Time Division Multiple Access Protocol Research Articles

A State-Interactive MAC Layer TDMA Protocol Based on Smart Antennas

Mobile ad hoc networks are self-organizing networks that do not rely on fixed infrastructure. Smart antennas employ advanced beamforming technology, enabling ultra-long-range directional transmission in wireless networks, which leads to lower power consumption and better utilization of spatial resources. The media access control (MAC) protocol design using smart antennas can lead to efficient usage of channel resources. However, during ultra-long-distance transmissions, there may be significant transport delays. In addition, when using the time division multiple access (TDMA) schemes, it can be difficult to manage conflicts arising from adjacent time slot advancement caused by latency compensation in ultra-long-range propagation. Directional transmission and reception can also cause interference between links that reuse the same time slot. This paper proposes a new distributed dynamic TDMA protocol called State Interaction-based Slot Allocation Protocol (SISAP) to address these issues. This protocol is based on slot states and includes TDMA frame structure, slot allocation process, interference self-avoidance strategy, and slot allocation algorithms. According to the simulation results, the MAC layer design scheme suggested in this paper can achieve ultra-long-distance transmission without conflicts. Additionally, it can reduce the interference between links while space multiplexing. Furthermore, the system exhibits remarkable performance in various network aspects, such as throughput and link delay.

Enhanced Clustering MAC Protocol Based on Learning Automata for UV Networks

Ultraviolet (UV) networks are widely applied in complex electromagnetic environments. Designing an efficient multi-node medium access control (MAC) protocol for these networks is important. In this study, we proposed an enhanced clustering time division multiple access (TDMA) MAC protocol based on clustering and learning automata (LA). Subsequently, the effects of the network topology, class of service, and number of cluster nodes on the network performance under the proposed protocol were analyzed. Then, the protocol was compared with the TDMA protocol and clustering system. Results revealed that it obtained a better network performance, proving its suitability for multi-node UV networking.

Performance Evaluation of Collision Avoidance for Multi-node LoRa Networks based on TDMA and CSMA Algorithm

LoRa can be used as the communication technology for the intelligent monitoring system. However, LoRa is usually used for outdoor communication. The usage of LoRa as indoor communication has many challenges. One of the challenges is that collision happens when using standard LoRa devices with only one channel. The algorithms based on TDMA (Time-division Multiple Access) and CSMA (Carrier-sense Multiple Access) protocols can be used to address this challenge. These two algorithms can be modified by applying the device that is the center of the network (gateway) as a central control and the data transmitter (sensor node) as a passive device. The test was conducted on the Intelligent Laboratory Monitoring System to evaluate this design on a multi-node LoRa network. RSSI testing proves that the distance and building interference affect the signal strength or RSSI of sensor nodes, so the average RSSI value is -73.75 with an RSSI threshold of value -106. The gateway successfully collected each sensor node data with an average success of about 64.953%. The experiment results show the success rate of the CSMA-based algorithm is 10% versus 100% in TDMA-based algorithm; the delay is 4125 ms for CSMA-based and 428.3 ms for TDMA-based. This result means that the CSMA-based algorithm is more complex, takes more time to process the data than the TDMA-based algorithm, has a low success rate, and is more prone to collisions.

A novel distributed multi-slot TDMA-based MAC protocol for LED-based UOWC networks

Underwater optical wireless communication (UOWC) networks are promising for many civilian and industrial applications due to underwater high-speed data transmission demand. This paper focuses on the distributed time division multiple access (TDMA) protocol design for UOWC networks. Unlike existing research, we focus on a more general underwater communication scenario where nodes are scattered, and node mobility is considered. We propose a distributed TDMA-based medium access control(MAC) protocol, called cluster-based cross-layer multi-slot MAC(CCM-MAC), which can assign multiple slots to each node according to the slot-occupying information. When using CCM-MAC, the network is divided into clusters. Each node maintains knowledge of the cluster topology and slot-occupying information of surrounding nodes through routing techniques; by updating this knowledge, collisions can also be detected and eliminated dynamically. Analysis results are presented to evaluate the performance of CCM-MAC, and simulations show that high network throughput and low collision rate can be realized in comparison with existing contention-based MAC protocols.

Over-the-Air Max-Consensus in Clustered Networks Adopting Half-Duplex Communication Technology

This work considers a network of autonomous agents that exploit the superposition property of the wireless channel for achieving max-consensus under communication constraints. In technical applications, superposition (or interference) is traditionally avoided by physically separating transmissions from different agents, e.g., by employing TDMA (Time Division Multiple Access) or FDMA (Frequency Division Multiple Access) protocols. In contrast, Over-the-Air Computation relies on simultaneous transmissions of signals in the same frequency band to boost performance. This paper extends the results presented in Molinari et al. [14] in a significant way: rather than requiring a new and hardly accessible technology that allows simultaneous receiving and transmission of signals (Full-Duplex), we present a solution based on cheap and ubiquitous Half-Duplex technology. However, Half-Duplex technology only allows agents to either receive or transmit at a given time, hence, requiring agents to be grouped into clusters. The proposed method, first, enables each cluster to achieve max-consensus within itself. Then, agents belonging to more than one cluster spread the information across different clusters that are, in general, not synchronized. The proposed max-consensus protocol can deal with asynchronism, and allows the network to achieve max-consensus within a finite number of steps. Simulations confirm our theoretical results.

Ultraviolet random access collaborative networking protocol based on time division multiple access

The ultraviolet network, with its advantages of high security, non-line-of-sight communication, and all-weather operation, has broad military application potential. This study proposes an ultraviolet random access collaborative networking protocol based on time division multiple access that combines the benefits of synchronous and asynchronous media access control protocols. Considering the physical layer characteristics, the frame structure of the protocol is constructed based on a cross-layer design. Compared with the time division multiple access protocol, the proposed protocol can achieve higher throughput with a lower delay and packet loss rate by the dynamic timeslot allocation mechanism. Then, the effects of maximum cache capacity and burst traffic on network performance are investigated. Finally, the conducted network experiments prove the cooperative forwarding and random access capabilities of the ultraviolet random access collaborative networking protocol. The proposed protocol provides a reliable and effective method for independent and flexible ultraviolet networks.

Detection of AIS messages falsifications and spoofing by checking messages compliance with TDMA protocol

Automatic identification system is a navigation aid system that allows vessels to exchange automatically positions, identity and other information. It improves the safety of the maritime traffic and helps to monitor it. However, this system can be manipulated to send falsified information and to mask illicit activities. While previous research has proposed strategies to detect these threats, none of them suggest a solution that considers the time-division multiple access (TDMA) communication protocol. In this work, the compliance of the sent messages with this protocol, specified by the system's standard, is checked for every ship to detect message falsifications. Furthermore, because the ships velocity affects TDMA protocol, a strategy based a Kalman filter is applied to track every ship and to assess the consistency of their velocity data sent. The proposed strategy was validated on real data and showed very promising results. Being computationally cheap, the method can be run in real time. Source codes of the method are open-source to foster research activities from both industry and academia in this field.

UAV-Enabled Mobile Edge Computing for Resource Allocation Using Cooperative Evolutionary Computation

Edge computing is a viable paradigm for supporting the Industrial Internet of Things deployment by shifting computationally demanding tasks from resource-constrained devices to powerful edge servers. In this study, mobile edge computing (MEC) services are provided for multiple ground mobile nodes (MNs) through a time-division multiple access protocol using the unmanned aerial vehicle (UAV)-enabled edge servers. Remotely controlled UAVs can serve as MEC servers due to their adaptability and flexibility. However, the current MEC approaches have proven ineffective in situations where the number of MNs rapidly increases, or network resources are sparsely distributed. Furthermore, suitable accessibility across wireless networks via MNs with an acceptable quality of service is a fundamental problem for conventional UAV-assisted communications. To tackle this issue, we present an optimized computation resource allocation model using cooperative evolutionary computation to solve the joint optimization problem of queue-based computation offloading and adaptive computing resource allocation. The developed method ensures the task computation delay of all MNs within a time block, optimizes the sum of MN's accessibility rates, and reduces the energy consumption of the UAV and MNs while meeting task computation restrictions. Moreover, we propose a multilayer data flow processing system to make full use of the computational capability across the system. The top layer of the system contains the cloud centre, the middle layer contains the UAV-assisted MEC (U-MEC) servers, and the bottom layer contains the mobile devices. Our numerical analysis and simulation results prove that the proposed scheme outperforms conventional techniques such as equal offloading time allocation and straight-line flight.

Acoustic positioning of multiple AUVs by an ASV: experimental validation and performance characterisation

Cooperation among heterogeneous marine vehicles can offer several benefits to underwater applications, such as supporting the navigation of submerged robots by leveraging the information available to a surface vehicle. Within such context, this paper describes an acoustic positioning and communication protocol developed for the localisation of multiple Autonomous Underwater Vehicles (AUVs) by means of an Autonomous Surface Vehicle (ASV) equipped with an Ultra-Short BaseLine (USBL) device. To avoid packet collisions, access to the acoustic channel is managed through a time slot division mechanism. Unlike a classical Time Division Multiple Access (TDMA) protocol, the approach considered in this work consists of a centralised scheduling handled by the ASV, in which AUVs are localised at regular time epoch but can transmit only when queried. This allows to prioritise the number of position measurements taken by the ASV and then relayed back to the submerged vehicles, with the final goal of improving the navigation accuracy of the latter. The solution is also designed to handle the latency of acoustic communication and to correctly associate each position measurement with the corresponding acquisition time. Furthermore, it does not require any a priori synchronisation between the clocks of the vehicles involved and ensures complete decoupling between their navigation algorithms. Experimental activities in very-shallow waters, involving an ASV and two target nodes, were carried out to validate the multi-AUVs positioning system and to provide a characterisation of its performance.

Dynamic Multichannel Access Based on Deep Reinforcement Learning in Distributed Wireless Networks

With the emergence of innovative applications in vertical industries such as smart home and industrial automation, machine communication has shown a spurt of development. Different from the traditional human-oriented cellular communication, machine communication is characterized by strong uncertainty and abruptness, large-scale concurrent device connection as well as uneven and unsaturated data traffic. This article investigates the dynamic multiple-devices multiple-channels access for unsaturated traffic with retransmission mechanism, which is aimed at reducing the long-term data packet loss resulting from buffer overflows and transmission failure. The instant channel selection will lead to a non-negligible impact on the future decision, motivating us to model this problem as a Markov decision process. Limited by the unknown environment knowledge, we proposed a dynamic access policy based on deep reinforcement learning algorithm to optimally select the channel for transmission or keep silent for Internet-of-Things devices. Simulation results confirm that our proposed channel access strategy can reduce the collision and the packet loss of network. Furthermore, it can also work well when coexisting with the devices that adopt time division multiple access (TDMA) or ALOHA protocol.

Online distributed evolutionary optimization of Time Division Multiple Access protocols

With the advent of cheap, miniaturized electronics, ubiquitous networking has reached an unprecedented level of complexity, scale and heterogeneity, becoming the core of several modern applications such as smart industry, smart buildings and smart cities. A crucial element for network performance is the protocol stack, namely the sets of rules and data formats that determine how the nodes in the network exchange information. A great effort has been put to devise formal techniques to synthesize (offline) network protocols, starting from system specifications and strict assumptions on the network environment. However, offline design can be hard to apply in the most modern network applications, either due to numerical complexity, or to the fact that the environment might be unknown and the specifications might not available. In these cases, online protocol design and adaptation has the potential to offer a much more scalable and robust solution. Nevertheless, so far only a few attempts have been done towards online automatic protocol design. These approaches, however, typically require a central coordinator, or need to build and update a model of the environment, which adds complexity. Here, instead, we envision a protocol as an emergent property of a network, obtained by an environment-driven Distributed Hill Climbing (DHC) algorithm that uses node-local reinforcement signals to evolve, at runtime and without any central coordination, a network protocol from scratch, without needing a model of the environment. We test this approach with a 3-state Time Division Multiple Access (TDMA) Medium Access Control (MAC) protocol and we observe its emergence in networks of various scales and with various settings. We also show how DHC can reach different trade-offs in terms of energy consumption and protocol performance.

Energy efficient medium access control protocol for data collection in wireless sensor network: A Q-learning approach

In emerging business markets, the data is becoming new gold for the industries. There are several places such as marketing, manufacturing, and analysis of future trends becoming data-intensive to achieve growth. The tiny sensor placements in the field, cities, industry, buildings and sea are helping to collect data and process it either for information retrieval or decision making. The periodic scheduling of radio transceivers assists in accomplishing efficient energy utilization in sensors often uses Time-division multiple access (TDMA) protocols for node scheduling. Our objective is to reduce the amount of time; the receiver node is in the wake-up state. Besides, the slot which potentially not being used for an extended period can utilize by other nodes. The efficient utilization of slots can help to achieve low power duty cycles with low latency. To accomplish that, we propose the emulation of the classroom learning environment with the Q-learning grading for node scheduling. We proposed an analytical mapping of WSNs to classroom learning. The initial benchmark of the performance has compared to the IEEE.802.11 (TDMA-scheduling). Further, the TDMA driven protocols such as Z-MAC, learning-driven protocols (E-MAC or aloha-Q), i-Queue are compared to evaluate the parameters such as energy consumption, throughput, and latency.

Performance Analysis of MAC Layer Protocols for WSN with Considering the Effects of Hidden Node Problem

In this paper, the effects of the hidden node problem in Wireless sensor networks are studied on three different MAC protocols using various field distances and various numbers of nodes. This study provides the best number of nodes to be disseminated in a specific field distance depending on the needed performance metrics. Six performance metrics are used in this study, which are Goodput, Throughput, Packet delivery ratio (PDR), Residual Energy, Average Delay, and the first and last node dead in the network. IEEE 802.11, IEEE 802.15.4, and time division multiple access (TDMA) protocols are used. Results show that TDMA gives the best energy conservation and high delay time with high PDR, while IEEE 802.11 provides the best throughput and goodput results and low delay time.

A Distributed Connectivity Maintenance Algorithm With Formal Guarantees for a Communication-Constrained Network of Unmanned Underwater Vehicles

This article presents a distributed connectivity maintenance algorithm for a multiagent system composed of unmanned underwater vehicles (UUVs). We consider a homogeneous network of UUVs that move on a 2-D plane with bounded linear speeds. The time-division multiple-access protocol, which is a commonly used communication protocol for UUVs, is used by the agents in the network to communicate with each other. Due to the communication constraints imposed by the protocol, the agents do not have access to the current positions of their neighbors. This presents a significant challenge in developing a connectivity maintenance algorithm that can be formally verified. Using only local information from an agent’s neighbors, the algorithm provides motion constraints for each agent in the network, which can then be used by each UUV’s motion planner to plan a connectivity-preserving reference trajectory. In addition to providing mathematical proofs expressed in a way that is typical in the systems and control community, we give formal proofs of the results that establish network connectivity for the presented algorithm under suitable assumptions on each agent’s motion planner and controller. The formal proofs are carried out using the KeYmaera X theorem prover, which is an interactive formal verification tool for hybrid systems. This article also highlights the utility of formal verification tools in identifying scenarios that could be overlooked when employing proofs that are not carried out in a formal system for complex distributed algorithms such as the one presented in this article.

Online Distributed Evolutionary Optimization of Time Division Multiple Access Protocols

Online Distributed Evolutionary Optimization of Time Division Multiple Access Protocols

Data Collision and Interference Minimization in Wireless Sensor Network using Node Data Addressing with Random Access Time

A wireless sensor network (WSN) refers to a spatially dispersed network of sensors that monitor and collect environmental data and forward the collected data to the central station. WSN has been widely used in daily life and industrial applications, ranging from surveillance, military, healthcare, habitat monitoring, and agriculture application. However, WSN that uses radiofrequency (RF) communication may suffer from noise and interference caused by two or more radios that uses the same frequency. Data collision is also expected within the wireless network especially when numerous sensor nodes are transmitting their data to the base station (BS) through a shared medium. Hence, this research contributes in mitigating the RF interference and data collision in the network to increase the network’s data reliability by using the concept of Time Division Multiple Access (TDMA) protocol where each sensor node will be transmitting their data at a different time to avoid collision and interference in the shared medium. However, in this research, each sensor node will access the channel or the transmission medium at a random time. To prove the concept of the proposed method on data collision and interference minimization, an Internet of Things (IoT) based wireless sensor network for alerting application will be designed and implemented in the fire station. It has been found from the experimental result that RF interference and data reliability in the network can be reduced by 90% with the proposed algorithm by allowing the sensor node to access the RF channel and transmit the data at a random time.

User Grouping and Reflective Beamforming for IRS-Aided URLLC

This letter studies an intelligent reflecting surface (IRS)-aided downlink ultra-reliable and low-latency communication (URLLC) system, in which an IRS is dedicatedly deployed to assist a base station (BS) to send individual short-packet messages to multiple users. To enhance the URLLC performance, the users are divided into different groups and the messages for users in each group are encoded into a single codeword. By considering the time division multiple access (TDMA) protocol among different groups, our objective is to minimize the total latency for all users subject to their individual reliability requirements, via jointly optimizing the user grouping and blocklength allocation at the BS together with the reflective beamforming at the IRS. We solve the latency minimization problem via the alternating optimization, in which the blocklengths and the reflective beamforming are optimized by using the techniques of successive convex approximation (SCA) and semi-definite relaxation (SDR), while the user grouping is updated by K-means and greedy-based methods. Numerical results show that the proposed designs can significantly reduce the communication latency, as compared to various benchmark schemes, which unveil the importance of user grouping and reflective beamforming optimization for exploiting the joint encoding gain and enhancing the worst-case user performance.

Robust Secure UAV Communications With the Aid of Reconfigurable Intelligent Surfaces

This paper investigates a novel unmanned aerial vehicles (UAVs) secure communication system with the assistance of reconfigurable intelligent surfaces (RISs), where a UAV and a ground user communicate with each other, while an eavesdropper tends to wiretap their information. Due to the limited capacity of UAVs, an RIS is applied to further improve the quality of the secure communication. The time division multiple access (TDMA) protocol is applied for the communications between the UAV and the ground user, namely, the downlink (DL) and the uplink (UL) communications. In particular, the channel state information (CSI) of the eavesdropping channels is assumed to be imperfect. We aim to maximize the average worst-case secrecy rate by the robust joint design of the UAV’s trajectory, RIS’s passive beamforming, and transmit power of the legitimate transmitters. However, it is challenging to solve the joint UL/DL optimization problem due to its non-convexity. Therefore, we develop an efficient algorithm based on the alternating optimization (AO) technique. Specifically, the formulated problem is divided into three sub-problems, and the successive convex approximation (SCA), <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {S}$ </tex-math></inline-formula> -Procedure, and semidefinite relaxation (SDR) are applied to tackle these non-convex sub-problems. Numerical results demonstrate that the proposed algorithm can considerably improve the average secrecy rate compared with the benchmark algorithms, and also confirm the robustness of the proposed algorithm.

Impairments-aware time slot allocation model for energy-constrained multi-hop clustered IoT nodes considering TDMA and DSSS MAC protocols

The possibility of Internet of Things (IoT) is that a large number of live items (e.g., apparatuses) in the network are available, detected, and interconnected. In any case, the performance of IoT networks may be limited due to several impairments, most importantly, the energy-constrained IoT nodes. In fact, this limitation opens the door to many researchers where using network clustering has proven to be efficient energy saving mechanism. To the best of our knowledge, there are no prior research, in the field of multi-hop clustered IoT networks, which addressed the energy-constrained IoT nodes problem along with the delay in receiving data messages from devices, located far away from the remote users (or control center), in timely basis. Practically, it is significantly challenging to contemplate and clarify this issue. Consequently, in this paper, we make major amendments on the prior work, Improved Energy and Distance Based CH Selection with Balanced Objective Function (IEDB-CHS-BOF), and particularly propose a multi-hop routing (MR) protocol in which the IoT network is divided into a number of virtual sections with lengths held below the cross-over communication distance, thereby ensuring minimal energy depletion. Over those virtual sections, efficient forwarder and cluster head selection algorithms are further proposed. Interestingly, we propose a novel delay-, power-, and interference-aware time slot allocation model in which Time Division Multiple Access (TDMA) and Direct Sequence Spread Spectrum (DSSS) MAC protocols are operated. Furthermore, it is a good representation of the above-mentioned proposals. As a result, our protocols are referred to as MR-IEDB-CHS-TDMA and MR-IEDB-CHS-DSSS, respectively. To this end, numerous simulations have been conducted for evaluating the performance of the proposed protocols in the perspective of IoT network lifetime. In addition, sufficient comparisons have been conducted with the existing state-of-the-art protocols. In overall, the MR-IEDB-CHS-TDMA protocol keeps the IoT network functioning the longest.

A collision feedback based multiple access control protocol for very high frequency data exchange system in E-navigation

AbstractThe very high frequency data exchange system (VDES) is promising in promoting electronic navigation (E-navigation) and improving navigation safety. The multiple access control (MAC) protocol is crucial to the transmission performance of VDES. The self-organising time division multiple access (SOTDMA) protocol, as the only access mode given by current recommendations, leads to a high rate of transmission collisions in the traditional automatic identification system (AIS), especially with heavy traffic loads. This paper proposes a novel feedback based time division multiple access (FBTDMA) protocol to address the problems caused by SOTDMA, such that collision of transmissions can be avoided in information transmission among vessels. Simulation results demonstrate that the proposed FBTDMA outperforms the traditional SOTDMA in terms of channel utilisation and throughput, and significantly reduces the transmission collision rate. The study is expected to provide insights into VDES standardisation and E-navigation modernisation.