Dynamic Minimum Candidate Resources Ratio in NR V2X Mode 2
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Solution Overview
Problem
In 5G New Radio (NR) Vehicle to Everything (V2X) Mode 2 resource selection, the existing method for minimizing resource collisions is inflexible, as it relies on a fixed X% ratio between resources passed to Step 2 and total available resources, failing to adapt to varying priority and traffic types, leading to potential interference and increased processing burden.
Innovation Solution
The method dynamically adjusts the X% constraint based on iteration number, priority, channel busy ratio, and traffic type, allowing different X% values for signaling and resource selection windows, and iteratively adjusts thresholds to avoid resource collisions, thereby reducing interference and processing burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed X% ratio is used between resources passed to Step 2 and total available resources, then the resource selection procedure is simple to implement, but the system cannot adapt to varying priority and traffic types, leading to increased interference and processing burden
Solution Approach 1:
The patent applies dynamics by making the X% ratio adjustable and adaptive rather than fixed. The system dynamically changes the minimum candidate resources ratio based on traffic type (periodic/aperiodic), priority levels, and channel conditions. This allows the resource selection procedure to adapt to varying conditions while maintaining a structured approach through predefined adjustment rules for different scenarios.
Solution Approach 2:
The patent changes the parameter X% (minimum candidate resources ratio) based on different conditions. Specifically, it adjusts X% according to traffic type (aperiodic traffic uses different ratios than periodic traffic), priority levels (higher priority traffic gets more resources), and channel busy ratio. This parameter adaptation resolves the contradiction by enabling flexibility without requiring complete redesign of the resource selection mechanism.
2Reliability
If the minimum candidate resources ratio is increased to reduce collision probability, then resource collision reduction is achieved, but the processing burden increases due to iterative threshold adjustments
Solution Approach 1:
The patent applies preliminary action by pre-defining the relationship between traffic type, priority, and the minimum candidate resources ratio X%. Instead of performing complex iterative searches during runtime, the system has predetermined adjustment rules that directly map traffic characteristics to appropriate X% values. This reduces processing time while maintaining reliability by ensuring appropriate resource ratios are selected based on traffic requirements.
Solution Approach 2:
The patent uses feedback mechanisms by monitoring channel busy ratio and adjusting the minimum candidate resources ratio accordingly. When the channel is busy, the system increases X% to ensure sufficient candidate resources are available, reducing collision probability. This feedback loop maintains reliability while controlling processing burden through condition-based adjustments rather than continuous iteration.
3Reliability
If iterative threshold adjustments are performed to avoid resource collisions, then resource collision avoidance is improved, but the processing burden and convergence time increase
Solution Approach 1:
The patent applies local quality by applying different minimum candidate resources ratios (X% values) to different traffic types and priority levels rather than using a uniform approach. Aperiodic traffic receives different treatment than periodic traffic, and high-priority traffic receives more resources than low-priority traffic. This localized approach improves collision avoidance for critical traffic while maintaining efficiency by not over-provisioning all traffic types equally.
Solution Approach 2:
The patent uses partial action by adjusting the minimum candidate resources ratio selectively based on traffic requirements. Instead of always using the maximum X% value, the system applies higher ratios only when necessary (e.g., for aperiodic traffic or high-priority transmissions). This maintains collision avoidance capability for critical traffic while improving overall efficiency by using lower ratios for less critical traffic types.
Data Source
AI summary
Method of resource selection where a selection window with a total number of resources is set. The method includes setting a sensing window and monitoring slots by decoding a physical sidelink control channel (PSCCH) and measuring a reference signal received power (RSRP), setting a threshold, excluding any restricted resources from the total number of resources, excluding any occupied resources from the total number of resources, and determining if an initial number of remaining resources is greater than or equal to an initial percentage of the total number of resources.