Cloud Network Optimizer for Connected Vehicles
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Solution Overview
Problem
Existing solutions for connected vehicles fail to optimize radio type selection due to neglecting external channel load and resource demand, leading to suboptimal radio type designation and channel congestion.
Innovation Solution
A cloud-based network optimizer that analyzes external channel load and resource demand to generate candidate radio configurations for connected vehicles, allowing them to select from multiple radio types based on probability, reducing channel congestion and maximizing residual channel load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing solutions define an optimum radio type and require all connected vehicles to use it, then all vehicles within the geographic region use the same radio type, but this results in channel congestion and poor performance
Solution Approach 1:
The system transitions from a static single-optimum radio type assignment to a dynamic multi-radio configuration system. The cloud server generates multiple radio configurations with different selection probabilities that are dynamically adjusted based on external channel load and resource demand conditions, allowing the system to adapt to changing network environments and avoid channel congestion.
Solution Approach 2:
The invention changes the parameter of radio type selection from a fixed single value to a probabilistic distribution across multiple radio types. By assigning different selection probabilities to different radio configurations based on real-time channel load and resource demand, the system enables vehicles to stochastically select radio types, thereby distributing traffic load and preventing congestion on any single channel.
2Device complexity
If existing solutions determine optimum radio types without considering external channel load and resource demand, then the determination process is simple, but the designated radio type is actually not optimum
Solution Approach 1:
The system implements feedback mechanisms where the cloud server continuously monitors external channel load and resource demand conditions, then uses this feedback to adjust the selection probabilities of different radio configurations. This closed-loop approach ensures that radio type recommendations remain optimal by incorporating real-time network state information into the decision-making process.
Solution Approach 2:
The cloud server performs preliminary analysis of external channel load and resource demand before generating radio configurations. By pre-calculating the most suitable radio types based on current network conditions and distributing these configurations to vehicles in advance, the system enables vehicles to make informed selection decisions without complex real-time calculations, balancing computational complexity with selection accuracy.
3Ease of operation
If existing solutions do not globally configure radio types to maximize residual channel load, then configuration is simpler, but network performance is not optimized
Solution Approach 1:
The cloud server acts as an intermediary that performs the complex task of global configuration optimization. It analyzes aggregate network data from multiple geographic regions, determines optimal radio type distributions that maximize residual channel load, and distributes these configurations to vehicles. This approach centralizes the computational complexity while keeping individual vehicle operations simple, thereby achieving both configuration ease and network performance optimization.
Data Source
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AI summary
The disclosure includes embodiments for providing cloud-based network optimization for connected vehicles. In some embodiments, a method includes receiving, by a connected vehicle, configuration data describing a set of candidate vehicle-to-anything (V2X) channels of a V2X radio of the connected vehicle and configuration selection probability values describing a likelihood that particular candidate V2X channels of the set will be selected. In some embodiments, the method includes selecting a V2X channel from the set that does not have the highest likelihood of being selected. In some embodiments, the method includes configuring the V2X radio of the connected vehicle to transmit data packets using the selected V2X channel.