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RainfalLTE: A Zero-effect Rainfall Sensing System Utilizing Existing LTE Infrastructure

Pengfei Shi, Fei Shang, Haohua Du

Abstract

Environmental sensing is an important research topic in the integrated sensing and communication (ISAC) system. Current works often focus on static environments, such as buildings and terrains. However, dynamic factors like rainfall can cause serious interference to wireless signals. In this paper, we propose a system called RainfalLTE that utilizes the downlink signal of LTE base stations for device-independent rain sensing. In articular, it is fully compatible with current communication modes and does not require any additional hardware. We evaluate it with LTE data and rainfall information provided by a weather radar in Badaling Town, Beijing The results show that for 10 classes of rainfall, RainfalLTE achieves over 97% identification accuracy. Our case study shows that the assistance of rainfall information can bring more than 40% energy saving, which provides new opportunities for the design and optimization of ISAC systems.

RainfalLTE: A Zero-effect Rainfall Sensing System Utilizing Existing LTE Infrastructure

Abstract

Environmental sensing is an important research topic in the integrated sensing and communication (ISAC) system. Current works often focus on static environments, such as buildings and terrains. However, dynamic factors like rainfall can cause serious interference to wireless signals. In this paper, we propose a system called RainfalLTE that utilizes the downlink signal of LTE base stations for device-independent rain sensing. In articular, it is fully compatible with current communication modes and does not require any additional hardware. We evaluate it with LTE data and rainfall information provided by a weather radar in Badaling Town, Beijing The results show that for 10 classes of rainfall, RainfalLTE achieves over 97% identification accuracy. Our case study shows that the assistance of rainfall information can bring more than 40% energy saving, which provides new opportunities for the design and optimization of ISAC systems.

Paper Structure

This paper contains 23 sections, 9 equations, 12 figures.

Table of Contents

  1. Introduction
  2. Why do LTE base stations need to perceive rainfall information?
  3. Rainfall significantly reduces base station coverage.
  4. Typical usage scenarios
  5. System overview
  6. System Design
  7. Basic model.
  8. Practical issues.
  9. Rainfall sensing network.
  10. Implementation
  11. Dataset.
  12. Details of data processing.
  13. Software.
  14. EVALUATION
  15. Baseline accuracy.
  16. ...and 8 more sections

Figures (12)

  • Figure 1: Sensing the rainfall based on LTE downlink signals.
  • Figure 2: Rainfall causes significant interference to LTE signals. (a) The coverage area of the base station signal on a sunny day. (b) Rainy weather causes a reduction in the coverage area by about 40%. (c) Signals in different frequency bands are sensitive to rain fading to varying degrees.
  • Figure 3: Overview of RainfalLTE.
  • Figure 4: Basic model of the system. (a) The probability density distribution of received signal strength is affected by the environment, distance, and device status, all of which are related to weather. (b) The RSSI distribution during rainfall. (c) The RSSI distribution when it does not rain.
  • Figure 5: Rainfall sensing network. (a) We construct a graph with adjacent base stations, using signal strength information and user behavior data to form node features. (b) We utilize RainNet to extract common features of the nodes for fine-grained rainfall sensing.
  • ...and 7 more figures