Wireless Data Packet Delay Adjustment for Base Station Service Optimization
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Solution Overview
Problem
Wireless networks face challenges in optimizing data packet delivery to ensure quality of service, particularly in scenarios where base stations serve multiple user equipment, leading to inefficiencies in queuing times and data packet arrival timing.
Innovation Solution
A method and system that estimate service parameters, such as outgoing rates and queuing times, to determine whether to adjust the arrival timing of data packets at the base station, delaying packets if the estimated rate is below a minimum required rate or queuing time is excessive, thereby optimizing service for individual user equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data packets are delayed at the base station to optimize service quality for individual user equipment, then the quality of service improves, but the arrival time of data packets is affected
Solution Approach 1:
The system estimates service parameters (outgoing rate, queuing time) in advance before data packet arrival at the base station. Based on these estimates, timing adjustments are pre-determined and applied to delay packets proactively, ensuring optimal service quality is achieved before congestion occurs rather than reacting after degradation happens.
Solution Approach 2:
The system continuously monitors actual service parameters (outgoing rate, queuing time) and compares them against estimated values and thresholds. This feedback mechanism enables dynamic adjustment of packet timing - when estimated parameters indicate potential congestion or poor service quality, packets are delayed accordingly, and the system adapts based on actual observed performance.
2Productivity
If the base station services multiple user equipment simultaneously, then network capacity is improved, but queuing time increases
Solution Approach 1:
The system performs preliminary estimation of service parameters for multiple user equipment before data packets arrive at the base station. By predicting outgoing rates and queuing times in advance, the system can proactively delay packets for users with poor estimated service conditions, thereby reducing actual queuing time despite serving multiple users simultaneously.
Solution Approach 2:
The system applies different timing strategies to different user equipment based on their individual service conditions. Each user's packets are evaluated independently using their specific outgoing rate and queuing time estimates, allowing selective delay only for users experiencing poor service conditions while maintaining normal delivery for users with good service conditions.
3Reliability
If data packets are delayed based on estimated outgoing rate, then service quality is optimized, but device complexity increases
Solution Approach 1:
The system introduces an intermediary timing adjustment mechanism between the data source and the base station. This intermediary layer estimates service parameters and applies timing adjustments without requiring complex modifications to the base station's scheduling algorithms or the user equipment's data transmission protocols, thereby optimizing service quality with minimal added complexity.
Solution Approach 2:
The system optimizes service quality by dynamically changing timing parameters (packet arrival time) based on estimated service parameters (outgoing rate, queuing time). Rather than modifying complex system architectures, the solution adjusts temporal parameters of data packet transmission, which is a simpler and more straightforward approach to quality optimization.
Data Source
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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.