Dynamic Spectrum Assignment for Variable Network Traffic
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Solution Overview
Problem
Existing wireless communication systems face inefficiencies in network resource utilization, leading to dropped communication operations and service interruptions due to insufficient network resources, which can be exacerbated by increased traffic demands.
Innovation Solution
Implementing machine learning algorithms and artificial intelligence commands to optimize and dynamically assign network resources, including power, memory, and processing resources, across communication sites, allowing for proactive reassignment and utilization of unutilized spectrum based on demand and consumption patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If network resources are allocated statically to communication sites, then resource assignment is simple and predictable, but spectrum utilization efficiency deteriorates when traffic demands vary
Solution Approach 1:
The patent implements dynamic spectrum sharing where network resources are not statically allocated but continuously adjusted based on real-time traffic conditions. The system monitors traffic demands at communication sites and dynamically reassigns spectrum resources to match actual usage patterns, transforming the rigid static allocation into a flexible dynamic system that adapts to varying traffic loads.
Solution Approach 2:
The system changes the allocation parameters of network resources based on observed traffic patterns and consumption requirements. By analyzing traffic data and adjusting spectrum assignment parameters dynamically, the system optimizes spectrum utilization efficiency while maintaining manageable complexity through automated decision-making algorithms.
2Reliability
If more network resources are allocated to meet increased traffic demands, then communication operations reliability is improved, but available network resources are depleted faster
Solution Approach 1:
The system recovers and reallocates spectrum resources that were previously allocated but not fully utilized. By identifying underutilized resources at communication sites and reallocating them to sites with higher traffic demands, the system maintains communication reliability for active users while preserving the overall quantity of available network resources through efficient reuse.
Solution Approach 2:
The patent creates a shared resource pool where spectrum resources serve multiple communication sites universally rather than being dedicated to single sites. This multi-functional allocation allows the same network resources to support different users at different times based on demand, maintaining service reliability while preventing resource depletion.
3Productivity
If network resources are reallocated dynamically based on traffic patterns, then spectrum utilization efficiency is improved, but system complexity and control difficulty increase
Solution Approach 1:
The system implements self-service mechanisms where communication sites automatically report their traffic conditions and resource needs, and the resource allocation system autonomously makes reassignment decisions based on predefined optimization criteria. This automated self-managing approach achieves dynamic spectrum utilization without requiring complex manual control or overly sophisticated centralized decision-making infrastructure.
Solution Approach 2:
The patent incorporates feedback loops where traffic consumption patterns are continuously monitored and fed back into the resource allocation system. This feedback mechanism enables the system to automatically adjust spectrum assignments based on actual usage, achieving high utilization efficiency through a relatively simple closed-loop control structure rather than complex open-loop planning.
4Reliability
If spectrum resources are assigned to prioritize certain users or services, then service quality for prioritized users is improved, but fairness and access for other users deteriorates
Solution Approach 1:
The system implements dynamic priority assignment where user priorities are not fixed but change based on real-time conditions such as traffic type, network load, and service requirements. This dynamic approach allows the system to provide high service quality to prioritized users when needed while maintaining flexibility to adjust priorities and ensure fair access for other users under different conditions, resolving the contradiction between service quality and allocation flexibility.
Data Source
AI summary
An apparatus comprises a memory and a processor communicatively coupled to one another. The processor is configured to monitor first resources assigned in the communication spectrum for one or more communication sites over a first period of time and obtain spectrum resource assignment information for the one or more communication sites. Further, in response to obtaining the spectrum resource assignment information, the processor is configured to execute the machine learning algorithm to analyze the spectrum resource assignment information based at least in part upon multiple communication conditions, generate multiple analysis results in response to analyzing the spectrum resource assignment information, generate one or more spectrum assignment recommendations based at least in part upon the analysis results, and assign second resources in the communication spectrum for the communication sites over a second period of time in accordance with the one or more spectrum assignment recommendations.