Wireless Signal Filtering via Blind Identification Engine
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Solution Overview
Problem
The challenge in the field of computer systems is the need for a method to efficiently filter out unwanted wireless signals from the vast spectrum of IoT devices, which is essential for reducing computational complexity and energy consumption, especially in the context of the Internet of Things (IoT) where numerous devices generate varying signals, making it difficult to analyze relevant data effectively.
Innovation Solution
The development of a blind signal identification engine with low computational complexity that filters out unwanted signals prior to analysis, utilizing a platform that includes IoT devices, hubs, and services, enabling efficient data collection and management through predefined networking protocols, secure key exchanges, and dynamic scan interval adjustments to optimize signal processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all signals in the wireless spectrum are captured for analysis, then complete data coverage is achieved, but computational complexity and energy consumption increase significantly
Solution Approach 1:
The patent applies preliminary action by performing signal filtering before full analysis. The system first captures all wireless signals, then applies a filtering mechanism that pre-identifies and removes unwanted signals (such as interference, non-targeted communications, or low-priority traffic) before the main analysis pipeline processes them. This preliminary filtering step reduces the volume of data requiring complex computational analysis, thereby lowering overall computational complexity while preserving complete signal coverage for potential review.
2Loss of information
If all signals in the wireless spectrum are captured for analysis, then complete data coverage is achieved, but energy consumption increases significantly
Solution Approach 1:
The system performs preliminary signal filtering to identify and discard unwanted signals before conducting energy-intensive analysis. By pre-processing the captured spectrum to remove non-targeted or low-value signals, the system reduces the computational workload and consequently lowers energy consumption while maintaining complete signal coverage capability for when it is needed.
3Use of energy by stationary object
If computational complexity is reduced by filtering signals, then energy consumption decreases, but ability to capture all signals for analysis is compromised
Solution Approach 1:
The filtering mechanism is designed to pre-process signals in a way that reduces computational load and energy consumption while preserving complete signal coverage. The system captures all signals first, then applies intelligent filtering that maintains the ability to access and analyze any signal if needed, thereby balancing energy efficiency with comprehensive data availability.
4Productivity
If unwanted signals are filtered out prior to analysis, then computational efficiency improves, but filtering accuracy must be maintained to avoid losing relevant data
Solution Approach 1:
The system applies preliminary filtering with carefully designed criteria that distinguish unwanted signals from relevant ones. The filtering mechanism uses multiple parameters (such as signal type, frequency range, source identification, and priority levels) to accurately identify and remove only truly unwanted signals while preserving all potentially relevant data for analysis, thereby maintaining filtering accuracy while improving computational efficiency.
Data Source
AI summary
An apparatus and method are described for filtering wireless signals. For example, one embodiment of the invention comprises: one or more radios to receive a plurality of wireless signals within a defined spectrum; an energy detection and filtering module to filter received wireless signals based on a detected energy level of the received wireless signals and in accordance with a set of energy-based filtering parameters, the energy detection and filtering module to output energy-filtered wireless signals; and a signal characteristic analysis and filtering module to analyze and filter the energy-filtered wireless signals based on characteristics of the received wireless signals in accordance with a set of signal analysis filtering parameters to output energy-and-characteristic filtered wireless signals.