Wireless Traffic Control via Scheduling Parameter Adjustment
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Solution Overview
Problem
Wireless communication systems face capacity limitations and service disruptions due to excessive traffic volume, leading to potential disconnections and quality deterioration for other users, necessitating effective traffic control mechanisms.
Innovation Solution
The system implements traffic control based on user quality of experience (QoE) by identifying heavy users and adjusting scheduling parameters, such as allocation and retention priority (ARP) values, to manage congestion and optimize resource allocation in wireless communication systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traffic control is implemented to manage congestion, then service stability and user QoE are improved, but system complexity increases due to additional control mechanisms
Solution Approach 1:
The system performs preliminary identification of heavy users based on traffic usage patterns before congestion occurs. By pre-categorizing users and preparing scheduling parameter adjustments in advance, the system can respond to congestion more efficiently without implementing complex real-time control mechanisms, thus improving service stability while limiting complexity increase
Solution Approach 2:
The system implements feedback mechanisms where the base station monitors congestion situations and throughput ratios, then adjusts scheduling parameters of heavy users accordingly. This closed-loop control allows the system to maintain service stability through dynamic adaptation rather than complex static control structures, resolving the contradiction between reliability improvement and complexity increase
2Reliability
If scheduling parameters of heavy users are adjusted to reduce their traffic, then congestion is alleviated and other users' QoE is improved, but the heavy users' service quality deteriorates
Solution Approach 1:
The system applies partial action by adjusting scheduling parameters only for identified heavy users rather than all users. By selectively controlling only those users whose traffic usage exceeds thresholds, the system alleviates congestion and protects other users' service quality while minimizing the impact on controlled users, thus balancing overall service quality with individual user experience
Solution Approach 2:
The system changes scheduling parameters (such as priority levels, resource allocation ratios) dynamically based on congestion detection. Instead of complete traffic blocking, the system adjusts parameters to achieve moderate traffic reduction, which alleviates congestion while maintaining acceptable service quality for controlled users, resolving the contradiction between overall service quality improvement and individual user quality deterioration
3Productivity
If real-time traffic monitoring and control is implemented, then congestion management is improved, but processing overhead and system resource consumption increase
Solution Approach 1:
The system segments users into different categories (heavy users, normal users) based on traffic usage patterns. By dividing the user population and applying different control strategies to different segments, the system improves congestion management efficiency for critical users while avoiding unnecessary processing for other users, thus reducing overall processing overhead and energy consumption
Solution Approach 2:
The system performs partial monitoring and control by focusing only on heavy users whose traffic exceeds predetermined thresholds. Instead of monitoring and controlling all users in real-time, the system applies control actions selectively to identified heavy users, which improves congestion management efficiency while significantly reducing processing overhead and system resource consumption
Data Source
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AI summary
A method for operating an apparatus that performs traffic control traffic in a wireless communication system is provided. The method includes receiving information about a terminal to be controlled, detecting a congestion situation in a cell, and changing a parameter relating to scheduling of the terminal to be controlled, according to the detection of the congestion situation.