Multi-Frequency V2X Scheduling for Dynamic Subchannel Allocation
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Solution Overview
Problem
Current V2X transmission scheduling methods in wireless communication systems rely on static frequency mappings, leading to poor capacity utilization and communication quality due to a lack of consideration for instantaneous conditions in the V2X environment.
Innovation Solution
Implementing a dynamic and opportunistic scheduling method for user equipment (UE) in a distributed C-V2X environment, where transmission frequencies are scheduled based on UE-specific, performance-related metrics such as estimated user numbers, bandwidth fit, channel loading conditions, and quality requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static frequency mapping is used for V2X transmission scheduling, then device complexity is reduced and ease of operation is improved, but capacity utilization and communication quality deteriorate
Solution Approach 1:
The patent implements dynamic frequency selection where UEs adaptively choose transmission frequencies based on real-time channel conditions, traffic load, and quality requirements. This transforms the static frequency mapping into a dynamic system that responds to instantaneous V2X environment conditions, thereby improving capacity utilization while maintaining operational simplicity through automated decision-making algorithms.
Solution Approach 2:
The system changes transmission frequency parameters dynamically based on multiple metrics including estimated user numbers, bandwidth fit, channel loading conditions, and quality requirements. By adjusting frequency allocation parameters in response to changing conditions, the system optimizes capacity utilization without requiring complex manual scheduling operations.
2Device complexity
If static frequency mapping is used for V2X transmission scheduling, then device complexity is reduced, but communication quality deteriorates
Solution Approach 1:
The patent employs dynamic frequency selection mechanisms that adapt to real-time channel conditions and traffic demands. This dynamic approach improves communication quality by selecting optimal frequencies based on instantaneous conditions, while the automated nature of the adaptation prevents excessive complexity in the scheduling system.
Solution Approach 2:
The system incorporates feedback loops where UEs monitor channel conditions, traffic load, and transmission quality, then use this information to adjust frequency selections. This feedback mechanism ensures high communication quality by continuously adapting to changing conditions without requiring complex centralized control, thereby maintaining manageable system complexity.
3Productivity
If dynamic and opportunistic scheduling is implemented, then capacity utilization and communication quality are enhanced, but device complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where each UE independently performs frequency selection based on local observations of channel conditions and traffic load. This distributed self-service approach enhances capacity utilization through adaptive frequency allocation while avoiding the complexity of centralized scheduling control, as each device makes autonomous decisions based on predefined criteria.
Solution Approach 2:
The system uses simplified models and metrics (such as estimated user numbers and channel loading conditions) that can be easily copied and exchanged between UEs. This allows complex scheduling decisions to be made using replicated information and algorithms, enhancing capacity utilization without proportionally increasing system complexity.
Data Source
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AI summary
A method, apparatus, and computer-readable medium at a transmitting user equipment (UE) in a distributed cellular vehicle-to-everything environment are disclosed to determine a schedule for transmissions on subchannels of multiple frequencies based on a set of UE-specific, dynamic, and performance related metrics or criteria. The metrics may include an estimated number of users on a subchannel, a best-bandwidth fit, channel loading conditions, transmission range, and quality requirements of an application, among others. Such a schedule for transmissions on subchannels of multiple frequencies may result in either an improved capacity utilization, an improved communication quality, or both.