RF Map Generation via Back Projection for Network Optimization
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Solution Overview
Problem
Traditional network optimization methods, such as drive testing, are limited in their ability to improve network performance across the entire network, rather than just addressing specific problem areas, and require frequent and costly data collection.
Innovation Solution
Generating radio frequency (RF) maps using existing test data and back projection techniques, allowing for the adjustment of network parameters like handoff and reselection parameters, antenna tilts, and power offsets to enhance network performance without the need for extensive new drive tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional drive testing methods are used to collect RF data, then network parameter optimization can be achieved, but the cost and time requirements increase significantly
Solution Approach 1:
The patent performs back projection calculations using existing historical drive test data before new drive tests are conducted. By pre-processing available data to create initial RF maps and attenuation functions, the system prepares optimization parameters in advance, reducing the need for extensive new data collection and accelerating the network optimization process.
Solution Approach 2:
The patent creates RF maps for a first network by copying and adapting test data from a second network. The back projection technique replicates attenuation characteristics from one network environment to another, allowing the system to generate useful optimization data without physically testing the target network, thereby significantly reducing time and resource requirements.
2Reliability
If traditional drive testing methods are used to collect RF data, then network parameter optimization can be achieved, but the cost increases significantly
Solution Approach 1:
The patent reuses existing drive test data from one network to generate RF maps for another network. By copying and adapting historical test data through back projection calculations, the system eliminates the need for expensive new drive tests while still achieving accurate network parameter optimization, directly reducing energy and resource costs.
Solution Approach 2:
The system uses its own existing data repositories and computational algorithms to generate RF maps without requiring external data collection resources. By self-serving through internal data processing and back projection techniques, the network eliminates dependence on costly external drive testing services while maintaining optimization quality.
3Reliability
If drive tests are conducted frequently to update network parameters, then network performance can be maintained, but the complexity of data collection increases
Solution Approach 1:
The patent copies existing RF map structures and attenuation functions from one network to another, maintaining performance parameters without requiring complex new data collection processes. This replication approach simplifies the system architecture by reusing proven data models rather than developing new collection and processing pipelines for each network.
Data Source
AI summary
At least one example embodiment discloses a method of generating a radio frequency (RF) map of a network. The method includes obtaining, by a controller, received signal strengths of at least one user equipment (UE) in a first technology network, determining, by the controller, a back projection of a second technology network based on the received signal strengths, and generating, by the controller, an RF map of the second technology network based on the determining. The back projection represents an attenuation function of a coverage area of the second technology network and the RF map illustrates the attenuation function of the coverage area of second technology network.