Dynamic Signal Processing Architecture for Spectrum Monitoring
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Solution Overview
Problem
Existing technologies struggle to monitor the wireless environment in real-time, particularly in applications like IoT, autonomous cars, and spectrum sharing systems, where quick and reliable detection of different user tiers is crucial for enforcing spectrum policies.
Innovation Solution
A scalable and flexible signal classification and processing architecture that includes a controller managing interactions between data interfaces, processing nodes, and controller plugins, allowing for dynamic processing flows and heterogeneous processing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional fixed architecture is used for signal processing, then the system structure is simple, but the system lacks flexibility and adaptability for different processing requirements
Solution Approach 1:
The system is divided into independent processing nodes, each capable of performing specific signal processing functions. These nodes can be individually configured and chained together to form different processing flows, enabling flexibility without requiring a complete system redesign for different applications.
Solution Approach 2:
The processing architecture allows dynamic configuration of processing flows at runtime. Users can chain together different processing nodes in various sequences and reconfigure the system adaptively based on specific signal processing requirements, making the system both flexible and relatively simple.
2Reliability
If real-time wireless environment monitoring is implemented, then the detection capability is improved, but the processing time and system complexity increase
Solution Approach 1:
The system pre-configures multiple processing nodes with specific detection functions. When a signal needs to be analyzed, the appropriate pre-configured nodes are chained together and executed, eliminating the need for runtime configuration decisions and reducing processing time while maintaining reliable detection.
Solution Approach 2:
The system enables rapid execution of signal processing by using pre-configured processing flows that can be quickly activated. Critical detection functions are prioritized and executed efficiently through optimized node chaining, allowing real-time monitoring without excessive processing delays.
Data Source
AI summary
Processing flows and related systems and methods are disclosed. A computing system includes one or more data interfaces, one or more other components, and a controller. The one or more data interfaces are configured to provide an interface to a data source. The one or more other components include one or more controller plugins, one or more processing nodes, or both the one or more controller plugins and the one or more processing nodes. The controller is configured to manage interactions between the one or more data interfaces and the one or more other components and enable a user to chain together the one or more data interfaces and the one or more other components according to one or more flows. The one or more controller plugins are configured to provide results of the one or more flows to one of a user interface and a system interface.


