Adaptive Wireless Network Control via Environmental Sensing
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Solution Overview
Problem
Industrial environments pose challenges for achieving highly reliable wireless communications due to the stochastic nature of wireless propagation media, which can be affected by environmental changes and interfering sources like moving objects, making it difficult to maintain consistent packet delivery rates and quality of service.
Innovation Solution
An automated network control system that adapts network configuration based on local environmental conditions by collecting sensory information, learning wireless propagation parameters, and predicting the effects of environmental changes, using a multi-unit structure with short-term and long-term memory subsystems to make immediate and coordinated decisions for optimizing network traffic quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wired interfaces are used to ensure high reliability of communications, then reliability is improved, but deployment cost and flexibility deteriorate
Solution Approach 1:
The patent replaces wired mechanical connections with wireless communication systems. The wireless network control system uses electronic signal processing and electromagnetic wave transmission to achieve communication without physical cable connections, thereby improving deployment flexibility while maintaining reliability through advanced error correction and network monitoring protocols.
Solution Approach 2:
The patent dynamically adjusts wireless communication parameters such as transmission power, modulation schemes, and error correction codes based on channel conditions. This allows the system to adapt to varying environmental factors and maintain high reliability comparable to wired connections while preserving the flexibility advantages of wireless deployment.
2Ease of operation
If wireless communications are used to improve deployment flexibility, then ease of deployment is improved, but communication reliability deteriorates due to stochastic propagation medium
Solution Approach 1:
The patent implements a network control system that continuously monitors wireless channel conditions, packet delivery rates, and error metrics. Based on this feedback, the system dynamically adjusts transmission parameters, selects appropriate modulation schemes, and activates error correction mechanisms to maintain reliable communications in the flexible wireless environment.
Solution Approach 2:
The patent employs dynamic adaptation of communication parameters in response to changing wireless channel conditions. The system adjusts transmission power, coding rates, and frequency selection in real-time based on environmental factors such as interference from moving objects and changes in the propagation medium, thereby maintaining reliability despite the stochastic nature of wireless channels.
3Reliability
If frequency and spatial redundancy techniques are used to address interference and reliability issues, then reliability is improved, but information transmission cost increases
Solution Approach 1:
The patent applies redundancy techniques selectively rather than universally. The network control system monitors channel conditions and activates error correction and redundancy mechanisms only when reliability thresholds are approached or exceeded, thereby reducing the overall amount of redundant information transmitted while maintaining adequate reliability levels.
Solution Approach 2:
The patent dynamically adjusts the degree of redundancy applied based on current channel conditions. When interference is detected or packet delivery rates decline, the system increases error correction codes and redundancy; when conditions are good, it reduces redundancy to minimize information overhead, thereby optimizing the balance between reliability and transmission efficiency.
Data Source
AI summary
Systems, apparatuses and methods may provide for technology that adjusts, via a short-term subsystem, a communications parameter for one or more of wireless communication devices based on data from one or more of a plurality of sensors. The technology may also determine, via a neural network, a prediction of future performance of the wireless network based on a state of the network environment, wherein the state of the network environment includes information from the short-term subsystem and location information about the wireless communication devices and other objects in the environment, and determine a change in network configuration to improve a quality of communications in the wireless network based on the prediction of future performance of the wireless network. The technology may further generate generic path loss models based on time-stamped RSSI maps and record a sequence of events that cause a significant drop in RSSI to determine a change in network configuration.