Wireless Measurement Engine for Dynamic Network Optimization
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Solution Overview
Problem
Conventional communication networks are static and unable to support multiple connection types efficiently, leading to increased deployment complexity and cost, as well as limitations in optimizing network quality and usage across various environmental and usage conditions.
Innovation Solution
A wireless measurement engine utilizing AI/ML techniques to continuously identify optimal communication connection technologies for devices, determining wireless measurements in real-time to configure and reconfigure network nodes, enabling autonomous connectivity across multiple spectrums and adapting to actual usage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional static networks are used, then deployment is simpler, but network quality optimization and adaptability to multiple connection types is limited
Solution Approach 1:
The network system is designed to support multiple connection types (5G, 4G, Wi-Fi, satellite, CBRS) through a unified architecture that can dynamically select and switch between different network technologies. The UE device incorporates a network selection module that evaluates multiple network options and autonomously selects the optimal connection type based on current conditions, enabling the system to perform multiple communication functions through a single integrated platform.
Solution Approach 2:
The patent implements dynamic network configuration where network parameters, bandwidth allocations, and connection types are continuously adjusted based on real-time conditions. The network selection module periodically evaluates network quality metrics and automatically reconfigures connections to optimize performance. This dynamic adaptation allows the system to respond to changing environmental conditions, usage patterns, and network availability without requiring manual reconfiguration or complex static planning.
2Adaptability or versatility
If multiple network types are supported, then connectivity options increase, but deployment cost increases
Solution Approach 1:
The patent consolidates multiple network interface functions and control mechanisms into a unified network selection module and centralized controller. Instead of deploying separate independent systems for each network type, the invention merges the management of 5G, 4G, Wi-Fi, satellite, and CBRS connections into a single intelligent platform that handles selection, switching, and optimization across all network types, thereby reducing overall deployment costs while maintaining multi-connectivity capabilities.
Solution Approach 2:
The network selection module autonomously performs network evaluation, selection, and switching without requiring manual intervention or complex operational support. The system automatically monitors network conditions, assesses quality metrics, and makes real-time connection decisions based on predefined policies and current usage patterns. This self-service capability reduces the need for additional operational personnel and system management overhead, thereby lowering deployment and operational costs.
3Reliability
If network configuration is manual, then control is precise, but optimization speed and responsiveness to usage changes is slow
Solution Approach 1:
The patent implements a feedback-driven network optimization system where the network selection module continuously monitors connection quality metrics, usage patterns, and network conditions. This real-time feedback information is fed back to the control algorithm, which automatically adjusts network parameters, switches connections, and reconfigures resources to maintain optimal performance. The feedback loop enables the system to respond dynamically to changing conditions while preserving reliable network quality through continuous monitoring and adjustment.
Solution Approach 2:
The network optimization system operates autonomously without requiring manual configuration or intervention. The network selection module automatically evaluates network conditions, selects optimal connection types, and configures parameters based on real-time measurements and usage patterns. This self-service capability enables rapid optimization responses to changing network conditions and usage demands while maintaining reliable connection quality through automated control algorithms.
4Productivity
If static network configuration is used, then deployment is faster, but ability to adapt to environmental and usage conditions is limited
Solution Approach 1:
The patent implements a dynamic network configuration system where connection parameters, bandwidth allocations, and network selection criteria are continuously adjusted based on real-time environmental conditions and usage patterns. The network selection module monitors metrics such as signal quality, network load, and device performance, automatically reconfiguring connections to optimize for current conditions. This dynamic approach enables the system to adapt to changing environments and usage demands while maintaining fast deployment through automated configuration processes that eliminate manual setup requirements.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods are disclosed for wireless network optimization. An example apparatus includes interface circuitry, machine readable instructions, and programmable circuitry. The example interface circuitry is to obtain multi-access wireless data from a wireless device associated with a network, the multi-access wireless data associated with an operation of at least one of the wireless device or infrastructure of the network. Additionally, the example programmable circuitry is to utilize the machine readable instructions to compute, in substantially real time relative to the operation, a measurement based on the multi-access wireless data. The example programmable circuitry is also to determine, in substantially real time relative to the operation, a change to a configuration of at least one of the wireless device or a virtual radio based on the measurement, the virtual radio associated with the network.