In the 6G Internet of Things(IoT)paradigm,unprecedented challenges will be raised to provide massive connectivity,ultra-low latency,and energy efficiency for ultra-dense IoT devices.To address these challenges,we expl...In the 6G Internet of Things(IoT)paradigm,unprecedented challenges will be raised to provide massive connectivity,ultra-low latency,and energy efficiency for ultra-dense IoT devices.To address these challenges,we explore the non-orthogonal multiple access(NOMA)based grant-free random access(GFRA)schemes in the cellular uplink to support massive IoT devices with high spectrum efficiency and low access latency.In particular,we focus on optimizing the backoff strategy of each device when transmitting time-sensitive data samples to a multiple-input multiple-output(MIMO)-enabled base station subject to energy constraints.To cope with the dynamic varied channel and the severe uplink interference due to the uncoordinated grant-free access,we formulate the optimization problem as a multi-user non-cooperative dynamic stochastic game(MUN-DSG).To avoid dimensional disaster as the device number grows large,the optimization problem is transformed into a mean field game(MFG),and its Nash equilibrium can be achieved by solving the corresponding Hamilton-Jacobi-Bellman(HJB)and Fokker-Planck-Kolmogorov(FPK)equations.Thus,a Mean Field-based Dynamic Backoff(MFDB)scheme is proposed as the optimal GFRA solution for each device.Extensive simulation has been fulfilled to compare the proposed MFDB with contemporary random access approaches like access class barring(ACB),slotted-Additive LinksOn-lineHawaii Area(ALOHA),andminimum backoff(MB)under both static and dynamic channels,and the results proved thatMFDB can achieve the least access delay and cumulated cost during multiple transmission frames.展开更多
Grant-free random access(RA)is attractive for future network due to the minimized access delay.In this paper,we investigate the grantfree RA in multicell massive multiple-input multipleoutput(MIMO)systems with pilot r...Grant-free random access(RA)is attractive for future network due to the minimized access delay.In this paper,we investigate the grantfree RA in multicell massive multiple-input multipleoutput(MIMO)systems with pilot reuse.With backoff mechanism,user equipments(UEs)in each cell are randomly activated,and active UEs randomly select orthogonal pilots from a predefined pilot pool,which results in a random pilot contamination among cells.With the help of indicators that capture the uncertainties of UE activation and pilot selection,we derive a closed-form approximation of the spectral efficiency per cell after averaging over the channel fading as well as UEs’random behaviors.Based on the analysis,the optimal backoff parameter and pilot length that maximize the spectral efficiency can be obtained.We find that the backoff mechanism is necessary for the system with large number of UEs,as it can bring significant gains on the spectral efficiency.Moreover,as UE number grows,more backoff time is needed.展开更多
A Mobile Ad Hoc Network (MANET) is a collection of mobile nodes that can communicate directly over wireless media, without the need for a preconfigured infrastructure. Several approaches have been suggested to improve...A Mobile Ad Hoc Network (MANET) is a collection of mobile nodes that can communicate directly over wireless media, without the need for a preconfigured infrastructure. Several approaches have been suggested to improve Quality of Service (QoS) in IEEE 802.11-based MANETs through modifying some of the IEEE 802.11 Medium Access Control (MAC) algorithms, such as the backoff algorithm that is used to control the packets collision aftermath. In this work, an adaptive IEEE 802.11 backoff algorithm to improve QoS is de-veloped and tested in simulations as well as in testbed implementation. While the Binary Exponential Backoff (BEB) algorithm deployed by IEEE 802.11 reacts based on individual packet transmit trials, the new algo-rithm takes the history of successive packet transmit trials into account to provide a better QoS performance. The new algorithm has been tested against the legacy IEEE 802.11 through simulations using QualNet and a Linux-based testbed comprising a number of stations. The performed tests have shown significant im-provements in performance, with up to 33.51% improvement in delay and 7.36% improvement in packet delivery fraction compared to the original IEEE 802.11.展开更多
Based on the Distributed Coordination Function (DCF) and the Enhanced DCF (EDCF) mechanisms in IEEE 802.11 and 802.11e, a novel backoff scheme for Wireless Local Area Network (WLAN) is proposed. The scheme is to solve...Based on the Distributed Coordination Function (DCF) and the Enhanced DCF (EDCF) mechanisms in IEEE 802.11 and 802.11e, a novel backoff scheme for Wireless Local Area Network (WLAN) is proposed. The scheme is to solve the problem of the packet loss and the decrease of performance due to the increasing Contention Window (CW) when there are continuous collisions. In the proposed scheme, the CW of the packet will change dynamically with different delay for the different traffics. Mathematic formulas are presented to indicate the relationship between the CW and the delay character. ,The performance of the new scheme is also discussed with simulation results. The results show that it helps WLAN system handle multimedia simultaneously.展开更多
Mobile Ad hoc Network (MANET) is a wireless network consisting of mobile devices (laptops, smart phones, etc.) that move and communicate with each other without the use of any existing network infrastructure or centra...Mobile Ad hoc Network (MANET) is a wireless network consisting of mobile devices (laptops, smart phones, etc.) that move and communicate with each other without the use of any existing network infrastructure or centralized server to avoid collisions which have negative effects on the performance of the network. Access to the shared media is controlled by a Backoff algorithm that is a part of the Media Access Protocol. In this paper, we improve the History Based Probabilistic Backoff (HPPB) algorithm by modifying the increment/decrement behavior of the Contention Window to introduce History Based Increment Backoff (HBIB) algorithm which outperforms HBPB in terms of throughput and end-to-end delay with various numbers of nodes and different traffic loads.展开更多
A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) i...A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) in a cluster, which is revealed by formulating resource allocation as a network utility maximization problem. Then, by maximizing the total network utility with constrains of minimizing collision probability, the optimal value of CW (Wopt) can be computed according to the number of sensor nodes. The new backoff algorithm uses the common optimal value Wopt and leads to fewer collisions than binary exponential backoff algorithm. The simulation results show that the proposed algorithm outperforms standard 802.11 DCF and S-MAC in average collision times, packet delay, total energy consumption, and system throughput.展开更多
Compared with flat routing protocols, clustering is a fundamental performance improvement technique in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we integrate the mul...Compared with flat routing protocols, clustering is a fundamental performance improvement technique in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we integrate the multi-hop technique with a backoff-based clustering algorithm to organize sensors. By using an adaptive backoff strategy, the algorithm not only realizes load balance among sensor node, but also achieves fairly uniform cluster head distribution across the network. Simulation results also demonstrate our algorithm is more energy-efficient than classical ones. Our algorithm is also easily extended to generate a hierarchy of cluster heads to obtain better network management and energy-efficiency.展开更多
With the increasing attention to front-edge vehicular communication applications,distributed resource allocation is beneficial to the direct communications between vehicle nodes.However,in highly dynamic distributed v...With the increasing attention to front-edge vehicular communication applications,distributed resource allocation is beneficial to the direct communications between vehicle nodes.However,in highly dynamic distributed vehicular networks,quality of service(QoS)of the systems would degrade dramatically because of serious packet collisions in the absence of sufficient link knowledge.Focusing on the fairness optimization,a Q-learning-based collision avoidance(QCA)scheme,which is characterized by an ingenious bidirectional backoff reward model RQCA corresponding to arbitrary backoff stage transitions,has been proposed in an intelligent distributed media access control protocol.In QCA,an intelligent bidirectional backoff agent based on the Markov decision process model can actively motivate each vehicle agent to update itself toward an optimal backoff sub-intervel BSIopt through either positive or negative bidirectional transition individually,resulting in the distinct fair communication with a proper balance of the resource allocation.According to the reinforcement learning theory,the problem of goodness evaluation on the backoff stage self-selection policy is equal to the problem of maximizing Q function of the vehicle in the current environment.The final decision on BSI_(opt) related to an optimal contention window range was solved through maximizing the Q value or Q_(max).The ε-greedy algorithm was used to keep a reasonable convergence of the Q_(max) solution.For the fairness evaluation of QCA,four kinds of dynamic impacts on the vehicular networks were investigated:mobility,density,payload size,and data rate with a network simulator NS2.Consequently,QCA can achieve fair communication efficiently and robustly,with advantages of superior Jain’s fairness index,relatively high packet delivery ratio,and low time delay.展开更多
The Probability Distribution of. Slot Selection (PDoSS) of IEEE 802.11 DCF is extremely uneven, which makes the packet collision probability very high. In this paper, the authors explore how to make the stations selec...The Probability Distribution of. Slot Selection (PDoSS) of IEEE 802.11 DCF is extremely uneven, which makes the packet collision probability very high. In this paper, the authors explore how to make the stations select:the slots uniformly, and give an RWBO(P-d,w) algorithm for 802.11 DCF to make the PDoSS even and decrease the packet collision probability. A Markov model is given to analyze the PDoSS of RWBO(p(d), w). The performance of RWBO(p(d), w) is evaluated, by. simulation in terms of saturation throughput and packet collision probability. The simulation results indicate that RWBO(p(d), w) can decrease the packet contention,probability to a large extent, and utilize the channel more efficiently as compared to the 802.11 DCF. Moreover, the relation between saturation throughput, and walking probability (p(d)),the relation between saturation throughput and contention windows (w), the relation between packet collision probability and walking probability (p(d)), and the relation between packet collision probability and contention windows (w) are analyzed. The analysis indicates that RWBO(p(d), w) has some remarkable features: its saturation throughout keeps high and packet collision probability keeps very low (under 0.1) in a large range of p(d) and w, which allow users to configure p(d) and w more flexibly.展开更多
太赫兹无线局域网(Wireless Local Area Network,WLAN)是实现大带宽、短距离无线接入的重要技术途径,受太赫兹波束极窄特性影响,现有的低频WLAN媒体接入控制(Media Access Control,MAC)地址已不能直接复用于太赫兹WLAN。针对太赫兹波束...太赫兹无线局域网(Wireless Local Area Network,WLAN)是实现大带宽、短距离无线接入的重要技术途径,受太赫兹波束极窄特性影响,现有的低频WLAN媒体接入控制(Media Access Control,MAC)地址已不能直接复用于太赫兹WLAN。针对太赫兹波束极窄特性导致的信道利用率低问题,提出了负载自适应的混合接入MAC协议(Load-Adaptive Hybrid Access MAC Protocol,LAHA-MAC)。通过记录上一次工作扇区的节点数量自适应地选择信道接入方式。当工作扇区节点数量N小于接入方式选择阈值N*时,该机制采用基于竞争的接入方式,能够同时获得较高的吞吐量和较低的端到端时延;当节点数量N大于接入方式选择阈值N*时,该机制采用基于调度的接入方式,能够避免节点之间的碰撞,提高传输效率。考虑到可能出现的接入方式选择错误,该机制能够实现灵活地接入方式切换。当信道中节点碰撞次数N col大于切换阈值N*col时,将基于竞争的接入方式切换为基于调度的接入方式。仿真结果表明,该机制能够在网络负载动态变化的情况下有效提高信道利用率。展开更多
The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-bas...The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.展开更多
Ad hoc网络是一种特殊的对等式网络。传统的基于固定的或有中心的网络的协议不能满足 Ad hoc网络的需要。首先研究了 Ad hoc网络信道接入协议要考虑的隐终端问题和暴露终端问题 ,并给出了一种可能的双信道解决方案。在分析了现有的两种...Ad hoc网络是一种特殊的对等式网络。传统的基于固定的或有中心的网络的协议不能满足 Ad hoc网络的需要。首先研究了 Ad hoc网络信道接入协议要考虑的隐终端问题和暴露终端问题 ,并给出了一种可能的双信道解决方案。在分析了现有的两种退避算法后 ,提出使用退避计数器广播加信道争用估计技术来消除不公平现象。在这些结果的基础上 ,提出了一种新的信道接入协议。展开更多
基金supported by the National Natural Science Foundation of China underGrant 62371036,supported authors Haibo Wang,Hongwei Gao and Pai Jiang.
文摘In the 6G Internet of Things(IoT)paradigm,unprecedented challenges will be raised to provide massive connectivity,ultra-low latency,and energy efficiency for ultra-dense IoT devices.To address these challenges,we explore the non-orthogonal multiple access(NOMA)based grant-free random access(GFRA)schemes in the cellular uplink to support massive IoT devices with high spectrum efficiency and low access latency.In particular,we focus on optimizing the backoff strategy of each device when transmitting time-sensitive data samples to a multiple-input multiple-output(MIMO)-enabled base station subject to energy constraints.To cope with the dynamic varied channel and the severe uplink interference due to the uncoordinated grant-free access,we formulate the optimization problem as a multi-user non-cooperative dynamic stochastic game(MUN-DSG).To avoid dimensional disaster as the device number grows large,the optimization problem is transformed into a mean field game(MFG),and its Nash equilibrium can be achieved by solving the corresponding Hamilton-Jacobi-Bellman(HJB)and Fokker-Planck-Kolmogorov(FPK)equations.Thus,a Mean Field-based Dynamic Backoff(MFDB)scheme is proposed as the optimal GFRA solution for each device.Extensive simulation has been fulfilled to compare the proposed MFDB with contemporary random access approaches like access class barring(ACB),slotted-Additive LinksOn-lineHawaii Area(ALOHA),andminimum backoff(MB)under both static and dynamic channels,and the results proved thatMFDB can achieve the least access delay and cumulated cost during multiple transmission frames.
基金supported in part by the National Natural Science Foundation of China under Grant 62171231 and 62071247in part by the National Key Research & Development Program of China under Grant No. 2020YFB1807202 and 2020YFB1804900
文摘Grant-free random access(RA)is attractive for future network due to the minimized access delay.In this paper,we investigate the grantfree RA in multicell massive multiple-input multipleoutput(MIMO)systems with pilot reuse.With backoff mechanism,user equipments(UEs)in each cell are randomly activated,and active UEs randomly select orthogonal pilots from a predefined pilot pool,which results in a random pilot contamination among cells.With the help of indicators that capture the uncertainties of UE activation and pilot selection,we derive a closed-form approximation of the spectral efficiency per cell after averaging over the channel fading as well as UEs’random behaviors.Based on the analysis,the optimal backoff parameter and pilot length that maximize the spectral efficiency can be obtained.We find that the backoff mechanism is necessary for the system with large number of UEs,as it can bring significant gains on the spectral efficiency.Moreover,as UE number grows,more backoff time is needed.
文摘A Mobile Ad Hoc Network (MANET) is a collection of mobile nodes that can communicate directly over wireless media, without the need for a preconfigured infrastructure. Several approaches have been suggested to improve Quality of Service (QoS) in IEEE 802.11-based MANETs through modifying some of the IEEE 802.11 Medium Access Control (MAC) algorithms, such as the backoff algorithm that is used to control the packets collision aftermath. In this work, an adaptive IEEE 802.11 backoff algorithm to improve QoS is de-veloped and tested in simulations as well as in testbed implementation. While the Binary Exponential Backoff (BEB) algorithm deployed by IEEE 802.11 reacts based on individual packet transmit trials, the new algo-rithm takes the history of successive packet transmit trials into account to provide a better QoS performance. The new algorithm has been tested against the legacy IEEE 802.11 through simulations using QualNet and a Linux-based testbed comprising a number of stations. The performed tests have shown significant im-provements in performance, with up to 33.51% improvement in delay and 7.36% improvement in packet delivery fraction compared to the original IEEE 802.11.
基金Supported by the National Natural Science Foundation of China (No.90304008) ShaanxiInternational Cooperation Project 2003KW-08.
文摘Based on the Distributed Coordination Function (DCF) and the Enhanced DCF (EDCF) mechanisms in IEEE 802.11 and 802.11e, a novel backoff scheme for Wireless Local Area Network (WLAN) is proposed. The scheme is to solve the problem of the packet loss and the decrease of performance due to the increasing Contention Window (CW) when there are continuous collisions. In the proposed scheme, the CW of the packet will change dynamically with different delay for the different traffics. Mathematic formulas are presented to indicate the relationship between the CW and the delay character. ,The performance of the new scheme is also discussed with simulation results. The results show that it helps WLAN system handle multimedia simultaneously.
文摘Mobile Ad hoc Network (MANET) is a wireless network consisting of mobile devices (laptops, smart phones, etc.) that move and communicate with each other without the use of any existing network infrastructure or centralized server to avoid collisions which have negative effects on the performance of the network. Access to the shared media is controlled by a Backoff algorithm that is a part of the Media Access Protocol. In this paper, we improve the History Based Probabilistic Backoff (HPPB) algorithm by modifying the increment/decrement behavior of the Contention Window to introduce History Based Increment Backoff (HBIB) algorithm which outperforms HBPB in terms of throughput and end-to-end delay with various numbers of nodes and different traffic loads.
基金Project(60772088) supported by the National Natural Science Foundation of China
文摘A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) in a cluster, which is revealed by formulating resource allocation as a network utility maximization problem. Then, by maximizing the total network utility with constrains of minimizing collision probability, the optimal value of CW (Wopt) can be computed according to the number of sensor nodes. The new backoff algorithm uses the common optimal value Wopt and leads to fewer collisions than binary exponential backoff algorithm. The simulation results show that the proposed algorithm outperforms standard 802.11 DCF and S-MAC in average collision times, packet delay, total energy consumption, and system throughput.
基金Supported by the National Natural Science Foundation of China under Grant No. 60872018,60721002,60875038the National Basic Research 973 Program of China under Grant No. 2007CB310607+2 种基金SRFDP Project under Grant No. 20070293001the Science and Technology Support Foundation of Jiangsu Province under Grant No. BE2009142 and BE2010180the Scientific Research Foundation of Graduate School of Nanjing University under Grant No. 2011CL07
文摘Compared with flat routing protocols, clustering is a fundamental performance improvement technique in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we integrate the multi-hop technique with a backoff-based clustering algorithm to organize sensors. By using an adaptive backoff strategy, the algorithm not only realizes load balance among sensor node, but also achieves fairly uniform cluster head distribution across the network. Simulation results also demonstrate our algorithm is more energy-efficient than classical ones. Our algorithm is also easily extended to generate a hierarchy of cluster heads to obtain better network management and energy-efficiency.
文摘With the increasing attention to front-edge vehicular communication applications,distributed resource allocation is beneficial to the direct communications between vehicle nodes.However,in highly dynamic distributed vehicular networks,quality of service(QoS)of the systems would degrade dramatically because of serious packet collisions in the absence of sufficient link knowledge.Focusing on the fairness optimization,a Q-learning-based collision avoidance(QCA)scheme,which is characterized by an ingenious bidirectional backoff reward model RQCA corresponding to arbitrary backoff stage transitions,has been proposed in an intelligent distributed media access control protocol.In QCA,an intelligent bidirectional backoff agent based on the Markov decision process model can actively motivate each vehicle agent to update itself toward an optimal backoff sub-intervel BSIopt through either positive or negative bidirectional transition individually,resulting in the distinct fair communication with a proper balance of the resource allocation.According to the reinforcement learning theory,the problem of goodness evaluation on the backoff stage self-selection policy is equal to the problem of maximizing Q function of the vehicle in the current environment.The final decision on BSI_(opt) related to an optimal contention window range was solved through maximizing the Q value or Q_(max).The ε-greedy algorithm was used to keep a reasonable convergence of the Q_(max) solution.For the fairness evaluation of QCA,four kinds of dynamic impacts on the vehicular networks were investigated:mobility,density,payload size,and data rate with a network simulator NS2.Consequently,QCA can achieve fair communication efficiently and robustly,with advantages of superior Jain’s fairness index,relatively high packet delivery ratio,and low time delay.
文摘The Probability Distribution of. Slot Selection (PDoSS) of IEEE 802.11 DCF is extremely uneven, which makes the packet collision probability very high. In this paper, the authors explore how to make the stations select:the slots uniformly, and give an RWBO(P-d,w) algorithm for 802.11 DCF to make the PDoSS even and decrease the packet collision probability. A Markov model is given to analyze the PDoSS of RWBO(p(d), w). The performance of RWBO(p(d), w) is evaluated, by. simulation in terms of saturation throughput and packet collision probability. The simulation results indicate that RWBO(p(d), w) can decrease the packet contention,probability to a large extent, and utilize the channel more efficiently as compared to the 802.11 DCF. Moreover, the relation between saturation throughput, and walking probability (p(d)),the relation between saturation throughput and contention windows (w), the relation between packet collision probability and walking probability (p(d)), and the relation between packet collision probability and contention windows (w) are analyzed. The analysis indicates that RWBO(p(d), w) has some remarkable features: its saturation throughout keeps high and packet collision probability keeps very low (under 0.1) in a large range of p(d) and w, which allow users to configure p(d) and w more flexibly.
文摘太赫兹无线局域网(Wireless Local Area Network,WLAN)是实现大带宽、短距离无线接入的重要技术途径,受太赫兹波束极窄特性影响,现有的低频WLAN媒体接入控制(Media Access Control,MAC)地址已不能直接复用于太赫兹WLAN。针对太赫兹波束极窄特性导致的信道利用率低问题,提出了负载自适应的混合接入MAC协议(Load-Adaptive Hybrid Access MAC Protocol,LAHA-MAC)。通过记录上一次工作扇区的节点数量自适应地选择信道接入方式。当工作扇区节点数量N小于接入方式选择阈值N*时,该机制采用基于竞争的接入方式,能够同时获得较高的吞吐量和较低的端到端时延;当节点数量N大于接入方式选择阈值N*时,该机制采用基于调度的接入方式,能够避免节点之间的碰撞,提高传输效率。考虑到可能出现的接入方式选择错误,该机制能够实现灵活地接入方式切换。当信道中节点碰撞次数N col大于切换阈值N*col时,将基于竞争的接入方式切换为基于调度的接入方式。仿真结果表明,该机制能够在网络负载动态变化的情况下有效提高信道利用率。
基金Research Supporting Project Number(RSP2024R421),King Saud University,Riyadh,Saudi Arabia。
文摘The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.
文摘Ad hoc网络是一种特殊的对等式网络。传统的基于固定的或有中心的网络的协议不能满足 Ad hoc网络的需要。首先研究了 Ad hoc网络信道接入协议要考虑的隐终端问题和暴露终端问题 ,并给出了一种可能的双信道解决方案。在分析了现有的两种退避算法后 ,提出使用退避计数器广播加信道争用估计技术来消除不公平现象。在这些结果的基础上 ,提出了一种新的信道接入协议。
