Wireless Network Object Detection Using mmWave Reflections
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Solution Overview
Problem
Existing wireless network systems face challenges in accurately determining the location and movement of individuals due to insufficient information about UE presence, leading to inefficient resource allocation, inaccurate emergency response, and security vulnerabilities.
Innovation Solution
Utilizing reflected radio frequency signals to detect the presence and movement of objects by emitting mmWave frequencies and sensing their reflections, which are processed to infer information about animate and inanimate objects without relying on UE presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If wireless network systems rely on UE presence information to determine location and movement, then network resource allocation can be simplified, but detection accuracy and reliability deteriorate due to insufficient information about individual presence
Solution Approach 1:
The patent introduces mmWave signals as an intermediary medium to detect objects and movement patterns. The wireless network transmits mmWave signals that reflect off objects, and the reflected signals are analyzed to determine location and movement without requiring direct UE presence information. This intermediary approach resolves the contradiction by enabling accurate detection through physical signal interaction rather than relying solely on UE-reported data.
Solution Approach 2:
The patent replaces the traditional information-based detection system (relying on UE presence reporting) with a physics-based detection system using mmWave electromagnetic signals. By substituting the information-gathering mechanism from software-based UE reporting to physics-based signal reflection analysis, the system achieves both operational simplicity and detection accuracy simultaneously.
2Device complexity
If wireless networks use traditional methods to track individual location, then device complexity remains low, but security vulnerabilities and emergency response accuracy worsen due to insufficient detection capability
Solution Approach 1:
The patent makes the wireless network infrastructure multi-functional by enabling it to perform both traditional communication tasks and object detection/security monitoring functions using the same mmWave infrastructure. The base stations and network elements continue their communication roles while simultaneously detecting objects, patterns, and movement through signal analysis, thus improving security reliability without adding separate dedicated tracking devices.
Solution Approach 2:
The wireless network infrastructure serves itself by using its existing mmWave transmission capability to simultaneously perform detection functions. The same network elements that transmit data for communication also detect objects and movement patterns through signal reflection analysis, eliminating the need for separate dedicated detection devices and maintaining low system complexity while enhancing security reliability.
3Measurement precision
If wireless networks deploy more network elements to improve detection coverage, then detection precision improves, but network complexity and resource consumption increase
Solution Approach 1:
The patent merges the detection function with existing network elements rather than adding separate detection devices. Base stations, access points, and other network infrastructure components continue their communication functions while simultaneously performing object detection through mmWave signal analysis. This merging approach improves detection coverage and precision by utilizing the existing distributed network elements without increasing overall system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise detection of objects and movement patterns, optimizing network resource allocation, improving emergency response, and enhancing security by accurately identifying the presence of individuals in various conditions.
Implementation Method 1
determining whether an object detection criterion is satisfied within a target spatial area by sensing reflected radio frequency signals
Implementation Method 2
emitting mmWave frequencies and sensing their reflections
Data Source
AI summary
Systems and methods for detecting objects and motion using wireless networks can include determining beamforming control parameters for one or more transceivers, transmitting, by a processing device, the beamforming control parameters to the one or more transceivers, and receiving, from one or more of the transceivers, data representative of detected radio frequency reflection signals. They can also include determining, based on the aggregated data, whether an object detection criterion is satisfied within a target spatial area, and responsive to the determination that the object detection criterion is satisfied, transmitting a notification reflective of the satisfaction of the object detection criterion. They can further include adjusting, based on the data, the beamforming control parameters, and transmitting adjusted beamforming control parameters to one or more transceivers of the plurality of transceivers.