This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networ...This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networks.Unlike conventional Deep Reinforcement Learning(DRL)-based approaches for CW size adjustment,which often suffer from overestimation bias and limited exploration diversity,leading to suboptimal throughput and collision performance.Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions.First,SETL adopts a DDQN architecture(SETL-DDQN)to improve Q-value estimation accuracy and enhance training stability.Second,we incorporate a Gumbel distribution-driven exploration mechanism,forming SETL-DDQN(Gumbel),which employs the extreme value theory to promote diverse action selection,replacing the conventional-greedy exploration that undergoes early convergence to suboptimal solutions.Both models are evaluated through extensive simulations in static and time-varying IEEE 802.11 network scenarios.The results demonstrate that our approach consistently achieves higher throughput,lower collision rates,and improved adaptability,even under abrupt fluctuations in traffic load and network conditions.In particular,the Gumbel-based mechanism enhances the balance between exploration and exploitation,facilitating faster adaptation to varying congestion levels.These findings position Gumbel-enhanced DRL as an effective and robust solution for CW optimization in wireless networks,offering notable gains in efficiency and reliability over existing methods.展开更多
IEEE 802.11系列标准是无线局域网WLAN(Wireless Local Area Network)中应用最广的标准。其中IEEE 802.11a工作在5.8GHz频段,除了不受向下兼容性的限制外,同频段系统之间的干扰也很小,因而比较适合高密度、高容量的网络。IEEE 802.11a...IEEE 802.11系列标准是无线局域网WLAN(Wireless Local Area Network)中应用最广的标准。其中IEEE 802.11a工作在5.8GHz频段,除了不受向下兼容性的限制外,同频段系统之间的干扰也很小,因而比较适合高密度、高容量的网络。IEEE 802.11a采用正交频分复用(OFDM)调制方式,理论最高传输速率可达54Mbit/s,但在实际应用中,其传输净数据率均远低于此。为了评估其数据业务支持能力,指导网络容量规划,文章主要从MAC层协议性能方面对IEEE 802.11aWLAN网络的性能进行了分析,并给出了其实际吞吐量。展开更多
文摘This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network(SETL-DDQN)and an extended Gumbel distribution method,designed to optimize the Contention Window(CW)in IEEE 802.11 networks.Unlike conventional Deep Reinforcement Learning(DRL)-based approaches for CW size adjustment,which often suffer from overestimation bias and limited exploration diversity,leading to suboptimal throughput and collision performance.Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions.First,SETL adopts a DDQN architecture(SETL-DDQN)to improve Q-value estimation accuracy and enhance training stability.Second,we incorporate a Gumbel distribution-driven exploration mechanism,forming SETL-DDQN(Gumbel),which employs the extreme value theory to promote diverse action selection,replacing the conventional-greedy exploration that undergoes early convergence to suboptimal solutions.Both models are evaluated through extensive simulations in static and time-varying IEEE 802.11 network scenarios.The results demonstrate that our approach consistently achieves higher throughput,lower collision rates,and improved adaptability,even under abrupt fluctuations in traffic load and network conditions.In particular,the Gumbel-based mechanism enhances the balance between exploration and exploitation,facilitating faster adaptation to varying congestion levels.These findings position Gumbel-enhanced DRL as an effective and robust solution for CW optimization in wireless networks,offering notable gains in efficiency and reliability over existing methods.
文摘IEEE 802.11系列标准是无线局域网WLAN(Wireless Local Area Network)中应用最广的标准。其中IEEE 802.11a工作在5.8GHz频段,除了不受向下兼容性的限制外,同频段系统之间的干扰也很小,因而比较适合高密度、高容量的网络。IEEE 802.11a采用正交频分复用(OFDM)调制方式,理论最高传输速率可达54Mbit/s,但在实际应用中,其传输净数据率均远低于此。为了评估其数据业务支持能力,指导网络容量规划,文章主要从MAC层协议性能方面对IEEE 802.11aWLAN网络的性能进行了分析,并给出了其实际吞吐量。
