18558663. LANDSCAPE SENSING USING RADIO SIGNALS simplified abstract (Telefonaktiebolaget LM Ericsson (publ))
Contents
- 1 LANDSCAPE SENSING USING RADIO SIGNALS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 LANDSCAPE SENSING USING RADIO SIGNALS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about Landscape Sensing using Radio Signals
- 1.11 Original Abstract Submitted
LANDSCAPE SENSING USING RADIO SIGNALS
Organization Name
Telefonaktiebolaget LM Ericsson (publ)
Inventor(s)
Vijaya Yajnanarayana of Bangalore (IN)
Dongdong Huang of Nanjing (CN)
Deep Shrestha of Linköping (SE)
Yi Geng of Nanjing, Jiangsu (CN)
Ali Behravan of Stockholm (SE)
Erik Dahlman of Stockholm (SE)
LANDSCAPE SENSING USING RADIO SIGNALS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18558663 titled 'LANDSCAPE SENSING USING RADIO SIGNALS
Simplified Explanation
The patent application describes systems and methods for landscape sensing using radio signals. A base station communicates with User Equipment (UE) to determine the landscape type in which the UE is operating based on channel measurements, without the need for additional sensors or radar infrastructure.
- Base station obtains channel measurements related to the UE
- Determines landscape type based on the measurements
- Reduces signaling between base stations
- Reduces computational complexity with smaller input features
- Can be implemented on embedded base station hardware
Key Features and Innovation
- Landscape sensing using radio signals - Base station communicates with UE to determine landscape type - No need for additional sensors or radar infrastructure - Reduces signaling between base stations - Reduces computational complexity with smaller input features
Potential Applications
- Telecommunications industry - IoT devices - Smart cities - Environmental monitoring - Agriculture
Problems Solved
- Efficiently determining landscape type without additional sensors - Reducing signaling between base stations - Reducing computational complexity for implementation
Benefits
- Cost-effective landscape sensing - Improved communication efficiency - Simplified infrastructure requirements - Enhanced data collection for various applications
Commercial Applications
"Radio Signal Landscape Sensing Technology for Telecommunications and IoT Devices"
This technology can be utilized in telecommunications networks and IoT devices to enhance communication efficiency and data collection. It can also be applied in smart city initiatives, environmental monitoring systems, and agricultural operations to improve overall performance and decision-making processes.
Questions about Landscape Sensing using Radio Signals
How does this technology impact the telecommunications industry?
This technology improves communication efficiency and reduces the need for additional infrastructure, making it cost-effective for telecommunications companies.
What are the potential applications of landscape sensing using radio signals beyond telecommunications?
This technology can be applied in various industries such as IoT devices, smart cities, environmental monitoring, and agriculture for improved data collection and decision-making processes.
Original Abstract Submitted
Systems and methods for landscape sensing using radio signals are provided. In some embodiments, a base station configured to communicate with a User Equipment (UE) includes a radio interface and processing circuitry configured to: obtain a plurality of channel measurements relating to the UE; and determine a landscape type in which the UE is operating based on the plurality of channel measurements. In this way, the base station can infer the UE's landscape without the need for any new sensor or radar infrastructure requirements. In this way, the signaling need between base stations can be reduced. In some embodiments, smaller dimension input features will reduce the computational complexity so that it can be implemented on an embedded base station hardware.