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Intelligent Multi-link EDCA Optimization for Delay-Bounded QoS in Wi-Fi 7

Peini Yi, Wenchi Cheng, Jingqing Wang, Jinzhe Pan, Yuehui Ouyang, Wei Zhang

TL;DR

This paper investigates the correlation between overall MLO QoS indicators and the configuration of EDCA parameters and Acess Catagory (AC) traffic allocation among links, and forms a constrained optimization problem aiming to minimize the sum of overall packet loss rates for all access categories while satisfying their respective overall delay violation probability constraints.

Abstract

IEEE 802.11be (Wi-Fi 7) introduces Multi-Link Operation (MLO) as a While MLO offers significant parallelism and capacity, realizing its full potential in guaranteeing strict delay bounds and optimizing Quality of Service (QoS) for diverse, heterogeneous traffic streams in complex multi-link scenarios remain a significant challenge. This is largely due to the limitations of static Enhanced Distributed Channel Access (EDCA) parameters and the complexity inherent in cross-link traffic management. To address this, this paper investigates the correlation between overall MLO QoS indicators and the configuration of EDCA parameters and Acess Catagory (AC) traffic allocation among links. Based on this analysis, we formulate a constrained optimization problem aiming to minimize the sum of overall packet loss rates for all access categories while satisfying their respective overall delay violation probability constraints. A Genetic Algorithm (GA)-based MLO EDCA QoS optimization algorithm is designed to efficiently search the complex configuration space of AC assignments and EDCA parameters. Experimental results demonstrate that the proposed approach's efficacy in generating adaptive MLO configuration strategies that align with diverse service requirements. The proposed solution significantly improves delay distribution characteristics, and enhance QoS robustness and resource utilization efficiency in high-load MLO environments.

Intelligent Multi-link EDCA Optimization for Delay-Bounded QoS in Wi-Fi 7

TL;DR

This paper investigates the correlation between overall MLO QoS indicators and the configuration of EDCA parameters and Acess Catagory (AC) traffic allocation among links, and forms a constrained optimization problem aiming to minimize the sum of overall packet loss rates for all access categories while satisfying their respective overall delay violation probability constraints.

Abstract

IEEE 802.11be (Wi-Fi 7) introduces Multi-Link Operation (MLO) as a While MLO offers significant parallelism and capacity, realizing its full potential in guaranteeing strict delay bounds and optimizing Quality of Service (QoS) for diverse, heterogeneous traffic streams in complex multi-link scenarios remain a significant challenge. This is largely due to the limitations of static Enhanced Distributed Channel Access (EDCA) parameters and the complexity inherent in cross-link traffic management. To address this, this paper investigates the correlation between overall MLO QoS indicators and the configuration of EDCA parameters and Acess Catagory (AC) traffic allocation among links. Based on this analysis, we formulate a constrained optimization problem aiming to minimize the sum of overall packet loss rates for all access categories while satisfying their respective overall delay violation probability constraints. A Genetic Algorithm (GA)-based MLO EDCA QoS optimization algorithm is designed to efficiently search the complex configuration space of AC assignments and EDCA parameters. Experimental results demonstrate that the proposed approach's efficacy in generating adaptive MLO configuration strategies that align with diverse service requirements. The proposed solution significantly improves delay distribution characteristics, and enhance QoS robustness and resource utilization efficiency in high-load MLO environments.

Paper Structure

This paper contains 10 sections, 22 equations, 6 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Analytical Model for Multi-Link EDCA QoS
  4. EDCA Collision Model
  5. Delay Performance
  6. Multi-Link EDCA Optimization
  7. Parameters Sensitivity
  8. Delay Bound QoS Optimization Problem
  9. Results and Discussion
  10. Conclusion

Figures (6)

  • Figure 1: Multi-link EDCA system with $M=2$ links and AC-to-link allocation.
  • Figure 2: The EDCA contention process within the AIFS zone model on a single link.
  • Figure 3: The parameter sensitivity of EDCA: (a) impact to delay reliability index, (b) impact of packet loss probability.
  • Figure 4: Fitness function convergence for MLO and Single-Link EDCA Optimization.
  • Figure 5: Comparison of QoS performance for Default EDCA, Optimized EDCA, and Optimized MLO EDCA: (a) delay violation probability, (b) packet loss probability.
  • ...and 1 more figures