Contention Window Value Research Articles

A neighbor discovery protocol with adaptive collision alleviation for wireless robotic networks

Recently, several movement control algorithms have been proposed to move robots to the desired locations and complete various collaborative tasks. These algorithms usually require information exchange among robots, which in turn relies on efficient neighbor discovery. However, neighbor discovery of robots is a challenging problem due to limited communication range and beacon collision. Here, how to set the time slot length and contention window to alleviate the beacon collisions is a major issue: too large or too small slot length and contention window values cannot achieve good performance in the robotic network. Therefore, we propose a neighbor discovery protocol with an adaptive collision alleviation mechanism, i.e. ND-ACA. ND-ACA adopts a simple mechanism to detect and avoid potential collisions before sending beacon, and adaptively adjusts both slot length and backoff window according to the number of historical beacon collections and beacon collisions. Extensive simulation results show the efficiency of our proposed approach. To the best of our knowledge, this is the first work in the literature that explore the joint implementation effects that simultaneously consider the robot mobility model and neighbor discovery.

Reinforcement Learning-based Wi-Fi Contention Window Optimization

The collision avoidance mechanism adopted by the IEEE 802.11 standard is not optimal. The mechanism employs a binary exponential backoff (BEB) algorithm in the medium access control (MAC) layer. Such an algorithm increases the backoff interval whenever a collision is detected to minimize the probability of subsequent collisions. However, the increase of the backoff interval causes degradation of the radio spectrum utilization (i.e., bandwidth wastage). That problem worsens when the network has to manage the channel access to a dense number of stations, leading to a dramatic decrease in network performance. Furthermore, a wrong backoff setting increases the probability of collisions such that the stations experience numerous collisions before achieving the optimal backoff value. Therefore, to mitigate bandwidth wastage and, consequently, maximize the network performance, this work proposes using reinforcement learning (RL) algorithms, namely Deep Q Learning (DQN) and Deep Deterministic Policy Gradient (DDPG), to tackle such an optimization problem. In our proposed approach, we assess two different observation metrics, the average of the normalized level of the transmission queue of all associated stations and the probability of collisions. The overall network’s throughput is defined as the reward. The action is the contention window (CW) value that maximizes throughput while minimizing the number of collisions. As for the simulations, the NS-3 network simulator is used along with a toolkit known as NS3-gym, which integrates a reinforcement-learning (RL) framework into NS-3. The results demonstrate that DQN and DDPG have much better performance than BEB for both static and dynamic scenarios, regardless of the number of stations. Additionally, our results show that observations based on the average of the normalized level of the transmission queues have a slightly better performance than observations based on the collision probability. Moreover, the performance difference with BEB is amplified as the number of stations increases, with DQN and DDPG showing a 45.52% increase in throughput with 50 stations.

A Modified IEEE 802.15.6 Mac Scheme to Enhance Performance of Wireless Body Area Networks in E-Health Applications

The recently released IEEE 802.15.6 standard specifies several physical (PHY) layers and medium access control (MAC) layer protocols for variety of medical and non-medical applications of Wireless Body Area Networks (WBAN). The medical applications of WBAN has several obligatory requirements and constrains viz. high reliability, strict delay deadlines and low power consumption. The standard IEEE 802.15.6 MAC scheme is not able to fulfil the all requirements of medical applications of WBAN. To address this issue we propose an IEEE 802.15.6-based MAC scheme that is the modification of superframe structure, user priorities and access mechanism of standard IEEE 802.15.6 MAC scheme. The proposed superframe has three access phases: random access phases (RAP), manage access phases (MAP) and contention access phase (CAP). The proposed four user priorities nodes access the channel during RAP using CAMA/CA mechanism with a large value of contention window. The proposed MAC scheme uses RTS/CTS access mechanism instead of basic access mechanism to mitigate the effect of hidden and expose terminal problem. Moreover, we develop an analytical model to evaluate the performance of proposed MAC scheme and solve the analytical model using Maple. The results show that the modified IEEE 802.15.6 MAC scheme achieve the better performance in terms of reliability, throughput, average access delay, energy consumption, channel utilization and fairness compared to standard IEEE 802.15.6 MAC scheme in E-health applications.

MODELING OF IEEE 802.11 COMPUTER NETWORKS OPERATION AT INCREASED INTERFERENCE INTENSITY

Context. High level of industrial noise increases the loss of information frames during transmission, which in turn decreases the network throughput. We propose a mathematical model of IEEE 802.11 networks operation under conditions of increased interference intensity. Objective. The purpose of this paper is to express in an explicit analytical form the effect of bit error rate (BER) on the probability of frame transmission and the network throughput. Method. We have proposed the method for constructing a model that allows you to directly calculate the dependence of the frame transmission probability on the number of stations operating in saturation mode, which is convenient for engineering calculations. The values of the model coefficients were selected by comparing the calculation results with the results obtained using the known Bianchi model, which describes the network operation in the form of a Markov process. In the range of up to 23 stations working with one access point, which corresponds to a collision probability of up to 0.5, the indicated dependences for both models satisfy each other with an accuracy sufficient for the practical application. An expression for the network throughput has been defined. Results. The results of the model development were used to take into account the effect of interference intensity on the information transfer process. This made it possible to explicitly express the effect of BER on the probability of frame transmission and the network throughput in the case of variations in the length of the frames and with a different number of competing stations. The degree of throughput reduction has been determined for BER = 10–5, 5∙10–5, 10–4 and increasing value of minimum contention window. Conclusions. In this work, a mathematical model has been developed for direct calculation of the probability of frame transmission and network throughput at different levels of BER.

Multilink Operation in IEEE 802.11be Wireless LANs: Backoff Overflow Problem and Solutions.

The next-generation wireless LAN standard named IEEE 802.11be supports a multilink operation to cost-efficiently boost throughput performance, for which an efficient multilink channel scheme is essential. The synchronous channel access scheme with an enhancement allowing multilink transmission before backoff completion greatly enhances the performance of multilink devices with no simultaneous transmit and receive capability, for which, however, backoff count compensation is necessary for coexistence with legacy and other multilink devices. In this paper, we identify the backoff count overflow problem of the enhanced synchronous channel access scheme with backoff compensation, which becomes aggravated once triggered due to repeated compensations. Then, we propose four solutions to mitigate this problem: limiting consecutive free-riding transmissions, limiting a compensated backoff value, using the contention window value of a main link, and balancing transmissions between links. Through comparative evaluation and analyses for dense single-spot and indoor random deployment scenarios, we demonstrate in terms of throughput and latency that the proposed solutions successfully mitigate the problem while preserving the coexistence performance.

Wireless Lan Performance Enhancement Using Double Deep Q-Networks

Due to the exponential growth in the use of Wi-Fi networks, it is necessary to study its usage pattern in dense environments for which the legacy IEEE 802.11 MAC (Medium Access Control) protocol was not specially designed. Although 802.11ax aims to improve Wi-Fi performance in dense scenarios due to modifications in the physical layer (PHY), however, MAC layer operations remain unchanged, and are not capable enough to provide stable performance in dense scenarios. Potential applications of Deep Learning (DL) to Media Access Control (MAC) layer of WLAN has now been recognized due to their unique features. Deep Reinforcement Learning (DRL) is a technique focused on behavioral sensitivity and control philosophy. In this paper, we have proposed an algorithm for setting optimal contention window (CW) under different network conditions called DRL-based Contention Window Optimization (DCWO). The proposed algorithm operates in three steps. In the initial step, Wi-Fi is being controlled by the 802.11 standards. In the second step, the agent makes the decisions concerning the value of CW after the TRAIN procedure for the proposed algorithm. The final phase begins after the training, defined by a time duration specified by the user. Now, the agent is fully trained, and no updates will be no longer received. Now the CW is updated via the OPTIMIZE process of DCWO. We have selected total network throughput, instantaneous network throughput, fairness index, and cumulative reward, and compared our proposed scheme DCWO with the Centralized Contention window Optimization with DRL (CCOD). Simulation results show that DCWO with Double Deep Q-Networks (DDQN) performs better than CCOD with (i) Deep Deterministic Policy Gradient (DDPG) and (ii) Deep Q-Network (DQN). More specifically, DCWO with DDQN gives on average 28% and 23% higher network throughput than CCOD in static and dynamic scenarios. Whereas in terms of instantaneous network throughput DCWO gives around 10% better results than the CCOD. DCWO achieves almost near to optimal fairness in static scenarios and better than DQN and DDPG with CCOD in dynamic scenarios. Similarly, while the cumulative reward achieved by DCWO is almost the same with CCOD with DDPG, the uptrend of DCWO is still encouraging.

Effect of service differentiation on QoS in IEEE 802.11e enhanced distributed channel access: a simulation approach

The enhanced distributed channel access (EDCA) protocol is a supplement to IEEE 802.11 medium access control (MAC), ratified by IEEE 802.11e task group to support quality of service (QoS) requirements of both data and real-time applications. Previous research show that it supports priority scheme for multimedia traffic but strict QoS is not guaranteed. This can be attributed to inappropriate tuning of the medium access parameters. Thus, an in-depth analysis of the EDCA protocol and ways of tuning medium access parameters to improve QoS requirements for multimedia traffic is presented in this work. An EDCA model was developed and simulated using MATLAB to assess the effect of differentiating contention window (CW) and arbitration inter-frame space (AIFS) of different traffic on QoS parameters. The optimal performance, delay, and maximum sustainable throughput for each traffic type were computed under saturation load. Insight shows that traffic with higher priority values acquired most of the available channels and starved traffic with lower priority values. The AIFS has more influence on the QoS of EDCA protocol. It was also observed that small CW values generate higher packet drops and collision rate probability. Thus, EDCA protocol provides mechanism for service differentiation which strongly depends on channel access parameters: CW sizes and AIFS.

Coexistence Analysis of 5G NR Unlicensed and WiGig in Millimeter-Wave Spectrum

The emerging 5G New Radio (NR) cellular systems that may operate in millimeter-wave (mmWave) frequency bands are expected to offer larger bandwidths. They are to be deployed in densely crowded environments, where the traffic load has a high degree of variability, which may introduce capacity bottlenecks. One of the options to alleviate the latter is to concurrently utilize the radio resources available in unlicensed mmWave bands, e.g., at 60 GHz. In this work, we address the coexistence of mmWave-based NR Unlicensed (NR-U) and WiGig technologies and account for the mmWave-specific directionality, propagation, and blockage effects. By further incorporating the features of duty cycling and random access operation, we construct a mathematical framework, which is capable of characterizing the achievable data rates of the NR-U users that operate over both licensed and unlicensed mmWave spectrum simultaneously. Our numerical results demonstrate that the rate attained by such devices is primarily regulated by the initial contention window size that, in its turn, heavily depends on the system and environmental parameters. We report the optimal contention window values for a wide range of blocker and user densities as well as antenna array configurations.

Joint Optimization of Multi-Hop Broadcast Protocol and MAC Protocol in Vehicular Ad Hoc Networks.

Beacon messages and emergency messages in vehicular ad hoc networks (VANETs) require a lower delay and higher reliability. The optimal MAC protocol can effectively reduce data collision in VANETs communication, thus minimizing delay and improving reliability. In this paper, we propose a Q-learning MAC protocol based on detecting the number of two-hop neighbors. The number of two-hop neighbors in highway scenarios is calculated with very little overhead using the beacon messages and neighbor locations to reduce the impact of hidden nodes. Vehicle nodes are regarded as agents, using Q-learning and beacon messages to train the near-optimal contention window value of the MAC layer under different vehicle densities to reduce the collision probability of beacon messages. Furthermore, based on the contention window value after training, a multi-hop broadcast protocol combined with contention window adjustment for emergency messages in highway scenarios is proposed to reduce forwarding delay and improve forwarding reliability. We use the trained contention window value and the state information of neighboring vehicles to assign an appropriate forwarding waiting time to the forwarding node. Simulation experiments are conducted to evaluate the proposed MAC protocol and multi-hop broadcast protocol and compare them with other related protocols. The results show that our proposed protocols outperform the other related protocols on several different evaluation metrics.

OFDMA Backoff Control Scheme for Improving Channel Efficiency in the Dynamic Network Environment of IEEE 802.11ax WLANs.

IEEE 802.11ax uplink orthogonal frequency division multiple access (OFDMA)-based random access (UORA) is a new feature for random channel access in wireless local area networks (WLANs). Similar to the legacy random access scheme in WLANs, UORA performs the OFDMA backoff (OBO) procedure to access the channel and decides on a random OBO counter within the OFDMA contention window (OCW) value. An access point (AP) can determine the OCW range and inform each station (STA) of it. However, how to determine a reasonable OCW range is beyond the scope of the IEEE 802.11ax standard. The OCW range is crucial to the UORA performance, and it primarily depends on the number of contending STAs, but it is challenging for the AP to accurately and quickly estimate or keep track of the number of contending STAs without the aid of a specific signaling mechanism. In addition, the one for this purpose incurs an additional delay and overhead in the channel access procedure. Therefore, the performance of a UORA scheme can be degraded by an improper OCW range, especially when the number of contending STAs changes dynamically. We first observed the effect of OCW values on channel efficiency and derived its optimal value from an analytical model. Next, we proposed a simple yet effective OBO control scheme where each STA determines its own OBO counter in a distributed manner rather than adjusting the OCW value globally. In the proposed scheme, each STA determines an appropriate OBO counter depending on whether the previous transmission was successful or not so that collisions can be mitigated without leaving OFDMA resource units unnecessarily idle. The results of a simulation study confirm that the throughput of the proposed scheme is comparable to the optimal OCW-based scheme and is improved by up to 15 times compared to the standard UORA scheme.

AP-based CW Synchronization Scheme in IEEE 802.11 WLANs

In this paper, an optimal CW (Contention Window) synchronization scheme is proposed in IEEE 802.11 WLANs. IEEE 802.11 WLANs operates with DCF (Distributed Coordination Function) mode for the MAC (Medium Access Control). In DCF, CW becomes the minimum CW according to the success of data transmissions and increases exponentially due to the collisions. In this situation, the smaller value of the minimum CW can increase the collision probability because stations have higher opportunity to access the medium. On the other hand, the higher value of the minimum CW will delay the transmission, which can result in the network performance degradation. In IEEE 802.11, since the base minimum CW value is a fixed value depending on the hardware or standard, it is difficult to provide the optimal network performance that can be determined by the flexible CW value according to the number of active stations. In addition, the synchronization of optimal CW is required among mobile stations to adapt the network parameters. Especially for the newly joined stations such as moving or turning on stations, they need to adapt the minimum CW value to get the optimal network performance. The shorter the adaptation time is, the better the network performance can maintain. Therefore, in this paper, AP (Access Point) calculates the optimal CW and shares it with mobile stations using beacon and probe response messages for the fast CW synchronization. Extensive simulation results show that the proposed scheme outperforms the previous schemes in terms of the network throughput and adaptation time. Â

Adaptive Contention Window MAC Protocol in a Global View for Emerging Trends Networks

Massive tremendous amount of miniaturized wireless Internet of Things (IoT) devices are widely employed in many fields such as industrial production, social life, public (and defense) security and management of human society. The limitation of node device's energy capacity is the bottleneck issue of these network systems. MAC protocol is a key communication protocol for such sensor nodes which both rationally saves energy (an alternative to energy harvesting way) and improves the performances of the wireless sensor networks. There are complex tradeoff optimization relationships between the size of contention window and energy consumption, delay and collision, in which too large or too small contention window value cannot make the network performance optimal. This paper firstly gives an optimization algorithm for the size of the contention window through theoretical analysis, which can achieve a compromise between energy consumption (i.e. alternative energy harvesting) and delay. Then, a global view based adaptive contention window (GV-ACW) MAC protocol is proposed to further reduce latency and improve alternative energy harvesting. The GV-ACW MAC protocol adopts the optimized size of contention window in the near sink area to meet the functional requirements of data forwarding, while in the far sink area, the size of contention window is larger than it required by node for data transmission so as to reduce the latency and thereby improve the network performance as a whole. The theoretical analysis and experimental results show that, comparing with previous MAC protocol, GV-ACW protocol can realize effective alternative energy harvesting which resulting increasement of the network lifetime by 6% and reduce the network delay by 15%.

Contention Resolution in Wi-Fi 6-Enabled Internet of Things Based on Deep Learning

Internet of Things (IoT) is expected to vastly increase the number of connected devices. As a result, a multitude of IoT devices transmit various information through wireless communication technology, such as the Wi-Fi technology, cellular mobile communication technology, low-power wide-area network (LPWAN) technology. However, even the latest Wi-Fi technology is still ready to accommodate these large amounts of data. Accurately setting the contention window (CW) value significantly affects the efficiency of the Wi-Fi network. Unfortunately, the standard collision resolution used by IEEE 802.11ax networks is nonscalable; thus, it cannot maintain stable throughput for an increasing number of stations, even when Wi-Fi 6 has been designed to improve performance in dense scenarios. To this end, we propose a CW control strategy for Wi-Fi 6 systems. This strategy leverages deep learning to search for optimal configuration of CW under different network conditions. Our deep neural network is trained by data generated from a Wi-Fi 6 simulation system with some varying key parameters, e.g., the number of nodes, short interframe space (SIFS), distributed interframe space (DIFS), and data transmission rate. Numerical results demonstrated that our deep learning scheme could always find the optimal CW adjustment multiple by adaptively perceiving the channel competition status. The finalized performance of our model has been significantly improved in terms of system throughput, average transmission delay, and packet retransmission rate. This makes Wi-Fi 6 better adapted to the access of a large number of IoT devices.

A Testbed System For Impact of QoS Parameter in Wireless ad Hoc Network

In our paper, we evaluate the impact of some QoS parameters on multimedia data in IEEE 802.11 wireless networks by deploying an experimental testbed systems. The evaluation results show that Contention Window (CW) value has a great influence on the throughput ratio between multimedia data types.

Fair Adaptive Cross-Layer Resource Allocation Scheme for IEEE 802.16 Broadband Wireless Networks

In a WiMAX network, the Medium Access Control (MAC) protocol deals with resource allocation to different types of traffic. The key components that ensure Quality of Service (QoS) guarantees in a WiMAX network include Call Admission Control (CAC), Bandwidth and Burst allocation. In this Paper, a Cross-layer framework is designed to efficiently allocate resources to various classes of traffic. CAC and Bandwidth allocation are dealt in the MAC layer, while Burst allocation in the PHYsical layer. The predominant goal of this work is to reduce delay and Information Element (IE) overheads by efficiently utilizing the available frame space. The History based CAC (HCAC) proposed in this paper deals with call acceptance based on the Contention Window (CW) values. The History based Bandwidth Allocation (HBA) scheme deals with allocating bandwidth based on Consumption and Equity measures. The proposed tightly coupled Delay Tolerance based Scheduler (DTS) and Bucket based Burst Allocator (BBA) allocate resources by prioritizing flows with least delay tolerance. It is seen that the proposed schemes offer better performance in contrast to the existing benchmarked schemes in terms of Throughput, Average Delay and Packet Loss Ratio (PLR).

An accurate and complete performance modeling of the IEEE 802.11p MAC sublayer for VANET

This paper proposes an analytical model for the throughput, channel access delay, and queueing delay of the IEEE 802.11p enhanced distributed channel access (EDCA) mechanism in the medium-access control (MAC) sublayer. In order to make the proposed analytical model explicitly solvable and to avoid computation complexity caused by most of existing 3-D or 4-D Markov-chain-based analytical models, a combination of 2-D and 1-D Markov chain model is used. The 2-D Markov chain is established to model the backoff procedure of each access category (AC) queue, deriving a relationship between the transmission probability and collision probability for each AC queue. Afterwards, a 1-D discrete-time Markov chain is established to model the contention period caused by the distinction of four different arbitration inter-frame space (AIFS) and contention window (CW) values, deriving another relationship between the transmission probability and collision probability of each AC queue. In order to consider both saturated and non-saturated cases, an infinite-long 1-D Markov chain model is used. In the proposed analytical model, all the features in the EDCA such as different CW and AIFS for each AC, various saturation status, internal collision, backoff counter freezing, up-to-date standard parameters, and initial-carrier-sensing procedure are taken into consideration. Based on the two Markov models, we further derive performance models which describe the relationships between the network parameters and channel access performance metrics in terms of normalized throughput, channel access delay, and queueing delay, respectively. The proposed analytical model applies to both basic access mode and request-to-send/clear-to-send (RTS/CTS) access mode, and is suitable for four access categories of traffic in the IEEE 802.11p. The proposed model can be employed to analyze the performance of real-world vehicular network. Simulation results are shown to verify the accuracy and effectiveness of the proposed analytical model.

The analysis of IEEE 802.11 DCF protocol based on LEO satellite Wi-Fi network

Aiming at the problems of traditional IEEE 802.11 DCF protocol applied to LEO satellite Wi-Fi network, the influence of propagation delay, hidden terminal and user collision on the throughput of MAC layer is fully analysed, and a specific scheme is proposed to adjust the ACK Timeout and the minimum contention window value. The improved two-dimensional Markov model has been used to analyse the DCF protocol throughput theoretically. By using MATLAB simulation, it is verified that the throughput performance is directly related to the transmission probability, and throughput performance is negative correlated with the number of nodes and transmission distance.

QoS supported adaptive and multichannel MAC protocol in vehicular ad-hoc network

Based on IEEE 802.11p and IEEE 1609.4 protocols, vehicular ad hoc network (VANETs) transmit safety and non-safety packets through multichannel. Due to the increase in usage of various infotainment applications, the quality-of-service (QoS) is not met in VANETs resulting in high congestion over transmission. To ensure QoS in safety, transport efficiency and infotainment applications, we proposed a multichannel approach with optimal minimum contention window (CW) technique named as reinforcement learning and multichannel MAC protocol (RL- M -MAC). In this paper, an algorithm is proposed to select the channel for transmission. Proposed RL-M-MAC protocol uses conditional Markov chain technique to identify the optimal CW value. Theoretical performance analysis and extensive simulation results shows that RL-M-MAC protocol can support QoS services with lower collision probability, higher throughput, and high fairness.

Estimation of probabilistic processes in wireless networks of 802.11 standard

The article analyzes mechanisms of collision in a wireless 802.11 network with competitive access to a radio channel. The calculated relationships for determining the probabilities of collisions in the network as a whole in the presence of N active stations with a saturated load, and also for one station when implementing the binary exponential mechanism of increasing the competitive window are presented. The graphs, which illustrate the proposed equations, are given in this article too. An equation is also proposed for determining the probability of successful transmission of a data frame depending on the number of active stations and the initial value of the competitive window. The equations are obtained using the concept of a virtual competitive window.It was shown that in the case, where the number of active stations is one third of the contention window, the probability of collisions is about 0.25. This means that in the network with such number of active stations, each station will experience the collision at every fourth attempt to transmit a frame of data in average. The next attempt to transmit frame of data will be carried out by using the larger contention window. Collisions will cause the increase of transmitting time duration and its irregularity.It was analyzed the efficacy of application of binary exponential law for the change of the contention window for active stations, caught in a conflict when trying to access the channel.The equation for estimate the changes in the probability of collision and the number of competing stations in the access cycle was obtained by taken into account that it will take place when a quasi-stationary mode of operation of wireless networks is established. It was shown that the most effectively this mechanism is triggered in the early stages of repeated access to radio channel. Those stations that carry out the 5-th and 6-th attempts to access channel have a little impact on the probability of collisions on the network. Such result may be explained because every station after successful transmit the data frame will begin a new attempt from the initial meaning of contention window. So, if the initial number of active stations in the wireless network approximately equal to the value of contention window, in steady state of saturated network the effective number of active stations will be twice less due to application of binary exponential law for the change of the competitive window. If the initial number of active stations will be only 30% from the value of contention window, the effective number of active stations will be less twice too.It was gave the estimation of the overall probability of collisions in a saturated 802.11 network with competitive access to the radio channel. The threat of collisions increases quickly in comparison with the increase of number of active stations in the networkFrom the analysis of the received equations and graphs it follows that for the normal operation of the wireless network, it is necessary that the number of active stations that simultaneously compete for access to the radio channel does not exceed a third of the initial value of the contention window used in this network. In this case, the probability of successful transmission will be more than 0.85.Ref. 10, fig. 7.

Mitigating tail latency in IEEE 802.11–based networks

SummaryDelay sensitive applications are being actively introduced with the advent of 5G and vehicular communications, and such applications are very sensitive to tail latency. However, tail latency has not been seriously considered so far, especially in IEEE 802.11–based networks. Channel access is scheduled by random Contention Window (CW) values in IEEE 802.11–based networks, and the node with the larger CW waits longer, and it may even observe multiple transmissions from a single contending node, which results in a long latency tail. In this paper, we propose a new decentralized MAC called SynchMAC to mitigate this latency tail. In SynchMAC, every competing node transmits exactly one packet within a virtual time slot without a centralized controller. Using the proposed approach, the maximum channel access latency is bounded by T×2N, where T is the time required for transmitting a single packet (including Inter‐Frame Space and CW) and N is the number of competing nodes. To maximize the system throughput, the proposed scheme optimizes the value of T by considering the probability of successful transmission. Our simulation study shows that SynchMAC reduces the maximum access latency by up to 94% and 53% compared with the conventional IEEE 802.11 MAC and the comparative scheme, respectively, without degrading throughput performance. We also show that SynchMAC is easily extended to support weighted access.