Dynamic QoS Channel Allocation for Wireless Networks
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Solution Overview
Problem
Conventional wireless networks allocate communication channels based on predefined quality-of-service (QoS) classes and subscription levels, failing to dynamically adjust to the varying usage characteristics and mobility of user equipment, which can lead to inefficient bandwidth utilization and suboptimal service quality, especially in IoT and machine-type communications.
Innovation Solution
Implementing an intelligent QoS channel engine within Evolved Node B (eNB) that monitors usage and mobility characteristics of user equipment, dynamically assigning new communication channels with optimized bandwidth based on usage patterns, leveraging autonomic Subscriber Identity Modules (A-SIMs) to facilitate QoS-based channel adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If communication channels are allocated based on predefined QoS classes and subscription levels, then service quality is maintained for standard users, but bandwidth utilization becomes inefficient and service quality deteriorates for users with varying usage characteristics
Solution Approach 1:
The system dynamically adjusts communication channel allocation based on real-time monitoring of usage characteristics including data traffic volume, timing patterns, and mobility metrics. The eNB processor continuously evaluates these characteristics and reassigns QoS channels accordingly, transitioning from static predefined allocation to dynamic adaptive allocation that responds to actual user equipment behavior patterns
Solution Approach 2:
The system implements a feedback mechanism where the eNB processor monitors usage characteristics of user equipment and uses this information to make informed decisions about channel reassignment. The monitoring data flows back to the allocation algorithm, creating a closed-loop system that continuously optimizes channel assignment based on observed performance and usage patterns
2Reliability
If static channel allocation is used based on subscription levels, then network complexity is reduced, but service quality deteriorates for mobile users with varying mobility patterns
Solution Approach 1:
The system enables user equipment to effectively self-configure their service quality parameters through the monitoring and reporting of their own usage characteristics. The eNB processor uses this self-reported data to automatically adjust channel allocation without requiring manual intervention or complex user configuration, allowing the network to self-optimize based on observed behavior
Solution Approach 2:
The system changes the QoS channel parameters dynamically based on monitored usage characteristics such as data traffic volume, timing patterns, and mobility metrics. By adjusting these parameters in response to observed conditions rather than maintaining fixed assignments, the system improves service quality consistency for users with varying patterns while keeping the underlying allocation mechanism manageable
3Ease of operation
If predefined QoS classes are used for channel assignment, then ease of operation is improved, but adaptability to varying usage patterns deteriorates
Solution Approach 1:
The system performs preliminary monitoring of usage characteristics before making channel assignment decisions. By continuously collecting data on data traffic volume, timing patterns, and mobility metrics in advance, the system prepares the information needed for optimal channel selection, enabling simple automated decisions based on pre-gathered usage evidence rather than complex real-time analysis
Data Source
AI summary
Methods, computer program products, and systems are presented. The methods include, for instance: attaching a user equipment to a communication network via Evolved Nodes B respectively controlling radio cells of the communication network. A new communication channel for the user equipment is assigned based on usage characteristics of the user equipment.