Autonomous Wireless Network Master Station Positioning
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Solution Overview
Problem
Existing wireless communications networks face challenges in optimizing network performance and accessibility, particularly when devices are not within visual range of the master station or base station, and manual interventions are not feasible when the network has access to a fixed network.
Innovation Solution
A method for establishing a wireless, autonomous communications network that auto-configures by determining the current network configuration and optimal position of the master station or base station through measurements, allowing the network to dynamically adjust and compensate for failures without manual intervention, using an algorithm that transfers functionality to a better-suited transceiver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual intervention is used to optimize network topology, then network performance can be optimized, but manual intervention is not possible when the network has access to a fixed network via the master station
Solution Approach 1:
The network enables self-configuration through an algorithm that automatically determines current network configuration and optimal master station position based on measurement data from transceivers. The system autonomously identifies when optimization is needed and executes the reconfiguration without human intervention, allowing the network to serve itself.
Solution Approach 2:
The master station functionality is made dynamic by allowing it to be transferred between different transceivers based on their current positions and network conditions. The algorithm continuously evaluates which transceiver is best suited to be the master station and enables automatic transfer of functionality to maintain optimal network performance.
2Ease of operation
If the master station or base station is placed in a fixed position, then network configuration is simplified, but devices not within visual range cannot join the network
Solution Approach 1:
The system makes the master station position dynamic by enabling functionality transfer between transceivers. When devices are added or removed from the network, the algorithm recalculates optimal master station placement and automatically transfers functionality to a transceiver that provides the best network coverage, ensuring all devices can join regardless of initial positioning.
Solution Approach 2:
The algorithm performs preliminary evaluation of network configuration and transceiver positions to determine the optimal master station location before any reconfiguration occurs. This allows the system to proactively prepare for topology changes and ensure continuous optimal coverage as devices are added or removed.
3Productivity
If the master station or base station is manually positioned for optimal performance, then network illumination is optimized, but the network cannot autonomously compensate for failures or changes
Solution Approach 1:
The network automatically detects when the current master station can no longer provide optimal coverage due to failure or positional changes, and the algorithm autonomously selects a new transceiver to take over master station functionality. This self-healing capability ensures continuous optimal network performance without manual intervention.
Solution Approach 2:
The system prepares for potential failures by having all transceivers capable of assuming master station functionality. The algorithm continuously evaluates which transceiver would be the best replacement, so when a failure occurs, the network can immediately switch to a pre-identified suitable candidate, providing redundancy and reliability.
4Reliability
If fixed-network access is implemented via the master station or base station, then network connectivity is ensured, but the master station position becomes constrained
Solution Approach 1:
The patent separates the fixed-network access function from the master station functionality. The transceiver with fixed-network access remains stationary to maintain reliable connectivity, while the master station functionality can be dynamically assigned to any transceiver based on optimal network coverage requirements. This extraction allows both functions to operate independently without constraining each other.
Data Source
AI summary
The present disclosure provides optimal network performance and network illumination in a wireless, autonomous communications network with a dynamic network topology achieved by auto-configuration. Functional alogorthemic enhancements of the communications network are used, enabling the communications network to automatically determine the current network configuration and the accessibility of the transceivers that are associated with the communications network by using measurements and to determine the optimal position of a master station at any one time from the data obtained from the measurements.