Binary Exponential Backoff Mechanism Research Articles

Multiaccess Point Coordination for Next-Gen Wi-Fi Networks Aided by Deep Reinforcement Learning

Wi-Fi in the enterprise - characterized by overlapping Wi-Fi cells - constitutes the design challenge for next-generation networks. Standardization for recently started IEEE 802.11be (Wi-Fi 7) Working Groups has focused on significant medium access control layer changes that emphasize the role of the access point (AP) in radio resource management (RRM) for coordinating channel access due to the high collision probability with the distributed coordination function (DCF), especially in dense overlapping Wi-Fi networks. This paper proposes a novel multi-AP coordination system architecture aided by a centralized AP controller (APC). Meanwhile, a deep reinforcement learning channel access (DLCA) protocol is developed to replace the binary exponential backoff mechanism in DCF to enhance the network throughput by enabling the coordination of APs. First-Order Model-Agnostic Meta-Learning further enhances the network throughput. Subsequently, we also put forward a new greedy algorithm to maintain proportional fairness (PF) among multiple APs. Via the simulation, the performance of DLCA protocol in dense overlapping Wi-Fi networks is verified to have strong stability and outperform baselines such as Shared Transmission Opportunity (SH-TXOP) and Request-to-Send/Clear-to-Send (RTS/CTS) in terms of the network throughput by 10% and 3% as well as the network utility considering proportional fairness by 28.3% and 13.8%, respectively.

Sliding Group Window with Rebacking off for Collision Avoidance in High-Efficiency Wireless Networks

It is difficult for wireless local area networks (WLANs), IEEE 802.11ax high-efficiency WLAN (HEW), to join next-generation innovations such as 5th generation (5G) and Internet of Things (IoT) because they still have their conventional channel access mechanism as their essential medium access control (MAC) protocol. The MAC protocol uses a traditional binary exponential backoff (BEB) algorithm to access channel resources that depend on the noncognitive increment of contention parameters for collision avoidance. In BEB, the collision issue increases with the increase in connected devices in the network due to a fixed contention window size. The larger the size of the network, the larger the collision in the network. To avoid such a circumstance, in this paper, we propose a sliding group window (sGW) mechanism dependent on collision-point assessment in order to improve the performance of MAC protocol for HEW. The proposed algorithm additionally presents a rebacking off for collision avoidance (ReBOCA) system for sGW, which combines the uniform dispersion of the contention parameters. This variation of an ordinary backoff algorithm permits the reasonable sliding of the user groups in the case of collision. The algorithm explicitly accounts for the peculiarities of dense environments and backward compatibility. Key aspects of the proposed solution include collision-point estimation, rebacking off for collision distribution convergence for fair treatment, and adaptive sliding of group windows to mitigate contention unfairness. We further formulated a closed-form Markov chain model for the performance analysis of our proposed sGW with ReBOCA scheme. Theoretical and practical results prove that our proposed scheme achieved maximal efficiency, even under dense environments. An increase in throughput with a lower packet collision probability was achieved with the proposed mechanism, and the efficiency increased as the number of contending stations increased than compared to traditional BEB performance. Our proposed ReBOCA mechanism enhanced network throughput by 38.18% than compared to the conventional BEB mechanism.

Optimization Method of Adaptive Backoff and Duty Cycle for S-MAC Protocol in Wireless Sensor Networks

As a matter of fact that the network traffic has a great influence on the binary exponential backoff mechanism, duty cycle mechanism, and fixed transmission power mechanism adopted by the Sensor Medium Access Control (S-MAC) protocol. The paper proposes an Adaptive Backoff and Duty Cycle for S-MAC protocol (ABDC-SMAC). In the backoff mechanism, considering the failure times of channel competitions, the length of buffer queue, and the node residual energy across the board, a cross-control backoff mechanism is proposed. In the duty cycle mechanism, the network traffic is judged by the average network flow factor. Based on the average network flow factor, the value of duty cycle can change around its initial value. In the power control mechanism, the minimum transmission power can be obtained by the Friis formula. At the same time, the exponential formula following the change of network traffic is selected and multiplied by the minimum transmission formula. The simulation results show that the performance of proposed ABDC-SMAC protocol is improved obviously on energy consumption and transmission delay.

Performance optimization of QoS-supported dense WLANs using machine-learning-enabled enhanced distributed channel access (MEDCA) mechanism

Quality of service (QoS) implementation in a wireless local area network (WLAN) enables the prediction of network performance and utilization of effective bandwidth for multimedia applications. In QoS-supported WLAN, enhanced distributed channel access (EDCA) adjusts back-off parameters to implement priority-based channel access at the medium access control (MAC) layer. Although conventional QoS-supported EDCA in WLANs can provide a certain degree of QoS guarantee, the performance of best effort data (low-priority) traffic is sacrificed owing to the blind use of a binary exponential back-off (BEB) mechanism for collision avoidance among WLAN stations (STAs). In EDCA, the BEB mechanism exponentially increases the contention window (CW[AC]) for any specific priority access category (AC) when collision occurs and resets it to its initial size after successful data transmission. This increase and reset of CW[AC] is performed regardless of the network density inference, i.e., a scarce WLAN does not require an unnecessary exponential increase in CW[AC]. Similarly, a dense WLAN causes more collisions if CW[AC] is reset to its initial minimum size. Machine-learning algorithms can scrutinize an STA’s experience for WLAN inference. Therefore, in this study, we propose a machine-learning-enabled EDCA (MEDCA) mechanism for QoS-supported MAC layer channel access in dense WLANs. This mechanism utilizes a Q-learning algorithm, which is one of the prevailing models of machine learning, to infer the network density and adjust its back-off CW[AC] accordingly. Simulation results show that MEDCA performs better as compared to the conventional EDCA mechanism in QoS-supported dense WLANs.

Cognitive backoff mechanism for IEEE802.11ax high-efficiency WLANs

Carrier sense multiple access with collision avoidance(CSMA/CA) in current IEEE 802.11 wireless local area networks (WLANs) uses a uniformly distributed binary exponential backoff (BEB) mechanism that is mainly based upon exponential increases of the contention window (CW) to avoid repeated collisions. After each consecutive collision, the CW is doubled until it reaches the maximum value. Under dense conditions, however, the blind selection of the CW greatly reduces throughput, whereas under sparse conditions with smaller number of contending stations, the blind exponential increase of the CW for collision avoidance causes unnecessarily long delays. Therefore, it fails to achieve high efficiency in both dense and sparse environments with the current BEB mechanism. In this paper, we propose a cognitive backoff (CB) mechanism that adaptively determines the CW to provide efficient collision avoidance with high throughput and low delay under both dense and sparse conditions. In the proposed CB mechanism, the measured conditional collision probability and the number of backoff stages determine the CW. A performance analysis with an event-driven simulator, NS3, reveals that the proposed CB can achieve higher throughput and lower delay than the BEB, without much implementation complexity while preserving fairness.

A Differentiated Reservation MAC Protocol for Achieving Fairness and Efficiency in Multi-Rate IEEE 802.11 WLANs

This paper focuses on designing a medium access control and channel usage algorithm in multi-rate wireless local area networks for improving the efficiency and fairly sharing channel resources among the contending nodes. Aiming for the problems that the high collision is often caused by binary exponential backoff mechanism in the legacy IEEE 802.11 and the shared channel can be overused by low bitrate nodes, we propose a differentiated reservation (DR) algorithm to reduce the collision among the contending nodes by setting their backoff counter as a deterministic value once accessing successfully to the channel. Furthermore, to eliminate the performance anomaly, some nodes are permitted to send multiple packets in one transmission opportunity according to their feature. Moreover, we present the implementation of the DR algorithm that is readily applied to both the existing 802.11 DCF and 802.11e EDCA networks with minimum modification. In addition, we also investigate the limitation of the DR algorithm and propose a group-based differentiated reservation (GDR) algorithm applied to high dense scenarios. The results of the theoretical analysis and simulation validate that our proposed algorithms (DR and GDR) can obtain high throughput, good airtime fairness, and low collision rate.

Channel observation‐based scaled backoff mechanism for high‐efficiency WLANs

A channel observation-based scaled backoff (COSB) mechanism for the carrier sense multiple access with collision avoidance of high efficiency wireless local area networks (WLANs) is devised. The proposed protocol modifies the blind scaling of contention window (W) in binary exponential backoff (BEB) scheme of currently deployed WLANs. COSB is employed to adaptively scale-up and scale-down the W size during the backoff mechanism for collided and successfully transmitted data frames, respectively. It can achieve higher throughput and shorter delay compared to the conventional BEB mechanism in highly dense WLANs.

A Self-Scrutinized Backoff Mechanism for IEEE 802.11ax in 5G Unlicensed Networks

The IEEE 802.11ax high-efficiency wireless local area network (HEW) is promising as a foundation for evolving the fifth-generation (5G) radio access network on unlicensed bands (5G-U). 5G-U is a continued effort toward rich ubiquitous communication infrastructures, promising faster and reliable services for the end user. HEW is likely to provide four times higher network efficiency even in highly dense network deployments. However, the current wireless local area network (WLAN) itself faces huge challenge of efficient radio access due to its contention-based nature. WLAN uses a carrier sense multiple access with collision avoidance (CSMA/CA) procedure in medium access control (MAC) protocols, which is based on a binary exponential backoff (BEB) mechanism. Blind increase and decrease of the contention window in BEB limits the performance of WLAN to a limited number of contenders, thus affecting end-user quality of experience. In this paper, we identify future use cases of HEW proposed for 5G-U networks. We use a self-scrutinized channel observation-based scaled backoff (COSB) mechanism to handle the high-density contention challenges. Furthermore, a recursive discrete-time Markov chain model (R-DTMC) is formulated to analyze the performance efficiency of the proposed solution. The analytical and simulation results show that the proposed mechanism can improve user experience in 5G-U networks.

A Multi-Priority Service Differentiated and Adaptive Backoff Mechanism over IEEE 802.11 DCF for Wireless Mobile Networks

Backoff mechanism serves as one of the key technologies in the MAC-layer of wireless mobile networks. The traditional Binary Exponential Backoff (BEB) mechanism in IEEE 802.11 Distributed Coordination Function (DCF) and other existing backoff mechanisms poses several performance issues. For instance, the Contention Window (CW) oscillations occur frequently; a low delay QoS guarantee cannot be provided for real-time transmission, and services with different priorities are not differentiated. For these problems, we present a novel Multi-Priority service differentiated and Adaptive Backoff (MPAB) algorithm over IEEE 802.11 DCF for wireless mobile networks in this paper. In this algorithm, the backoff stage is chosen adaptively according to the channel status and traffic priority, and the forwarding and receding transition probability between the adjacent backoff stages for different priority traffic can be controlled and adjusted for demands at any time. We further employ the 2-dimensional Markov chain model to analyze the algorithm, and derive the analytical expressions of the saturation throughput and average medium access delay. Both the accuracy of the expressions and the algorithm performance are verified through simulations. The results show that the performance of the MPAB algorithm can offer a higher throughput and lower delay than the BEB algorithm.

An adaptive contention slot selection mechanism for improving the performance of IEEE 802.11 DCF

In IEEE 802.11 distributed coordination function (DCF) standard, binary exponential back-off (BEB) mechanism is used to perform collision avoidance. And, contention slot selection (CSS) distribution function of the BEB mechanism plays a prominent role in the DCF performance. In this paper, therefore, we have proposed an adaptive BEB mechanism, named as adaptive contention slot selection-based binary exponential back-off (ACSSB). This mechanism selects slots for back-off timer based on the number of competing stations in order to enhance the performance of the DCF. The proposed mechanism differs from the standard back-off mechanism by choosing the back-off timer in accordance to a non-uniform probability distribution function in the contention window (CW) interval. However, CW reset/expansion method used in proposed mechanism is the same as in standard back-off rule. Simulation results demonstrate that the ACSSB mechanism outperforms the earlier schemes, especially when there is large number of competing stations.

An adaptive contention slot selection mechanism for improving the performance of IEEE 802.11 DCF

In IEEE 802.11 distributed coordination function (DCF) standard, binary exponential back-off (BEB) mechanism is used to perform collision avoidance. And, contention slot selection (CSS) distribution function of the BEB mechanism plays a prominent role in the DCF performance. In this paper, therefore, we have proposed an adaptive BEB mechanism, named as adaptive contention slot selection-based binary exponential back-off (ACSSB). This mechanism selects slots for back-off timer based on the number of competing stations in order to enhance the performance of the DCF. The proposed mechanism differs from the standard back-off mechanism by choosing the back-off timer in accordance to a non-uniform probability distribution function in the contention window (CW) interval. However, CW reset/expansion method used in proposed mechanism is the same as in standard back-off rule. Simulation results demonstrate that the ACSSB mechanism outperforms the earlier schemes, especially when there is large number of competing stations.

A backoff algorithm based on self-adaptive contention window update factor for IEEE 802.11 DCF

The binary exponential backoff (BEB) mechanism is applied to the packet retransmission in lots of wireless network protocols including IEEE 802.11 and 802.15.4. In distributed dynamic network environments, the fixed contention window (CW) updating factor of BEB mechanism can't adapt to the variety of network size properly, resulting in serious collisions. To solve this problem, this paper proposes a backoff algorithm based on self-adaptive contention window update factor for IEEE 802.11 DCF. In WLANs, this proposed backoff algorithm can greatly enhance the throughput by setting the optimal CW updating factor according to the theoretical analysis. When the number of active nodes varies, an intelligent scheme can adaptively adjust the CW updating factor to achieve the maximal throughput during run time. As a result, it effectively reduces the number of collisions, improves the channel utilization and retains the advantages of the binary exponential back-off algorithm, such as simplicity and zero cost. In IEEE 802.11 distributed coordination function (DCF) protocol, the numerical analysis of physical layer parameters show that the new backoff algorithm performance is much better than BEB, MIMD and MMS algorithm.

A Simple but Effective Collision and Error Aware Adaptive Back-Off Mechanism to Improve the Performance of IEEE 802.11 DCF in Error-Prone Environment

In a realistic wireless network, all the unsuccessful transmission attempts are not due to packet collisions only. But the transmission errors also played an important role because of the non-ideal channel conditions. In addition, non-saturation condition for a contending station is also a realistic phenomenon. It is now very established fact that performance of the distributed coordination function (DCF) significantly degrades in non-ideal situations due to the traditionally fixed behavior of its binary exponential back-off (BEB) mechanism. To enhance the performance of the DCF, many adaptive back-off mechanisms have been suggested. However, these mechanisms still suffer due to inefficient adaptation procedure followed by them. In order to overcome such inefficiencies, in this paper, we propose an effective contention window (CW) and contention slot selection (CSS) mechanism, called Collision and Error Aware Adaptive Back-off (CEAAB), to improve the performance of IEEE 802.11 DCF. In the proposed CEAAB mechanism, CW and CSS strategies differ from the BEB back-off mechanism to adopt the network situation. A Markov chain based analytical model is developed for the proposed CEAAB mechanism to derive the performance metrics-throughput and delay. Simulation results illustrate that the CEAAB mechanism outperforms the earlier proposed mechanisms.

A Simple but Effective Contention Aware and Adaptive Back-off Mechanism for Improving the Performance of IEEE 802.11 DCF

In IEEE 802.11 standard, Distributed Coordination Function (DCF) is used as a primary medium access mechanism to share the common wireless medium. It is now well established that performance of the DCF degrades, especially when there is a large number of stations in the network contending for the wireless medium. This occurs due to the traditional parameter setting of its Binary Exponential Back-off (BEB) mechanism, which is used for collision avoidance. Therefore, in this paper, we propose an effective Contention Window (CW) and Contention Slot Selection (CSS) mechanism, named Contention Aware and Adaptive Back-off (CAAB) mechanism, to enhance performance of the IEEE 802.11 DCF. This mechanism differs from the standard back-off mechanism in two ways. First, contention window is not reset after successful transmission. Instead, stations will be allowed to go back to the possible preceding back-off stage after successful packet transmission in order to maintain the CW selection as a continuous process. Second, back-off timer is also not uniformly chosen in the respective CW interval. Instead to it, a non-uniform CSS distribution is used to select back-off timer in order to make the selection process adaptive according to the contention level. A Markov chain model is developed to derive the throughput and delay performance of the DCF based on CAAB mechanism. Finally, performance of our mechanism is evaluated with respect to the BEB and Double Increment Double Decrement mechanisms. Simulation results show that the proposed mechanism outperforms the referenced mechanisms in almost each count.

EARC: Enhanced Adaptation of Link Rate and Contention Window for IEEE 802.11 Multi-Rate Wireless Networks

IEEE 802.11 wireless network supports multiple link rates at the physical layer. Each link rate is associated with a certain required Signal-to-Interference-and-Noise Ratio (SINR) threshold for successfully decoding received packets. On transmission failures, the 802.11 DCF performs a binary exponential backoff mechanism to discourage channel access attempts, hoping to reduce congestion. When traditional link adaptation is applied, both rate reduction and binary backoff represent double penalties for this wireless link, which may cause overly conservative transmission attempts. On the other hand, once transmission succeeds, 802.11 DCF resets the backoff contention window to the minimum value to encourage channel access attempts. At the same time, traditional link adaptation may also decide to increase the data rate, which leads to overly aggressive transmission attempts. We observe this improper interaction of link rate and backoff mechanism that harms the 802.11 system performance, due to separate consideration of those two parameters. In this paper, we propose to jointly adapt the rate and backoff parameters. Specifically, an Enhanced Adaptation of link Rate and Contention window, abbreviated as EARC, is devised. EARC is a closed-loop (receiver-assisted) link rate adaptation protocol that jointly considers the backoff mechanism. With only one extra byte carried by the DATA packet, EARC incurs little controlling overhead despite its receiver-assisted nature. Moreover, since SINR information commonly utilized by receiver-assisted protocols is not precisely supported in real devices, we introduce a rate selection reference (RSR) table empirically derived by constantly monitoring the environmental energy level and reception behavior. The RSR table then guides the receiver to select the best sustainable rate for the transmitter. Simulation results demonstrate the RSR table is a practical option for making the rate decision, and the proposed EARC approach is effective in maintaining high system throughput, compared to other link adaptation algorithms.

Fair Coexistence MAC Protocol for Contention-Based Heterogeneous Networks

This paper proposes a contention-based fair coexistence mechanism among heterogeneous networks that have different transmission power and/or coverage. First, we show that the existing carrier sensing multiple access (CSMA) mechanism, that is a prevailing contention-based protocol, results in significant unfairness in channel access when heterogeneous networks coexist; a system with lower transmission power hardly occupies the shared channel due to interference from a system with higher transmission power. We analyze the causes of unfairness in terms of (i) the asymmetry of carrier sensing and (ii) the blindness of binary exponential backoff mechanism and the link adaptation mechanism, and we derive an analytical model of per-system throughput to investigate the effects of these causes. To resolve this problem, we propose a fair coexistence CSMA protocol consisting of access etiquette and interference-aware backoff. The former adaptively controls the contention window size so that the high-power system allows transmission opportunities to the low-power system in a fair and efficient manner. The latter differentiates between the response to transmission failure caused by collision and the response to failure caused by interference. The simulation results confirm that the proposed scheme effectively mitigates the unfairness of channel sharing while attaining high spectral efficiency.

Throughput analysis of the IEEE 802.11 distributed coordination function considering erroneous channel and capture effects

This paper presents a performance study of the distributed coordination function (DCF) of 802.11 networks considering erroneous channel and capture effects under non-saturated traffic conditions employing a basic access method. The aggregate throughput of a practical wireless local area network (WLAN) strongly depends on the channel conditions. In a real radio environment, the received signal power at the access point from a station is subjected to deterministic path loss, shadowing, and fast multipath fading. The binary exponential backoff (BEB) mechanism of IEEE 802.11 DCF severely suffers from more channel idle time under high bit error rate (BER). To alleviate the low performance of IEEE 802.11 DCF, a new mechanism is introduced, which greatly outperforms the existing methods under a high BER. A multidimensional Markov chain model is used to characterize the behavior of DCF in order to account both non-ideal channel conditions and capture effects.

An Efficient Medium Access Control Protocol for under water Acoustic Sensor Network

a terrestrial wireless communication which uses radio waves, underwater communication relies on acoustic waves. The long latency and limited bandwidth pose great challenges in Underwater Media Access Control (MAC) design. So this paper proposes a new MAC protocol for wireless sensor acoustic network which are adaptable to underwater environment. This new protocol is based on the classic MACA to avoid hidden and exposed node problem. It also address the fragmentation issue, instead of sending a large packet it proposes to send fragmented packets to improve the throughput of the network. It introduces a new binary exponential back-off mechanism to reduce the possibilities of collision and hence to improve the throughput. The simulation result of the proposed protocol shows that its performance is better than the other MAC protocol. The simplicity and throughput stability of proposed MAC make it an appropriate reference MAC protocol.

On the Design of Opportunistic MAC Protocols for Multihop Wireless ; Networks with Beamforming Antennas

Beamforming antennas promise a significant increase in the spatial reuse of the wireless medium when deployed in multihop wireless networks. However, existing directional Medium Access Control (MAC) protocols with the default binary exponential backoff mechanism are not capable of fully exploiting the offered potential. In this paper, we discuss various issues involved in the design of MAC protocols specific for beamforming antennas. Based on our discussion, we argue that the traditional binary exponential backoff mechanism limits the possible spatial reuse and aggravates some beamforming-related problems such as deafness and head-of-line blocking. To grasp the transmission opportunities offered by beamforming antennas, we design an Opportunistic Directional MAC (OPDMAC) protocol for multihop wireless networks. The OPDMAC protocol employs a novel backoff mechanism in which the node is not forced to undergo idle backoff after a transmission failure but can rather take the opportunity of transmitting other outstanding packets in other directions. This mechanism minimizes the idle waiting time and increases the channel utilization significantly and thereby enables OPDMAC to enhance the spatial reusability of the wireless medium and reduce the impact of the deafness problem without additional overhead. Through extensive simulations, we demonstrate that OPDMAC enhances the performance in terms of throughput, delay, packet delivery ratio, and fairness. To further improve its performance, we discuss and evaluate the benefits of carefully choosing some protocol parameters instead of using the default values commonly used by other directional MAC protocols.

Performance analysis of bandwidth requests under unicast, multicast and broadcast pollings in IEEE 802.16d/e

In the polling mode in IEEE 802.16d/e, one of three modes: unicast, multicast and broadcast pollings, is used to reserve bandwidth for data transmission. In the unicast polling, the BS polls each individual MS to allow to transmit a bandwidth request packet, while in the multicast and broadcast pollings, the truncated binary exponential backoff (TBEB) mechanism is adopted as a contention resolution among mobile stations (MSs) in a multicast or broadcast group. This paper investigates the delay of bandwidth requests in the unicast, multicast and broadcast pollings, by deriving the delay distribution of the unicast polling and the TBEB by means of analytical methods. We consider an error-free channel as well as an error-prone channel with i.i.d. constant packet error rate per frame. Furthermore, we find the utilization of transmission opportunity to see efficiency of the bandwidth in the TBEB. Performance evaluations are provided to show that analytical results are well-matched with simulations. By the numerical results, we can find the optimal parameters such as the initial backoff window size of the TBEB and the number of transmission opportunities (or slots) satisfying quality of service (QoS) requirement on delay and loss, and thus we can determine which scheme is better than others depending on the probability of a request arrival during one frame. Numerical examples address that the TBEB performs better than the unicast polling for light traffic loads and vice versa for heavy traffic loads. Also, it is shown that the multicast polling has better performance than the broadcast polling in the sense of shorter delay, lower loss probability and higher utilization of transmission opportunity.