IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment sc...IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment scenarios,the potentially high packet collision rate significantly decreases the communication efficiency of WLAN.In this paper,we propose an adaptive STA grouping scheme to overcome this dense network challenge in IEEE 802.11ax by using Buffer State Report(BSR)based Two-stage Mechanism(BTM).In order to achieve the optimal efficiency of BSR delivery,we analyze the functional relationship between STA number in group and Resource Unit(RU)efficiency.Based on this analysis results,an adaptive STA grouping algorithm with variable group size is proposed to achieve efficient grouping in BTM.The numerical results demonstrate that the proposed adaptive BTM grouping algorithm significantly improves the BSR delivery efficiency and the throughput of overall system and each STA in the ultra-dense wireless network.展开更多
The new IEEE 802.11 standard, IEEE 802.11ax, has the challenging goal of serving more Uplink (UL) traffic and users as compared with his predecessor IEEE 802.11ac, enabling consistent and reliable streams of data (ave...The new IEEE 802.11 standard, IEEE 802.11ax, has the challenging goal of serving more Uplink (UL) traffic and users as compared with his predecessor IEEE 802.11ac, enabling consistent and reliable streams of data (average throughput) per station. In this paper we explore several new IEEE 802.11ax UL scheduling mechanisms and compare between the maximum throughputs of unidirectional UDP Multi Users (MU) triadic. The evaluation is conducted based on Multiple-Input-Multiple-Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) transmission multiplexing format in IEEE 802.11ax vs. the CSMA/CA MAC in IEEE 802.11ac in the Single User (SU) and MU modes for 1, 4, 8, 16, 32 and 64 stations scenario in reliable and unreliable channels. The comparison is conducted as a function of the Modulation and Coding Schemes (MCS) in use. In IEEE 802.11ax we consider two new flavors of acknowledgment operation settings, where the maximum acknowledgment windows are 64 or 256 respectively. In SU scenario the throughputs of IEEE 802.11ax are larger than those of IEEE 802.11ac by 64% and 85% in reliable and unreliable channels respectively. In MU-MIMO scenario the throughputs of IEEE 802.11ax are larger than those of IEEE 802.11ac by 263% and 270% in reliable and unreliable channels respectively. Also, as the number of stations increases, the advantage of IEEE 802.11ax in terms of the access delay also increases.展开更多
With the ever-increasing range of video and audio applications in portable handheld devices, demand for high throughput in Wi-Fi networks is escalating. In this paper we introduce several novel features defined in nex...With the ever-increasing range of video and audio applications in portable handheld devices, demand for high throughput in Wi-Fi networks is escalating. In this paper we introduce several novel features defined in next generation WLAN, termed as IEEE 802.11ax standard, and compare between the maximum throughputs received in IEEE 802.11ax and IEEE 802.11ac in a scenario where the AP continuously transmits to one station in the Single User mode. The comparison is done as a function of the modulation/coding schemes in use. In IEEE 802.11ax we consider two levels of frame aggregation. IEEE 802.11ax outperforms IEEE 802.11ac by about 29% and 48% in reliable and unreliable channels respectively.展开更多
The new IEEE 802.11ax standard is aimed to serve many users while enabling every station to transmit a consistent stream of data without interruption. In this paper we evaluate the upper bound on the throughput of a D...The new IEEE 802.11ax standard is aimed to serve many users while enabling every station to transmit a consistent stream of data without interruption. In this paper we evaluate the upper bound on the throughput of a Downlink IEEE 802.11ax channel using the Single User (SU) mode and using the Multi User Multiple-Input-Multiple-Output (MU-MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) mode. We compare between IEEE 802.11ax and IEEE 802.11ac for the case of 1, 4, 8, 16, 32 and 64 stations in different Modulation/Coding schemes (MCS) and different transmission windows’ sizes, 64 and 256 frames in IEEE 802.11ax. IEEE 802.11ax outperforms IEEE 802.11ac in the SU and MU modes by 52% and 74% in a reliable channel respectively, while in an unreliable channel the improvements are by 59% and 103% respectively. Also, in terms of the access delay, the advantage of IEEE 802.11ax increases as the number of stations increases.展开更多
IEEE 802.11ax系统中站点(Station,STA)数量众多和潜在的高数据包冲突率导致无线局域网通信效率显著降低,本文针对上行多用户传输中的无效帧填充问题,以每轮传输中用户组的传输延迟为优化目标,提出一种多用户调度和资源分配算法。基于OF...IEEE 802.11ax系统中站点(Station,STA)数量众多和潜在的高数据包冲突率导致无线局域网通信效率显著降低,本文针对上行多用户传输中的无效帧填充问题,以每轮传输中用户组的传输延迟为优化目标,提出一种多用户调度和资源分配算法。基于OFDMA上行调度接入中动态传输时间的帧交互方案,接入点(Access Point,AP)结合STA提供的信道状态信息(Channel State Information,CSI)和缓冲区状态报告(Buffer State Report,BSR)信息来确定各站点的传输延迟;针对最小化组内用户传输延迟差的优化问题,设计传输机会(Transmit Opportunity,TXOP)时长内用户分组策略及资源块(Resource Unit,RU)-STA匹配方案;进而以最大化信道利用率为目标,确定各站点的发射功率,同时保障每组用户的传输速率。与参考调度策略对比,本文提出的调度和资源分配算法在连续多帧传输的信道利用率上有10%~15%的提升,同时也保证了用户间传输速率的稳定性。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
文摘IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment scenarios,the potentially high packet collision rate significantly decreases the communication efficiency of WLAN.In this paper,we propose an adaptive STA grouping scheme to overcome this dense network challenge in IEEE 802.11ax by using Buffer State Report(BSR)based Two-stage Mechanism(BTM).In order to achieve the optimal efficiency of BSR delivery,we analyze the functional relationship between STA number in group and Resource Unit(RU)efficiency.Based on this analysis results,an adaptive STA grouping algorithm with variable group size is proposed to achieve efficient grouping in BTM.The numerical results demonstrate that the proposed adaptive BTM grouping algorithm significantly improves the BSR delivery efficiency and the throughput of overall system and each STA in the ultra-dense wireless network.
文摘The new IEEE 802.11 standard, IEEE 802.11ax, has the challenging goal of serving more Uplink (UL) traffic and users as compared with his predecessor IEEE 802.11ac, enabling consistent and reliable streams of data (average throughput) per station. In this paper we explore several new IEEE 802.11ax UL scheduling mechanisms and compare between the maximum throughputs of unidirectional UDP Multi Users (MU) triadic. The evaluation is conducted based on Multiple-Input-Multiple-Output (MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) transmission multiplexing format in IEEE 802.11ax vs. the CSMA/CA MAC in IEEE 802.11ac in the Single User (SU) and MU modes for 1, 4, 8, 16, 32 and 64 stations scenario in reliable and unreliable channels. The comparison is conducted as a function of the Modulation and Coding Schemes (MCS) in use. In IEEE 802.11ax we consider two new flavors of acknowledgment operation settings, where the maximum acknowledgment windows are 64 or 256 respectively. In SU scenario the throughputs of IEEE 802.11ax are larger than those of IEEE 802.11ac by 64% and 85% in reliable and unreliable channels respectively. In MU-MIMO scenario the throughputs of IEEE 802.11ax are larger than those of IEEE 802.11ac by 263% and 270% in reliable and unreliable channels respectively. Also, as the number of stations increases, the advantage of IEEE 802.11ax in terms of the access delay also increases.
文摘With the ever-increasing range of video and audio applications in portable handheld devices, demand for high throughput in Wi-Fi networks is escalating. In this paper we introduce several novel features defined in next generation WLAN, termed as IEEE 802.11ax standard, and compare between the maximum throughputs received in IEEE 802.11ax and IEEE 802.11ac in a scenario where the AP continuously transmits to one station in the Single User mode. The comparison is done as a function of the modulation/coding schemes in use. In IEEE 802.11ax we consider two levels of frame aggregation. IEEE 802.11ax outperforms IEEE 802.11ac by about 29% and 48% in reliable and unreliable channels respectively.
文摘The new IEEE 802.11ax standard is aimed to serve many users while enabling every station to transmit a consistent stream of data without interruption. In this paper we evaluate the upper bound on the throughput of a Downlink IEEE 802.11ax channel using the Single User (SU) mode and using the Multi User Multiple-Input-Multiple-Output (MU-MIMO) and Orthogonal Frequency Division Multiple Access (OFDMA) mode. We compare between IEEE 802.11ax and IEEE 802.11ac for the case of 1, 4, 8, 16, 32 and 64 stations in different Modulation/Coding schemes (MCS) and different transmission windows’ sizes, 64 and 256 frames in IEEE 802.11ax. IEEE 802.11ax outperforms IEEE 802.11ac in the SU and MU modes by 52% and 74% in a reliable channel respectively, while in an unreliable channel the improvements are by 59% and 103% respectively. Also, in terms of the access delay, the advantage of IEEE 802.11ax increases as the number of stations increases.
文摘IEEE 802.11ax系统中站点(Station,STA)数量众多和潜在的高数据包冲突率导致无线局域网通信效率显著降低,本文针对上行多用户传输中的无效帧填充问题,以每轮传输中用户组的传输延迟为优化目标,提出一种多用户调度和资源分配算法。基于OFDMA上行调度接入中动态传输时间的帧交互方案,接入点(Access Point,AP)结合STA提供的信道状态信息(Channel State Information,CSI)和缓冲区状态报告(Buffer State Report,BSR)信息来确定各站点的传输延迟;针对最小化组内用户传输延迟差的优化问题,设计传输机会(Transmit Opportunity,TXOP)时长内用户分组策略及资源块(Resource Unit,RU)-STA匹配方案;进而以最大化信道利用率为目标,确定各站点的发射功率,同时保障每组用户的传输速率。与参考调度策略对比,本文提出的调度和资源分配算法在连续多帧传输的信道利用率上有10%~15%的提升,同时也保证了用户间传输速率的稳定性。
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.
