This paper proposes a new channel access algorithm based on channel occupancy time （COT） fairness to guarantee fairness and improve the aggregate throughput of 802.11b multi-rate WLANs. In the algorithm, the COT is ...This paper proposes a new channel access algorithm based on channel occupancy time （COT） fairness to guarantee fairness and improve the aggregate throughput of 802.11b multi-rate WLANs. In the algorithm, the COT is used as fairness index to analyze the fairness of WLANs instead of the channel access probability （CAP） used in the distributed coordination function （DCF）. The standard COT is given by access point （AP） and broadcasted to all wireless stations. The AP and wireless stations in the WLAN can achieve COT-based fairness by adjusting their packet length, sending the multiple back-to-back packets at one time, or giving up an opportunity to access the channel. Analysis and simulations show that our algorithm can provide COT-fairness. Compared with the CAP-based algorithm, the proposed algorithm leads to improvements in aggregate throughput of IEEE 802. lib multi-rate WLANs.展开更多
In this paper, we propose a mechanism named modified backoff （MB） mechanism to decrease the channel idle time in IEEE 802.11 distributed coordination function （DCF）. In the noisy channel, when signal-to-noise rat...In this paper, we propose a mechanism named modified backoff （MB） mechanism to decrease the channel idle time in IEEE 802.11 distributed coordination function （DCF）. In the noisy channel, when signal-to-noise ratio （SNR） is low, applying this mechanism in DCF greatly improves the throughput and lowers the channel idle time. This paper presents an analytical model for the performance study of IEEE 802.11 MB-DCF for nonsaturated heterogeneous traffic in the presence of transmission errors. First, we introduce the MB-DCF and compare its performance to IEEE 802.11 DCF with binary exponential backoff （BEB）. The IEEE 802.11 DCF with BEB mechanism suffers from more channel idle time under low SNR. The MB-DCF ensures high throughput and low packet delay by reducing the channel idle time under the low traffic in the network. However, to the best of the authors＇ knowledge, there are no previous works that enhance the performance of the DCF under imperfect wireless channel. We show through analysis that the proposed mechanism greatly outperforms the original IEEE 802.11 DCF in the imperfect channel condition. The effectiveness of physical and link layer parameters on throughput performance is explored. We also present a throughput investigation of the heterogeneous traffic for different radio conditions.展开更多
With the exponential growth of mobile terminals and the widespread adoption of Internet of Things(IoT)technologies,an increasing number of devices rely on wireless local area networks(WLAN)for data transmission.To add...With the exponential growth of mobile terminals and the widespread adoption of Internet of Things(IoT)technologies,an increasing number of devices rely on wireless local area networks(WLAN)for data transmission.To address this demand,deploying more access points(APs)has become an inevitable trend.While this approach enhances network coverage and capacity,it also exacerbates co-channel interference(CCI).The multi-AP cooperation introduced in IEEE 802.11be(Wi-Fi 7)represents a paradigm shift from conventional single-AP architectures,offering a novel solution to CCI through joint resource scheduling across APs.However,designing efficient cooperation mechanisms and achieving optimal resource allocation in dense AP environment remain critical research challenges.To mitigate CCI in high-density WLANs,this paper proposes a radio resource allocation method based on 802.11be multi-AP cooperation.First,to reduce the network overhead associated with centralized AP management,we introduce a distributed interference-aware AP clustering method that groups APs into cooperative sets.Second,methods for multi-AP cooperation information exchange,and cooperation transmission processes are designed.To support network state collection,capability advertisement,and cooperative trigger execution at the protocol level,this paper enhances the 802.11 frame structure with dedicated fields for multi-AP cooperation.Finally,considering the mutual influence between power and channel allocation,this paper proposes a joint radio resource allocation algorithm that employs an enhanced genetic algorithm for resource unit(RU)allocation and Q-learning for power control,interconnected via an inner-outer dual-loop architecture.Simulation results demonstrate the effectiveness of the proposed CCI avoidance mechanism and radio resource allocation algorithm in enhancing throughput in dense WLAN scenarios.展开更多
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
基金Supported by National Natural Science Foundation of China (No.60472078 and No.90604013) .
文摘This paper proposes a new channel access algorithm based on channel occupancy time （COT） fairness to guarantee fairness and improve the aggregate throughput of 802.11b multi-rate WLANs. In the algorithm, the COT is used as fairness index to analyze the fairness of WLANs instead of the channel access probability （CAP） used in the distributed coordination function （DCF）. The standard COT is given by access point （AP） and broadcasted to all wireless stations. The AP and wireless stations in the WLAN can achieve COT-based fairness by adjusting their packet length, sending the multiple back-to-back packets at one time, or giving up an opportunity to access the channel. Analysis and simulations show that our algorithm can provide COT-fairness. Compared with the CAP-based algorithm, the proposed algorithm leads to improvements in aggregate throughput of IEEE 802. lib multi-rate WLANs.
文摘In this paper, we propose a mechanism named modified backoff （MB） mechanism to decrease the channel idle time in IEEE 802.11 distributed coordination function （DCF）. In the noisy channel, when signal-to-noise ratio （SNR） is low, applying this mechanism in DCF greatly improves the throughput and lowers the channel idle time. This paper presents an analytical model for the performance study of IEEE 802.11 MB-DCF for nonsaturated heterogeneous traffic in the presence of transmission errors. First, we introduce the MB-DCF and compare its performance to IEEE 802.11 DCF with binary exponential backoff （BEB）. The IEEE 802.11 DCF with BEB mechanism suffers from more channel idle time under low SNR. The MB-DCF ensures high throughput and low packet delay by reducing the channel idle time under the low traffic in the network. However, to the best of the authors＇ knowledge, there are no previous works that enhance the performance of the DCF under imperfect wireless channel. We show through analysis that the proposed mechanism greatly outperforms the original IEEE 802.11 DCF in the imperfect channel condition. The effectiveness of physical and link layer parameters on throughput performance is explored. We also present a throughput investigation of the heterogeneous traffic for different radio conditions.
基金supported by National Natural Science Foundation of China(No.62201074),Reliable Mechanism for Edge Collaboration Service in Highly Dynamic Scenarios.
文摘With the exponential growth of mobile terminals and the widespread adoption of Internet of Things(IoT)technologies,an increasing number of devices rely on wireless local area networks(WLAN)for data transmission.To address this demand,deploying more access points(APs)has become an inevitable trend.While this approach enhances network coverage and capacity,it also exacerbates co-channel interference(CCI).The multi-AP cooperation introduced in IEEE 802.11be(Wi-Fi 7)represents a paradigm shift from conventional single-AP architectures,offering a novel solution to CCI through joint resource scheduling across APs.However,designing efficient cooperation mechanisms and achieving optimal resource allocation in dense AP environment remain critical research challenges.To mitigate CCI in high-density WLANs,this paper proposes a radio resource allocation method based on 802.11be multi-AP cooperation.First,to reduce the network overhead associated with centralized AP management,we introduce a distributed interference-aware AP clustering method that groups APs into cooperative sets.Second,methods for multi-AP cooperation information exchange,and cooperation transmission processes are designed.To support network state collection,capability advertisement,and cooperative trigger execution at the protocol level,this paper enhances the 802.11 frame structure with dedicated fields for multi-AP cooperation.Finally,considering the mutual influence between power and channel allocation,this paper proposes a joint radio resource allocation algorithm that employs an enhanced genetic algorithm for resource unit(RU)allocation and Q-learning for power control,interconnected via an inner-outer dual-loop architecture.Simulation results demonstrate the effectiveness of the proposed CCI avoidance mechanism and radio resource allocation algorithm in enhancing throughput in dense WLAN scenarios.
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.
文摘为了提高W PAN应用环境下IEEE802.11b的吞吐量,首先分析IEEE802.11b DCF协议应用时的数据包传输时序,得到IEEE802.11b系统的吞吐量性能与包长及包错误概率的关系,然后对W PAN干扰网络存在时包错误概率与PLCP服务数据单元(PSDU,PLCP service data u-nit)值之间的关系进行建模.在理论上证明了在一定的W PAN干扰强度下,IEEE802.11b系统存在一个最佳的数据包长度,可以使得系统的吞吐量最大.在此基础上提出了W PAN干扰网络存在时的自适应包长方案.仿真结果表明,所提方案可以有效地提高网络吞吐量.
