Dynamic Frequency Allocation for Wireless Networks

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Wireless networks face challenges in efficiently managing frequency resources due to increasing user demand and interference, particularly in the CBRS band, where existing static allocation methods fail to optimize capacity and prevent interference with incumbent users.

Innovation Solution

A network device implements a self-organizing network (SON) with machine learning algorithms to dynamically allocate frequency resources to base stations based on demand and availability, utilizing licensed, unlicensed, and CBRS bands, ensuring optimal resource utilization and minimizing interference with incumbent users.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If static frequency allocation is used, then network simplicity is maintained, but network capacity and efficiency deteriorate under increasing user demand

Engineering Contradiction:

Improvenetwork capacityVSAvoidfrequency management complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements dynamic frequency allocation where base stations automatically adjust their frequency resources based on real-time network conditions, user demand, and interference levels. This transforms the static frequency assignment into a dynamic system that adapts to changing conditions, thereby increasing network capacity without proportionally increasing management complexity

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent employs self-organizing network (SON) functionality that enables base stations to autonomously perform frequency allocation and interference management without requiring manual intervention. The system self-adjusts frequency resources based on detected network conditions, reducing the operational complexity while enhancing network capacity and efficiency

Inventive Principle:

Principle #25Self-service

2Productivity

If more frequency resources are allocated to handle increasing user demand, then network capacity improves, but interference with incumbent users increases

Engineering Contradiction:

Improvenetwork capacityVSAvoidinterference with incumbent users

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent implements a feedback mechanism where base stations continuously monitor network conditions, including interference levels with incumbent users, and adjust frequency allocations accordingly. This feedback loop enables the system to increase network capacity while maintaining interference protection for incumbent users by dynamically adapting resource allocation based on real-time conditions

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent applies different frequency allocation strategies to different base stations and geographic locations based on local conditions. Base stations operating in areas with incumbent users employ more conservative frequency selection, while those in areas with less interference can utilize additional frequency resources, thereby maximizing overall network capacity while protecting incumbent users locally

Inventive Principle:

Principle #3Local quality

3Ease of operation

If manual frequency management is used, then control precision is maintained, but processing requirements and operational overhead increase

Engineering Contradiction:

Improvefrequency allocation automationVSAvoidprocessing requirements

Core Design Contradiction:

Ease of operationVSPower

Solution Approach 1:

The patent implements self-organizing network functionality that enables base stations to autonomously perform frequency allocation decisions based on pre-configured rules and real-time measurements. This automation eliminates manual frequency management operations while the distributed decision-making architecture keeps processing requirements manageable by performing computations locally at each base station rather than requiring centralized processing

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS10805862B2Sensor and self-learning based dynamic frequency assignment for wireless networks

Publication Date: 2020.10.13 T MOBILE US INC

AI summary

Techniques for dynamically assigning frequency resources in a wireless network are discussed herein. For example, a network device can implement a self-organizing network to allocate frequency resources to a base station based on an availability of such frequency resources, as well as data indicating one or more conditions at a base station. The network device can receive information associated with the base station, such as load information, coverage information, capability information, interference information, and the like. In some examples, the network device can use a machine learning algorithm to select frequency resources from licensed bands, a Citizens Broadband Radio Service band, or unlicensed bands. Frequency resource allocation information can be used to configure the base station to facilitate wireless communications using such frequency resources. As the conditions at a base station change over time (e.g., hourly, daily, weekly, etc.), frequency resources can be allocated and deallocated at the base station.