Wireless Network Analytics Engine for Mitigating Interference and Contention
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Solution Overview
Problem
Wireless networks, particularly Wi-Fi networks, face issues such as connectivity problems, poor throughput, and user experience due to factors like dense device deployment, proprietary algorithms, and interference from non-WiFi devices, which are difficult to detect and diagnose.
Innovation Solution
An analytics engine is introduced as a central intelligence to detect, analyze, classify, and control wireless network problems by mapping user input and state information into problem signatures, determining instructions for alleviation, and providing actionable insights to mitigate these issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If CSMA/CA mechanisms are used to regulate transmissions in densely deployed Wi-Fi networks, then fairness and simplicity are maintained, but medium contention increases and throughput decreases
Solution Approach 1:
The patent introduces a centralized controller or coordination mechanism that acts as an intermediary between Wi-Fi devices and the medium. This controller manages back-off timing and transmission scheduling, replacing the purely distributed CSMA/CA approach. By introducing this intermediary, the system maintains the simplicity of CSMA/CA for basic operations while adding centralized intelligence to resolve medium contention and improve throughput in dense deployments.
2Adaptability or versatility
If proprietary algorithms are implemented by end device vendors for roaming, then device-specific optimization is achieved, but network performance becomes sub-optimal
Solution Approach 1:
The patent establishes a universal standardized algorithm for roaming that can be implemented across all devices in the network. This universal approach replaces proprietary vendor-specific algorithms, ensuring that all devices follow the same coordination rules. The standardized algorithm achieves network-wide optimization while maintaining the ability to adapt to different device types through parameter configuration rather than fundamental algorithmic differences.
3Adaptability or versatility
If legacy (802.11a/b/g) end devices are supported in the network, then compatibility is maintained, but overall network throughput is reduced
Solution Approach 1:
The patent implements local quality by allowing different transmission parameters and rates for different device types within the same network. Legacy devices (802.11a/b/g) can operate at their native lower speeds while newer devices can utilize higher throughput modes. The system optimizes locally for each device type rather than forcing a uniform approach, thereby maintaining compatibility while minimizing the impact on overall network throughput through efficient resource allocation.
4Quantity of substance
If unlicensed bands are used for WiFi communication, then spectrum availability is increased, but interference from non-WiFi devices increases
Solution Approach 1:
The patent implements enhanced carrier sense mechanisms that provide feedback about channel conditions and interference levels. Devices monitor the medium not only for WiFi signals but also for non-WiFi interference, and this feedback information is used to adjust transmission timing and power levels. The feedback loop enables the network to adapt to interference from non-WiFi devices in unlicensed bands, maintaining spectrum utilization while mitigating harmful effects.
Data Source
AI summary
Systems, methods and apparatuses for mitigating a wireless networking problem of a wireless network are disclosed. One method includes determining, by an analytics engine, a problem associated with the wireless network, wherein the analytics engine is operative as a central intelligence for detection, analyzing, classifying, root-causing, or controlling the wireless network. The method further includes receiving, by the analytics engine, a collected user input and state information, mapping, by at least the analytics engine, a problem signature of the user input and the state information to at least one of a number of possible problem network conditions, determining, by the analytics engine, instructions for alleviating the problem based on the mapping of the problem signature, and providing, by the analytics engine, the instructions.