Cross-RAT RAN Planning Using Existing Signal Measurements
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Solution Overview
Problem
Existing radio access network (RAN) design techniques are costly, time-consuming, and lack automation, requiring extensive measurement campaigns and high expertise due to complex propagation models and ray tracing methods, with limited accuracy and reusability, especially with the advent of higher frequency bands in 5G networks.
Innovation Solution
A method and apparatus that utilize measurements from an existing RAN operating under a different radio access technology or frequency range to design a new RAN layer by converting and extrapolating signal quality measurements, enabling accurate network planning and optimization with reduced costs and increased automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If propagation model optimization campaigns are used to characterize propagation environments, then measurement precision is improved, but loss of time and device complexity increase
Solution Approach 1:
The patent uses crowdsource location data as a copy or proxy representation of actual user distribution patterns. Instead of performing time-consuming propagation model optimization campaigns, the system copies existing measurement data (cell traffic recordings with location information) to infer propagation characteristics and network performance metrics, thereby reducing time consumption while maintaining sufficient accuracy for network design.
2Measurement precision
If ray tracing models with detailed 3D databases are used, then measurement precision is improved, but device complexity and loss of energy increase
Solution Approach 1:
The patent replaces expensive and complex ray tracing models with simpler, more lightweight statistical models that use crowdsource location data. These simplified models consume significantly less computational resources and energy while providing sufficient accuracy for network planning and design purposes, effectively substituting high-cost tools with low-cost alternatives.
3Ease of operation
If triangulation techniques are used for user location, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent introduces crowdsource location data as an intermediary that bridges the gap between simple triangulation operations and accurate user location. This intermediary data source combines the ease of operation of existing network measurements with improved precision by aggregating location information from multiple sources and using statistical methods to infer accurate user distributions, thereby overcoming the limitations of pure triangulation.
4Measurement precision
If extensive measurement campaigns are conducted, then measurement precision is improved, but loss of time and device complexity increase
Solution Approach 1:
The patent enables the network to serve itself by utilizing existing crowdsource location data and cell traffic recordings that are already being collected for other network functions. Instead of conducting separate extensive measurement campaigns, the system reuses existing data resources to characterize propagation environments, thereby reducing the complexity and time requirements of measurement activities while maintaining high measurement precision.
Data Source
AI summary
According to an aspect, there is provided a computer-implemented method for designing a first radio access network, RAN, that is to operate according to a first radio access technology, RAT, in a first frequency range. The method comprises (i) obtaining (901) second RAN radio signal measurements of a second RAN. The second RAN operates according to a second RAT that is different to the first RAT, and/or with a second frequency range that is different to the first frequency range. The second RAN comprises a plurality of second RAN base stations that operate a plurality of second RAN cells, and the second RAN radio signal measurements comprise measurements by a plurality of wireless devices of radio signals on one or more frequencies from one or more of the plurality of second RAN base stations. The method further comprises (ii) processing (902) the second RAN radio signal measurements to estimate corresponding first RAN radio signal measurements that could be measured by said wireless devices if each of said second RAN cells were respective first RAN cells operating according to the first RAT and in the first frequency range; (iii) forming (903) an initial cell deployment for the first RAN based on an estimate of which wireless devices each first RAN cell provides coverage for according to said first RAN radio signal measurements, wherein the initial cell deployment comprises a subset of the first RAN cells; (iv) determining (904) a best serving first RAN cell in the initial cell deployment for each of the wireless devices based on the first RAN radio signal measurements; (v) for each first RAN cell in the initial cell deployment, estimating (905) the first RAN cell resource utilisation based on the wireless devices for which said first RAN cell is determined to be the best serving first RAN cell; and (vi) determining (906) an updated cell deployment based on the initial cell deployment and the estimated first RAN cell resource utilisation for each first RAN cell in the initial cell deployment.