Radio-Aware Image Analytics for 5G Neighbour Identification

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing Automatic Neighbour Relations (ANR) methods in 5G communication systems are inadequate for identifying neighbours of moving cells, such as drone base transceiver stations, as they rely solely on 2D geographical parameters and do not consider radio parameters or visual inputs, leading to inconsistent results and incorrect neighbour identification.

Innovation Solution

A radio-aware image analytics method is proposed for ANR optimization, using image analytics on 2D and 3D images representing antenna beam patterns to determine overlapping transmission areas, generated by applying Gaussian functions or masks based on beam and antenna parameters, to accurately identify neighbouring cells.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If 2D geographical parameters are used for neighbour identification, then the method is simple to implement, but the accuracy of neighbour identification deteriorates for moving cells

Engineering Contradiction:

Improveease of implementationVSAvoidneighbour identification accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent transitions from 2D geographical parameters to 3D spatial representation by incorporating altitude/height information. This is achieved by generating image data where pixel coordinates represent geographical position and additional dimensions represent transmission range and beam patterns, enabling accurate neighbour identification for moving cells including drones.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent introduces image data as an intermediary representation between raw transmitter parameters and neighbour identification results. The image data visually encodes transmission ranges, beam patterns, and geographical positions, allowing the system to accurately determine overlapping coverage areas and identify neighbours without complex mathematical computations.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Device complexity

If radio parameters are not considered in ANR methods, then the system complexity is reduced, but the reliability of neighbour identification deteriorates

Engineering Contradiction:

Improvesystem complexityVSAvoidneighbour identification reliability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent merges multiple parameters (geographical location, beam direction, beam width, transmission power) into a unified image data representation. Each transmitter's characteristics are encoded in the image data through visual patterns, allowing the system to consider radio parameters without increasing computational complexity, as the image processing inherently handles these multi-dimensional attributes.

Inventive Principle:

Principle #5Merging (Combining)

3Difficulty of detecting and measuring

If visual inputs are not used for ANR, then the measurement process is simpler, but the precision of transmission range determination deteriorates

Engineering Contradiction:

Improvemeasurement complexityVSAvoidtransmission range determination precision

Core Design Contradiction:

Difficulty of detecting and measuringVSMeasurement precision

Solution Approach 1:

The patent creates visual copies (image data) of the physical transmission environment. Instead of directly measuring complex radio propagation characteristics, the system generates image representations that copy the spatial and directional properties of transmitter coverage, making measurement simpler while maintaining precision through visual pattern analysis.

Inventive Principle:

Principle #26Copying

4Productivity

If 2D geographical parameters are used, then data processing is faster, but the adaptability to moving nodes deteriorates

Engineering Contradiction:

Improvedata processing speedVSAvoidadaptability to moving nodes

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent adds the height/altitude dimension to the traditional 2D geographical representation, creating a 3D spatial model. This allows the system to track and identify neighbours of moving nodes (such as drones) at different altitudes, significantly improving adaptability while maintaining processing efficiency through image-based representation.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enables accurate and periodic optimization of Neighbour Cell Relations (NCRs) across various antenna patterns and beam directions, including those of moving nodes, improving load balancing and mobility robustness by considering multi-dimensional radio environments.

Implementation Method 1

generate the image data by, for each of the plurality of transmitters, applying a respective Gaussian function to image data representing the location of said each of the plurality of transmitters

Methodology Applied

Scientific EffectGaussian function:

Data Source

PatentUS12149961B2Apparatus, methods, and computer programs for automatic neighbor relations

Publication Date: 2024.11.19 NOKIA TECHNOLOGIES OY

AI summary

There is provided an apparatus configured to: receive, from a management service, location data associated with each of a plurality of transmitters; receive beam and/or antenna parameters associated with beams provided by the plurality of transmitters; use the received location data and received parameters to generate image data representing transmission ranges of the plurality of transmitters; and provide the generated image data to the management service.