• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.1035-1048
• /
• 2023

The IEEE 802.11 WLAN adopts a random backoff algorithm for its collision avoidance mechanism, and it is well known that the contention-based algorithm may suffer from performance degradation especially in congested networks. In this paper, we design an efficient backoff algorithm that utilizes a reinforcement learning method to determine optimal values of backoffs. The mobile nodes share a common contention window (CW) in our scheme, and using a Q-learning algorithm, they can avoid collisions by finding and implicitly reserving their optimal time slot(s). In addition, we introduce Frame Size Control (FSC) algorithm to minimize the possible degradation of aggregate throughput when the number of nodes exceeds the CW size. Our simulation shows that the proposed backoff algorithm with FSC method outperforms the 802.11 protocol regardless of the traffic conditions, and an analytical modeling proves that our mechanism has a unique operating point that is fair and stable.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.334-349
• /
• 2022

The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CW_Threshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.4A
• /
• pp.329-336
• /
• 2011

This paper addresses the fairness issue between uplink and downlink traffic in IEEE 802.11 WLANs. Some solutions in existing work try to solve this issue by giving smaller minimum contention window (CWmin) value to an AP compared to stations. In contrast to the existing solutions, a proposed algorithm in this paper aims at finding CWmin values that not only provides fairness between uplink and downlink traffic among stations but also achieves high throughput. For this, in the proposed algorithm, an AP checks the number of stations that have uplink and downlink traffic, respectively. Based on this information, the AP calculates optimal CWmin values and announces it to stations. Our simulation results show that the proposed algorithm outperforms existing algorithms in terms of fairness and throughput.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.1B
• /
• pp.15-20
• /
• 2012

In this paper, an algorithm that enhances the conventional directional CSMA/CA protocol in IEEE 802.15.3c is proposed under saturation environments. For the algorithm, a Markov chain model is presented and analyzed in no-ACK mode. The effects of directional antennas and the features of IEEE 802.15.3c MAC are considered in the model. The optimal sizes of contention window are derived from the numerical results. The numerical results show that the proposed directional CSMA/CA algorithm outperforms conventional one. The overall analysis is verified by simulation. The obtained results provide the criterion for selecting the optimal parameters and developing a MAC protocol that enhances the performance of mmWave WPANs.

• Journal of Communications and Networks
• /
• v.15 no.6
• /
• pp.606-613
• /
• 2013

This paper proposes a complete solution of a contention-based medium access control in wireless local networks to provide station level quality of service guarantees in both downstream and upstream directions. The solution, based on the mature distributed coordination function protocol, includes a new fixed contention window backoff scheme, a tuning procedure to derive the optimal parameters, a super mode to mitigate the downstream bottleneck at the access point, and a simple admission control algorithm. The proposed system guarantees that the probability of the delay bound violation is below a predefined threshold. In addition, high channel utilization can be achieved at the same time. The numerical results show that the system has advantages over the traditional binary exponential backoff scheme, including efficiency and easy configuration.

• Journal of Internet of Things and Convergence
• /
• v.6 no.4
• /
• pp.15-19
• /
• 2020

In this paper, we propose a optimal CW(Conention Window) synchronization scheme in IEEE 802.11 WLANs. IEEE 802.11 WLANs support DCF(Distributed Coordination Function) mode for the MAC(Medium Access Control) operation. In DCF, the CW increases exponentially according to the collisions and becomes minimum CW according to the success of data transmissions. However, since the base minimum CW value is hardware or standard specific, the number of active stations and network status are not considered to determine the CW value. Even though the researches on optimal CW have beend conducted, they do not consider the optimal CW synchronization among mobile stations which occur network performance degradation. Therefore, this paper calculates the optimal CW value and shares it with mobile stations in the network.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.6C
• /
• pp.483-491
• /
• 2012

In vehicle-to-vehicle (V2V) communications, each vehicle should periodically disseminate a beacon message including the kinematics information, such as position, speed, steering, etc., so that a neighbor vehicle can better perceive and predict the movement of the vehicle. However, a simple broadcasting of such messages may lead to a low reception probability as well as an excessive delay. In this paper, we attempt to analyze the impact of the following key parameters of the beacon dissemination on the performance of vehicular networks: beacon period, carrier-sensing range, and contention window (CW) size. We first derive a beacon period which is inversely proportional to the vehicle speed. Next, we mathematically formulate the maximum beacon load to demonstrate the necessity of the transmit power control. We finally present an approximate closed-form solution of the optimal CW size that leads to the maximum throughput of beacon messages in vehicular networks.

• Journal of information and communication convergence engineering
• /
• v.9 no.3
• /
• pp.341-346
• /
• 2011

Wireless sensor networks (WSNs) are formed by a great quantity of sensor nodes, which are consisted of battery-powered and some tiny devices. In WSN, both efficient energy management and Quality of Service (QoS) are important issues for some applications. Real-time services are usually employed to satisfy QoS requirements in critical environment. This paper proposes a real-time MAC (Medium Access Control) protocol with extended backoff scheme for wireless sensor networks. The basic idea of the proposed protocol employs (m,k)-firm constraint scheduling which is to adjust the contention window (CW) around the optimal value for decreasing the dynamic failure and reducing collisions DBP (Distant Based Priority). In the proposed protocol, the scheduling algorithm dynamically assigns uniform transmitting opportunities to each node. Numerical results reveal the effect of the proposed backoff mechanism.

• Journal of information and communication convergence engineering
• /
• v.19 no.1
• /
• pp.1-7
• /
• 2021

Reinforcement learning is an area of machine learning that studies how an intelligent agent takes actions in a given environment to maximize the cumulative reward. In this paper, we propose a new MAC protocol based on the Q-learning technique of reinforcement learning to improve the performance of the IEEE 802.11 wireless LAN CSMA/CA MAC protocol. Furthermore, the operation of each access point (AP) and station is proposed. The AP adjusts the value of the contention window (CW), which is the range for determining the backoff number of the station, according to the wireless traffic load. The station improves the performance by selecting an optimal backoff number with the lowest packet collision rate and the highest transmission success rate through Q-learning within the CW value transmitted from the AP. The result of the performance evaluation through computer simulations showed that the proposed scheme has a higher throughput than that of the existing CSMA/CA scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.10
• /
• pp.3458-3474
• /
• 2014

The performance of IEEE 802.11e enhanced distributed channel access (EDCA) is influenced by several interactive parameters that make quality of service (QoS) control complex and difficult. In EDCA, the most critical performance influencing parameters are the arbitration interframe space (AIFS) and contention window size (CW) of each access category (AC). The objective of this paper is to provide a scheme for parameter control such that the throughput per station as well as the overall system throughput of the network is maximized and controllable. For this purpose, a simple and accurate analytical model describing the throughput behavior of EDCA networks is presented in this paper. Based on this model, the paper further provides a scheme in which a Pareto optimal system configuration is obtained via an appropriate CW control for a given AIFS value, which is a different approach compared to relevant papers in the literature that deal with CW control only. The simulation results confirm the effectiveness of the proposed method which shows significant performance improvements compared to other existing algorithms.