which may not necessarily affect en-route data packets such as outputting a report, and/or an action which may affect en-route data packets such as delaying packets, not delaying packets, and/or stopping the delaying of packets. An action which affects data packets may or may not affect data packets uniformly. An action may or may not result in an improvement in quality of user experience.