Tech-invite3GPPspaceIETFspace
21222324252627282931323334353637384‑5x

Content for  TR 22.837  Word version:  19.3.0

Top   Top   Up   Prev   Next
0…   4   5…   5.2…   5.3…   5.4…   5.5…   5.6…   5.7…   5.8…   5.9…   5.10…   5.11…   5.12…   5.13…   5.14…   5.15…   5.16…   5.17…   5.18…   5.19…   5.20…   5.21…   5.22…   5.23…   5.24…   5.25…   5.26…   5.27…   5.28…   5.29…   5.30…   5.31…   5.32…   6…   7…

 

5.3  Use case on rainfall monitoringp. 20

5.3.1  Descriptionp. 20

Rainfall monitoring is a topic of great importance for several application contexts: hydraulic structure design, agriculture, weather forecasting, climate modelling, etc. At present, the most widely used measurement method is rain gauge.
Traditional rainfall monitoring use rain gauges, which are located at a particular location. Wide-area rainfall monitoring using traditional rain gauges would be costly. The base stations are deployed by the operators with radio cell planning that could cover a wider area. With base stations monitoring the rainfall, for example rain rate (mm/h), it could obtain a horizontally wider-area measurement.
Radio signals, as they propagate through the atmosphere, are reduced in intensity by constituents of the atmosphere. Oxygen and water vapor are the two major components which are responsible for the signal absorption. If it is a rainy day, an additional attenuation caused by rain further increases the propagation path loss. [7] The rain attenuation depends on the size and distribution of the water droplets, hence, by quantifying and modelling the base station signal measurements, we are able to know the rain rate.
The mmWave bands, such as 28GHz and 38GHz have been used to assess coverage, large-scale path loss, and fading and multipath effects [6]. Since the 28 GHz and 38 GHz bands are also licensed for wireless backhaul communications, these frequencies can be used for rainfall monitoring [7].
The granularity of the rainfall monitoring could be smaller than the traditional measurements.
Up

5.3.2  Pre-conditionsp. 20

Peter is a farmer who takes care of a big farm that grows different crops. Peter needs to monitor the rainfall of his farm to manage reasonable irrigation, drainage and fertilizer. When there is less rainfall, Peter can select reasonable irrigation plans to improve the farmland water content condition. When there is high rainfall, Peter should improve the drainage system and fertilize the crops to avoid crop losses.

5.3.3  Service Flowsp. 20

  1. Peter has a subscription for the premium service of rainfall monitoring for a more granular location.
  2. Peter is at daily working routine and wants to check the timely rainfall information from the weather application on his phone.
  3. The RAN obtains the NR based 3GPP sensing data every hour and the 5G system processes the 3GPP sensing data to obtain sensing results and exposes the NR based sensing results to the weather application via the core network.
  4. Based on the sensing results above, the application server obtains the rainfall information (i.e. rainfall and whether it is raining) associated with location information.
  5. Peter obtains timely rainfall information from weather application on his phone.
Up

5.3.4  Post-conditionsp. 21

Peter could check the rainfall information at any time on his phone. Based on the timely rainfall information, Peter could plan the irrigation, drainage and fertilizer for the crops in his farm.

5.3.5  Existing feature partly or fully covering use case functionalityp. 21

None.

5.3.6  Potential New Requirements needed to support the use casep. 21

[PR 5.3.6-1]
The 5G network shall support collection of the NR based 3GPP sensing data from the base station.
[PR 5.3.6-2]
Based on operator's policy, the 5G system shall support mechanisms to process the 3GPP sensing data to derive the sensing results.
[PR 5.3.6-3]
Based on operator's policy, the 5G system shall provide mechanisms to expose NR based sensing results with sensing contextual information, e.g. location, to a trusted third-party application via the core network.
[PR 5.3.6-4]
The 5G system shall support sensing services with KPIs as given in Table 5.3.6-1.
Scenario Sensing service area Confidence level [%] Rainfall estimation accuracy (for a target confidence level) Accuracy of positioning estimate by sensing (for a target confidence level) Accuracy of velocity estimate by sensing (for a target confidence level) Sensing resolution Max sensing service latency[ms] Refreshing rate [s] Missed detection [%] False alarm [%]
Horizontal
[m]
Vertical [m] Horizontal [m/s] Vertical [m/s] Range resolution [m] Velocity resolution (horizontal/ vertical) [m/s x m/s]
Rainfall monitoringoutdoor95[1mm/h]
NOTE 2
N/AN/AN/AN/AN/AN/A1 min10min, application configurable55
NOTE 1:
The terms in Table 5.3.6-1 are found in clause 3.1.
NOTE 2:
For rainfall rain rate >1 mm/h[39]. Rainfall estimation accuracy describes the closeness of the measured rainfall estimation to its true rainfall value.
Up

Up   Top   ToC