Uplink Multi-User Trigger Frame Retransmission via Dynamic Backoff

The patent applies preliminary action by implementing a prediction mechanism that forecasts transmission success before actual transmission occurs. The access point predicts whether uplink multi-user transmission will succeed based on historical data and current channel conditions, and only transmits trigger frames when prediction indicates high success probability. This prevents wasted transmissions in poor conditions, improving both throughput and reliability.

The patent implements feedback by continuously monitoring transmission outcomes and using this information to adjust future transmission decisions. The system collects feedback on transmission success/failure, updates prediction models, and adapts trigger frame transmission strategies accordingly. This closed-loop feedback mechanism enables the system to learn from past performance and improve reliability while maintaining high throughput.

The patent applies preliminary action by performing prediction analysis before retransmission decisions. Instead of blindly retransmitting trigger frames after failures, the system first predicts whether retransmission is likely to succeed based on current channel conditions and historical patterns. This preliminary assessment prevents futile retransmissions that would waste resources, while still enabling retransmission when conditions are favorable.

The patent implements parameter changes by dynamically adjusting retransmission parameters such as backoff counters, transmission power, and timing based on prediction results and failure analysis. When predictions indicate poor conditions, the system modifies transmission parameters to optimize success probability while minimizing resource consumption. This adaptive parameter adjustment resolves the contradiction between reliability and resource loss.

The patent applies dynamics by making backoff counter values dynamic rather than fixed. The system adjusts backoff counter values based on real-time channel conditions, prediction results, and traffic priorities. For high-priority traffic or favorable channel conditions, smaller backoff values are used to reduce delay. For congested conditions or low-priority traffic, larger backoff values prevent collisions. This dynamic adjustment resolves the contradiction between collision avoidance and transmission delay.

The patent implements parameter changes by varying backoff counter parameters adaptively based on multiple factors including channel quality, traffic priority, and prediction outcomes. The system can select from different backoff strategies (e.g., exponential backoff, linear backoff, or predictive backoff) and adjust parameters within each strategy to optimize the balance between collision avoidance and delay minimization for different traffic scenarios.