WLAN Client Stack Emulator for Connectivity Analysis
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Solution Overview
Problem
Existing methods for determining WLAN connectivity and reachability in client devices are limited, as they cannot analyze internal states or data, provide only partial reasoning, are hardware-dependent, or produce large amounts of encrypted data that require extensive processing and expertise to decode.
Innovation Solution
A client device with a processor executing a client WLAN stack that emulates multiple layers to analyze connectivity, link quality, and network reachability, using unencrypted packets and event data to provide real-time analysis, and optionally reporting outputs to an external device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing methods use serving network entities to analyze WLAN connectivity, then generic connection states can be determined, but internal device states and client-side protocol facilitation cannot be observed
Solution Approach 1:
The patent introduces an intermediary analysis entity that receives and processes WLAN event data from client devices. This intermediary acts as a mediator between the client device's internal states and external observers, enabling visibility into protocol facilitation without requiring direct access to internal device memory or processing logic. The intermediary collects event data including protocol state transitions, packet exchange decisions, and hardware platform-specific information, then analyzes this data to provide comprehensive connectivity insights.
Solution Approach 2:
The patent creates a virtual copy of the WLAN protocol stack that runs alongside the actual protocol implementation. This copied protocol stack receives event data from the real stack and replicates its behavior and state transitions in a virtual environment. By observing this virtual copy, analysts can understand client-side protocol facilitation without interfering with actual device operation or exposing sensitive internal states directly.
2Loss of information
If WLAN sniffer modules are used for connectivity analysis, then partial reasoning about protocol facilitation can be obtained, but encrypted upper-layer traffic cannot be analyzed
Solution Approach 1:
The patent captures and analyzes WLAN event data at the protocol stack level, before upper-layer traffic is encrypted. By intercepting event data from the WLAN protocol stack and lower layers, the system obtains information about protocol facilitation decisions, packet exchange logic, and connectivity states in their raw, unencrypted form. This preliminary capture occurs at the point where data has not yet been subjected to end-to-end encryption, allowing comprehensive analysis of protocol behavior without the limitations of encrypted traffic analysis.
3Loss of information
If operating-system events are used for connectivity analysis, then data from lower protocol layers can be analyzed, but hardware platform specifics and protocol decision data are excluded
Solution Approach 1:
The patent segments the WLAN event data collection process into distinct components that capture different aspects of protocol operation and hardware interaction. The event data structure is divided into separate fields representing protocol state transitions, packet exchange decisions, hardware platform identifiers, and timing information. This segmentation allows the system to collect and analyze hardware-specific details and protocol decision data while maintaining the ability to adapt to different hardware platforms through standardized event data interfaces.
4Loss of information
If debugging software is used to analyze raw WLAN data, then internal low-layer data can be accessed, but large processing times and expert knowledge are required
Solution Approach 1:
The patent transforms raw WLAN event data into standardized, pre-processed parameters that are optimized for analysis. The event data undergoes parameter transformation where raw protocol states, packet information, and hardware details are converted into structured fields with consistent formats and meanings. This parameter change reduces processing time by eliminating the need for expert-level decoding of raw binary data, while preserving all essential information about internal low-layer WLAN operations. The transformed parameters can be directly analyzed by automated systems without requiring specialized knowledge.
Data Source
AI summary
A client device and method for analysis of a predetermined set of parameters associated with a radio coupling to a WLAN is provided. The client device includes a memory and a radio coupled to at least one processor. The at least one processor executes in the memory a first client Wireless Local Area Network (WLAN) stack having a plurality of layers configured to couple the radio to a WLAN. The at least one processor also executes in the memory a second client WLAN stack emulating the plurality of layers of the first client WLAN stack. The at least one processor is configured to receive, at the second client WLAN stack, data from the plurality of layers of the first client WLAN stack and analyze a predetermined set of WLAN parameters of the client device based on the data received from the plurality of layers of the first client WLAN stack.