Channel Access Scheme Research Articles

A Collision-Avoided MAC Protocol With Time Synchronization and Power Control for Underwater Sensor Networks

In recent years, there has been a great deal of interest in underwater sensor networks (UWSNs) because they can effectively monitor the submerged environment. However, due to the long delay, high bit error rate, and limited propagation bandwidth of underwater acoustic channels, the media access control (MAC) protocol cannot function effectively in underwater acoustic sensor networks, particularly in offshore waters. To solve these issues, an MAC protocol with time synchronization and power control (TSPC) is proposed for a particular scenario. In addition, the proposed protocol is a joint channel access scheme, and the central nodes are deployed on an offshore seabed, which can be used as a synchronization reference standard time. A power control strategy is also implemented to limit the communication range of nodes. In brief, integrating TSPC with layered concepts and distributed clustering algorithms can effectively prevent communication collisions and reduce the energy consumption of UWSNs. The simulation results indicate that the TSPC MAC protocol performs well with regard to packet transmission rate, synchronization error, collision-free operation, and energy consumption.

A Dueling Deep Recurrent Q -Network Framework for Dynamic Multichannel Access in Heterogeneous Wireless Networks

This paper investigates a deep reinforcement learning algorithm based on dueling deep recurrent Q -network (Dueling DRQN) for dynamic multichannel access in heterogeneous wireless networks. Specifically, we consider the scenario that multiple heterogeneous users with different MAC protocols share multiple independent channels. The goal of the intelligent node is to learn a channel access strategy that achieves high throughput by making full use of the underutilized channels. Two key challenges for the intelligent node are (i) there is no prior knowledge of spectrum environment or the other nodes’ behaviors; (ii) the spectrum environment is partially observable, and the spectrum states have complex temporal dynamics. In order to overcome the aforementioned challenges, we first embed the long short-term memory layer (LSTM) into the deep Q -network (DQN) to aggregate historical observations and capture the underlying temporal feature in the heterogeneous networks. And second, we employ the dueling architecture to overcome the observability problem of dynamic environment in neural networks. Simulation results show that our approach can learn the optimal access policy in various heterogeneous networks and outperforms the state-of-the-art policies.

Mutli-Link Channel Access Schemes for IEEE 802.11be Extremely High Throughput

Multi-link Operation (MLO) was introduced into 802.11be as a promising technology to improve throughput and provide Quality of Services (QoS) guarantees. In this article, we start by introducing the multi-link transmission issues for MLO. Particularly, we focus on the channel access issue, and we present the recently proposed channel access schemes in the latest 802.11 draft. More importantly, we propose the novel channel access schemes under the three different scenarios to increase the link utilization. Finally, we conduct simulations to demonstrate that the multi-link transmission can effectively improve the throughput performance.

Enabling the Internet of Bodies Through Capacitive Body Channel Access Schemes

The Internet of Bodies (IoB) is an imminent extension of the vast Internet of Things (IoT) domain, where wearable, ingestible, injectable, and implantable smart objects form a network in, on, and around the human body. The highly radiative nature of radio-frequency (RF) IoB devices unnecessarily extends the coverage range beyond the human body, which reduces energy efficiency, causes co-existence and interference issues, and exposes sensitive personal data to security threats. Alternatively, capacitive body channel communication (BCC) confine signal transmission to the human body to reduce signal leakage, experience less propagation loss, and reach pJ/b energy efficiency levels. Therefore, capacitive BCC is a key enabler to reach the ultimate design goals of ultra low power, high throughput, and small form-factor IoB devices. Albeit these attractive features, the communication and networking aspects of the capacitive BCC are not thoroughly explored yet. Therefore, this article proposes orthogonal and nonorthogonal capacitive body channel access schemes with or without cooperation among the IoB nodes. In order to address the Quality of Service (QoS) demand scenarios of different IoB applications, we present and formulate the max–min rate, max-sum rate, and QoS sufficient operational regimes, and then provide closed-form and numerical solution optimal power and phase time allocations. Extensive numerical results are analyzed to compare the performance of orthogonal and nonorthogonal schemes with and without cooperation for various design parameters under prescribed QoS regimes. The obtained results show that capacitive body channel access schemes can provide several Mb/s rates even at low transmission powers ranging between −60 and −90 dBm. Moreover, the cooperative schemes are shown to be effective to avoid performance degradation caused by increasing network size, low transmission power, and poor channel quality.

A proactive Medium Access Control (MAC) for finite-sized machine-to-machine (M2M) communication networks

In order to establish communication links among different communication devices or machines, the Medium Access Control (MAC) has to schedule the simultaneous transmissions by the contending nodes to constrain the probability of outage at each receiver. An efficient channel access scheme should be able to schedule the highest number of concurrent transmissions while being easy to implement with minimal coordination between the contending nodes.The existing MAC schemes provide network-wide solutions without adaptiveness, such as in existing guard zone-based solutions. On the other hand, an adaptive channel access scheme is proposed in this paper, which instead of declaring a network-wide fixed guard zone employs each interferer’s Transmitter–Receiver (Tx–Rx) separation to conclude its incorporation in the scheduled transmissions. The suggested scheme warrants the spatial separation among the scheduled links by suppressing the dominant interferers. The proposed MAC design functions approximately as good as the centralized, otherwise infeasible, joint scheduling and power control algorithm. In addition, the recommended scheme has proved its strength by outperforming both Carrier Sense Multiple Access (CSMA) and fix-sized guard zone schemes by significant margins under strict outage constraints and high contention density. The proposed scheme provided up to 100% and 60% better transmission capacity when compared with CSMA and fix-sized guard zone-based scheme, respectively. This paper also presents the closed-form results for the optimal guard zone size multiplier and the corresponding throughput capacity in terms of various network variables, such as contention density, outage constraint, Tx–Rx separation, network’s path loss exponent and spreading factor.

A Fair Channel Hopping Scheme for LoRa Networks with Multiple Single-Channel Gateways.

LoRa is one of the most prominent LPWAN technologies due to its suitable characteristics for supporting large-scale IoT networks, as it offers long-range communications at low power consumption. The latter is granted mainly because end-nodes transmit directly to the gateways and no energy is spent in multi-hop transmissions. LoRaWAN gateways can successfully receive simultaneous transmissions on multiple channels. However, such gateways can be costly when compared to simpler single-channel LoRa transceivers, and at the same time they are configured to operate with pure-ALOHA, the well-known and fragile channel access scheme used in LoRaWAN. This work presents a fair, control-based channel hopping-based medium access scheme for LoRa networks with multiple single-channel gateways. Compared with the pure-ALOHA used in LoRaWAN, the protocol proposed here achieves higher goodput and fairness levels because each device can choose its most appropriate channel to transmit at a higher rate and spending less energy. Several simulation results considering different network densities and different numbers of single-channel LoRa gateways show that our proposal is able to achieve a packet delivery ratio (PDR) of around 18% for a network size of 2000 end-nodes and one gateway, and a PDR of almost 50% when four LoRa gateways are considered, compared to 2% and 6%, respectively, achieved by the pure-ALOHA approach.

Interference-Aware Two-Level Differentiated Transmission for Improving Downlink Spatial Reuse in Dense WLANs.

In this study, we address the problem of downlink throughput degradation in dense wireless local area networks (WLANs) based on the IEEE 802.11ax standard. We demonstrate that this problem essentially results from the asymmetric characteristic of carrier sense multiple access between downlink and uplink transmissions in infrastructure WLANs, and it is exacerbated by a dynamic sensitivity control algorithm that aims to improve spatial reuse (SR) in IEEE 802.11ax. To solve this problem, we propose the interference-aware two-level differentiation mechanism consisting of the dual channel access (DCA) and supplemental power control (SPC) schemes. The proposed mechanism introduces a new measure called a spatial reusability indicator, which roughly estimates the signal-to-interference ratio from the received signal strength of beacon frames. Based on this measure, stations (STAs) are classified into the following two categories: spatial reusable STAs (SR-STAs) and non-spatial reusable STAs (NSR-STAs). Because SR-STAs are more robust to interference than NSR-STAs, the DCA scheme prioritizes transmissions to SR-STAs over those to NSR-STAs by using differentiated carrier sensing thresholds. Moreover, the SPC scheme selectively increases the transmission power to NSR-STAs to compensate for transmission failure due to interference. By combining the SPC and DCA schemes, the proposed mechanism effectively differentiates the downlink transmissions to SR-STAs and NSR-STAs in terms of channel access and transmission power, and it can boost the possibility of successful SR. The proposed mechanism can be easily implemented in IEEE 802.11ax without any complex calculation or significant signaling overhead. Moreover, we provide a practical guideline to determine appropriate parameter values for use in the proposed mechanism. The extensive simulation results obtained in this study confirm that the proposed mechanism increases the downlink throughput by more than several times without decreasing the overall throughput, compared to the existing mechanisms, and it maintains fairness between SR-STAs and NSR-STAs in terms of the ratio of successful transmission.

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.

Multi-Agent Reinforcement Learning-Based Distributed Channel Access for Next Generation Wireless Networks

In the next generation wireless networks, more applications will emerge, covering virtual reality movies, augmented reality, holographic three-dimensional telepresence, haptic telemedicine and so on, which require the provisioning of high bandwidth efficiency and low latency services. In order to better support the aforementioned applications and services, novel distributed channel access (DCA) schemes are necessary. Therefore, we propose a new MAC protocol, QMIX-advanced Listen-Before-Talk (QLBT), based on the cutting-edge multi-agent reinforcement learning (MARL) algorithm. It employs a centralized training with decentralized execution (CTDE) framework to exploit the overall information of all agents during training, and ensure that each agent can independently infer the optimal channel access behavior based on its local observation. We enhance QMIX, a well-known MARL algorithm, by introducing an extra individual Q-value for each agent in the mixing network apart from the original total Q-value, which makes QLBT more stable. Moreover, delay to last successful transmission (D2LT) is first introduced in this work as a part of the observations of each QLBT agent, which facilitates agents to reach a cooperative policy that prioritizes the agent with the longest delay. Finally, extensive simulation experiments are provided to show that the proposed QLBT algorithm: 1) outperforms CSMA/CA and even its theoretical performance bound in various scenarios including saturated traffic, unsaturated traffic and delay-sensitive traffic; 2) is robust in dynamic environment; and 3) is able to friendly coexist with “legacy” CSMA/CA stations.

Uplink OFDMA-Based Random Access Mechanism With Bursty Arrivals for IEEE 802.11ax Systems

IEEE 802.11ax defines a new channel access scheme of OFDMA-based random access (UORA) for varying number of associated stations (STAs) to send their requests or data to the access point (AP) in a contention manner. This letter presents an analytical model to investigate the performance of UORA in transient condition under bursty arrivals with arbitrary distribution. The key performance metrics of access success probability; average access delay; cumulative distribution function (CDF) for the number of transmissions; and utilization of random access resource units (RA-RUs) were derived. Simulation results verified the accuracy of the proposed analytical model.

Enhancing Channel Contention Efficiency in IEEE 802.15.4 Wireless Networks.

Numerous Internet of Things (IoT) devices adopt the IEEE 802.15.4 standard, which targets low data rate wireless networks. With the explosive growth in the use of IoT devices, it is essential to design effective and efficient channel access schemes for the 802.15.4 networks. In order to improve channel contention efficiency (CCE), which is defined as the number of times of successfully gaining the channel per unit of backoff time whereby throughput is improved, the scheme of enhancing channel contention efficiency (ECCE) has been proposed to jointly optimize the three key parameters of macMinBe, macMaxBe and macMaxCsmaBackoffs in the carrier sense multiple access with collision avoidance (CSMA-CA) mechanism in the 802.15.4 standard. A novel Markov chain was developed to model the CSMA-CA mechanism, which yielded the expected number of failures in gaining the channel, the expected number of backoff periods and the expected number of backoffs when a node intended to transmit a packet. These statistics resulted in CCE. An optimization problem that maximized the CCE with respect to the above-mentioned three key parameters was formulated. The solution to the optimization problem led to the optimal parameter values, which were applied in the ECCE scheme. The simulation results show that the proposed ECCE scheme outperformed the CSMA-CA mechanism in terms of CCE, delay and throughput.

Deep Reinforcement Learning Based Optical and Acoustic Dual Channel Multiple Access in Heterogeneous Underwater Sensor Networks.

In this paper, we investigate how to efficiently utilize channel bandwidth in heterogeneous hybrid optical and acoustic underwater sensor networks, where sensor nodes adopt different Media Access Control (MAC) protocols to transmit data packets to a common relay node on optical or acoustic channels. We propose a new MAC protocol based on deep reinforcement learning (DRL), referred to as optical and acoustic dual-channel deep-reinforcement learning multiple access (OA-DLMA), in which the sensor nodes utilizing the OA-DLMA protocol are called agents, and the remainder are non-agents. The agents can learn the transmission patterns of coexisting non-agents and find an optimal channel access strategy without any prior information. Moreover, in order to further enhance network performance, we develop a differentiated reward policy that rewards specific actions over optical and acoustic channels differently, with priority compensation being given to the optical channel to achieve greater data transmission. Furthermore, we have derived the optimal short-term sum throughput and channel utilization analytically and conducted extensive simulations to evaluate the OA-DLMA protocol. Simulation results show that our protocol performs with near-optimal performance and significantly outperforms other existing protocols in terms of short-term sum throughput and channel utilization.

Optimizing joint probabilistic caching and channel access for clustered D2D networks

Caching at mobile devices and leveraging device-to-device (D2D) communication are two promising approaches to support massive content delivery over wireless networks. Analysis of such D2D caching networks based on a physical interference model is usually carried out by assuming uniformly distributed devices. However, this approach does not capture the notion of device clustering. In this regard, this paper proposes a joint communication and caching optimization framework for clustered D2D networks. Devices are spatially distributed into disjoint clusters and are assumed to have a surplus memory that is utilized to proactively cache files, following a random probabilistic caching scheme. The cache offloading gain is maximized by jointly optimizing channel access and caching scheme. A closed-form caching solution is obtained and bisection search method is adopted to heuristically obtain the optimal channel access probability. Results show significant improvement in the offloading gain reaching up to 10% compared to the Zipf caching baseline.

Multi-Link Operation with Enhanced Synchronous Channel Access in IEEE 802.11be Wireless LANs: Coexistence Issue and Solutions.

Multi-link operation is a new feature of IEEE 802.11be Extremely High Throughput (EHT) that enables the utilization of multiple links using individual frequency channels to transmit and receive between EHT devices. This paper aims to illustrate enhanced multi-link channel access schemes, identify the associated coexistence challenge, and propose solutions. First, we describe the multi-link operation of IEEE 802.11be and how the asynchronous and synchronous channel access schemes facilitate multi-link utilization. Next, we describe the design variants of the synchronous channel access scheme and demonstrate the associated coexistence challenge. Subsequently, we propose four features to address this challenge by assigning penalties to multi-link devices (repicking a backoff count, doubling the contention window size, switching to another contention window set, and compensating the backoff count) as well as five coexistence solutions derived from combinations of these features. Comparative simulation results are provided and analyzed for dense single-spot and indoor random deployment scenarios, demonstrating that the throughput and latency gains of multi-link operation differ between schemes. At the same time, we investigate the coexistence performance of multi-link operation with and without the capability of simultaneous transmission and reception and demonstrate that the proposed solutions mitigate the coexistence problem. In particular, compensating the backoff count achieves the highest coexistence performance among the proposed solutions, with a marginal throughput decrease of multi-link devices. A metric for evaluating both the throughput and latency gains and the coexistence performance of a multi-link channel access scheme using a single value is also proposed.

Put others before itself: A multi-leader one-follower anti-jamming stackelberg game against tracking jammer

This paper mainly investigates the coordinated anti-jamming channel access problems in multiuser scenarios where there exists a tracking jammer who senses the spectrum and traces the channel with maximal receiving power. To cope with the challenges brought by the tracking jammer, a multi-leader one-follower anti-jamming Stackelberg (MOAS) game is formulated, which is able to model the complex interactions between users and the tracking jammer. In the proposed game, users act as leaders, chose their channel access strategies and transmit firstly. The tracking jammer acts as the follower, whose objective is to find the optimal jamming strategy at each time slot. Besides, the existence of Stackelberg equilibriums (SEs) is proved, which means users reach Nash Equilibriums (NEs) for each jamming strategy while the jammer finds its best response jamming strategy for the current network access case. An active attraction based anti-jamming channel access (3ACA) algorithm is designed to reach SEs, where jammed users keep their channel access strategies unchanged to create access chances for other users. To enhance the fairness of the system, users will adjust their strategies and re-learn after certain time slots to provide access chances for those users who sacrifice themselves to attract the tracking jammer.

A multi‐agent reinforcement learning anti‐jamming method with partially overlapping channels

This paper investigates the problem of multi-user anti-jamming channel access with partially overlapping channels (POC). Compared with traditional anti-jamming systems that use non-overlapping channels, POC improve the spectral efficiency. However, the partial overlap of channels also brings more serious interference. For this, physical distance and channel separation on the interference intensity under partially overlapping channels are first considered and the malicious jamming and interference among users are formulated as a hierarchical binary model. Secondly, to cope with multi-user decisions under dynamic jamming conditions, the Markov game framework is adopted to analyse the problem. Thirdly, a multi-user collaborative anti-jamming channel selection algorithm based on reinforcement learning is proposed as well as the optimal anti-jamming strategy can be obtained. Finally, the simulation results validate that the proposed algorithm helps users cope with jamming and eliminate mutual interference. Compared with the non-overlapping channel access scheme, the POC access scheme achieves higher network throughput.

Exploiting an Optimal Delay-Collision Tradeoff in CSMA-Based High-Dense Wireless Systems

A novel carrier sense multiple access strategy with collision avoidance (CSMA/CA) balancing contention probability and channel access time is proposed. The approach can be applied to any context where the computational simplicity of the MAC must be preferred to the complexity of the channel access strategy. Our MAC, called Delay-Collision CSMA (DC-CSMA), is a slotted nonpersistent CSMA/CA with nonuniform contention probability distribution, designed to reduce at the same time latency of contenders and preserve a high successful access probability. An utility function aiming at equalizing the effects of these two performance metrics is introduced, and the related theoretical properties and optimal distribution are derived. DC-CSMA is insensitive to the number of contenders and very robust with respect to contention window size, packet length, and impairments such as frame synchronization errors and hidden terminals, and it does not require any adaptive tuning to optimize its performance. Current technologies such as WSN, RFID, IoT devices can benefit from such a simple access technique. The numerical evaluation has been led out considering latency, successful probability and throughput, and DC-CSMA has been compared with other classical strategies such as CSMA with uniformly distributed contention probability, CSMA/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p^{\ast}$ </tex-math></inline-formula> and Sift distribution.

LSTM-Based Channel Access Scheme for Vehicles in Cognitive Vehicular Networks With Multi-Agent Settings

In this paper, we study the channel access problem of vehicles in a cognitive radio vehicular network, where each vehicle opportunistically accesses the channel resources of the primary network in order to successfully receive the necessary data packets within a time deadline. Given the access priority constraint and the limited bandwidth of the primary network, a smart channel connection scheme is indispensable to ensure a decent quality of service (QoS) at the vehicles’ side. Due to the competitive nature of vehicles, the vehicle access control is formulated as a multi-agent access problem that comes with an intrinsic challenge, i.e. the partial observation of the information about the environment dynamics. On top of that, considering the temporal usage profile of the primary network, the environment dynamics are also time-dependant, and hence making the aforementioned access control a non-Markovian problem. Consequently, the estimation of the system states, which are used for the decision making process of a vehicle, is very challenging. To deal with the issues arising from such non-Markovian problem, we propose a vehicle connection algorithm based on a deep recurrent Q-learning network. With the aid of a recurrent Long Short Term Memory (LSTM) layer integrated into a deep Q-network, the time-correlated system states can be properly estimated, thereby improving the vehicle channel access policy. Besides, we introduce novel reward quantities that help improving the network performance and the capability to flexibly adapt to unexplored scenarios. A new structure of the cumulative reward function is also presented to balance the performance trade off between the cooperative and competitive objectives. Simulation results are provided to verify the advantage and the stability of our proposed algorithm over the benchmark schemes.

3GPP V2X on Unlicensed Spectrum: Performance Analysis and Optimum Channel Access Strategies

Featuring unprecedentedly high data rates and high connection densities, 3GPP New Radio (NR) vehicle-to-everything (V2X) communications have been regarded as the most promising remedy to support the next generation driving use cases. For this purpose, although dedicated bands on 5.9 GHz spectrum have been allocated for Intelligent Transportation Systems (ITS), the limited bandwidth may not afford the desired service requirements. This engineering concern thus drives the utilization of unlicensed bands on 5 GHz spectrum adjacent to the ITS bands. However, subject to the fairness constraint in sharing unlicensed spectrum, various communication regulations have been imposed, and four different types of multi-band channel access procedures are consequently developed both in 3GPP LTE-A Licensed-Assisted Access (LAA) and NR on unlicensed spectrum (NR-U), to lead to a phenomenon that occupying more unlicensed bands may not suggest a proportional growth in the throughput. To empower high-throughout and high-density V2X communications, in this paper, we consequently propose the optimum channel access strategies for each V2X transmitter to decide the optimum number of unlicensed bands to access. To this end, analytic models for four types of multi-band channel access procedures in 3GPP NR-U are provided, which capture both inter-system and intra-system interference from coexisting WiFi transmitters and V2X transmitters. Subsequently, game-theoretically optimum strategies for each type of multi-band channel access procedures are derived. Performance evaluation results fully demonstrate the optimality of the proposed strategies, to serve the urgent demands in supporting the next generation driving use cases on unlicensed spectrum.

Dynamic Resource Allocation Strategy in Mobile Edge Cloud Computing Environment

With the development of the mobile Internet, smart mobile terminals have become an indispensable tool for people's lives and mobile applications are becoming more and more powerful. This research mainly discusses the dynamic resource allocation strategy of the mobile edge cloud computing environment. The physical resource layer in the network model is responsible for providing specific resources that are actually available, such as hardware resources, computing resources, storage resources, mainly including base stations, mobile edge computing servers, spectrum, power, and other communications of different infrastructure vendor basic components of the system. The functions of the virtual machine monitor include resource virtualization and resource management. As an important component of wireless network virtualization, virtual machine monitors are usually deployed in physical base stations to provide physical resources and to consider the connection between the virtual machine stations. The business of the business cache model is an application that is requested by users running on the mobile edge computing server or cloud at the base station. The computing task scheduling in the mobile edge environment can be classified as a wireless interaction model. This model captures the user throughput in cellular network interaction. The physical layer channel access strategy (CDMA) allows all mobile users to efficiently share the same spectrum resources at the same time. When the preference coefficient for task energy consumption varies between 0.35–0.55 and 0.65–1, the superior range of maximum system efficiency achieved by RAOM accounts for 55% of the entire range. This research contributes to the reasonable allocation of resources, and the mobile edge computing model improves the fairness of users with a lower transmission cost.