Communication In Wireless Networks Research Articles

A Throughput Fairness Control Method for Concurrent Communications in Wireless Local-Area Network with Multiple Access-Points

The IEEE 802.11n wireless local-area network (WLAN) has been widely deployed at every place around the world for the Internet access services. In WLAN, the throughput unfairness problem appears among concurrently communicating hosts due to their signal strength differences when the distances to access-points (APs) are different. Previously, to achieve fair network services among users, we have studied the method of controlling the packet transmission delay at one AP using PI controller. However, it cannot be applied to multiple APs that are common in WLAN. In this paper, we propose a throughput fairness control method of applying traffic shaping at the APs to provide the fair throughput among concurrently communicating hosts with multiple APs. For evaluations, we implement the testbed system using Raspberry Pi for APs and conduct extensive experiments in six topologies with up to four APs. The results show that the throughput of every host is similar to each other in any topology, which confirms the effectiveness of the proposal.

Energy Efficient UAV-Based Service Offloading Over Cloud-Fog Architectures

Unmanned Aerial Vehicles (UAVs) are poised to play a central role in revolutionizing future services offered by the envisioned smart cities, thanks to their agility, flexibility, and cost-efficiency. UAVs are being widely deployed in different verticals including surveillance, search and rescue missions, delivery of items, and as an infrastructure for aerial communications in future wireless networks. UAVs can be used to survey target locations, collect raw data from the ground (i.e., video streams), generate computing task(s) and offload it to the available servers for processing. In this work, we formulate a multi-objective optimization framework for both the network resource allocation and the UAV trajectory planning problem using Mixed Integer Linear Programming (MILP) optimization model. In consideration of the different stake holders that may exist in a Cloud-Fog environment, we minimize the sum of a weighted objective function, which allows network operators to tune the weights to emphasize/de-emphasize different cost functions such as the end-to-end network power consumption (EENPC), processing power consumption (PPC), UAV’s total flight distance (UAVTFD), and UAV’s total power consumption (UAVTPC). Our optimization models and results enable the optimum offloading decisions to be made under different constraints relating to EENPC, PPC, UAVTFD and UAVTPC which we explore in detail. For example, when the UAV’s propulsion efficiency (UPE) is at its worst (10% considered), offloading via the macro base station is the best choice and a maximum power saving of 34% can be achieved. Extensive studies on the UAV’s coverage path planning (CPP) and computation offloading have been conducted, but none has tackled the issue in a practical Cloud-Fog architecture in which all the elements of the access, metro and core layers are considered when evaluating the service offloading in a distributed architecture like the Cloud-Fog.

Compact Substrate Integrated Waveguide Filtering Antennas: A Review

In recent years, with the rapid development of integrated circuits, the filtering antenna (FA) circuit of the substrate integrated waveguide (SIW) has attracted widespread attention in wireless communications. Numerous structures have been proposed to improve the performance of SIW FA. Hence, this paper presents the development and miniaturization trend of the SIW FA, and briefly introduces the structure and historical development of the SIW FA. In terms of the mode, multi-mode cavities and incomplete mode cavities are constructed. Multi-layer structures, special structures and the slow-wave technology are constructed in physical structure. Several methods and design examples of the SIW FA miniaturization are introduced from these two aspects. Based on the combination of the filter and antenna, the FA remains the advantages of the SIW structure, mainly including small size, low insertion loss, high quality-factors, and easy integration in planar radio frequency components. Therefore, it can further reduce the circuit, allowing SIW FAs to be applied in many aspects such as the 5G (5th generation mobile communication technology) and wireless local area network communications.

Energy Aware Routing Protocol with Data Fusion and Machine Learning

The current wireless and communication system may be attributed to the contributions made by the Sensor Network in a significant measure. During the last decade, several efforts have been performed to examine and propose answers to challenges about the energy efficiency of wireless sensor network communications. Several different researchers has done these efforts. The challenge of constructing economical energy-use paths has not yet been overcome. Because sensors have limited computational capabilities, which are frequently coupled with energy limitations, it is rather difficult to guarantee that a sensor’s lifespan will be longer. This is because of the energy constraints often associated with these limitations. The results of this research have led to the development of a one-of-a-kind communication system for sensor networks that is not only environmentally friendly but also supported by three distinct revolutionary frameworks. The framework that has been recommended, which goes by the name Potential Energy Efficient Data Fusion (PEE-DF), is the one that is in charge of the optimization of energy. It achieves this with the aid of probabilistic approaches and clustering. The K-SOM (Korhonen self-organizing map) framework was designed using a globular topology, which aids load balancing during data fusion. K-SOM stands for Korhonen self-organizing map. This was done to ensure we got the most out of our resources. A novel method to routing is presented by the technique, which has the potential to be used to assist in the operation of energy-efficient routing in large-scale wireless sensor networks. The framework for the Tree-Based Fusion Technique (TBFT), which has been offered, comes up with a new way for dynamic reconfiguration. This is accomplished via the introduction of the concept of routing agents. The strategy enables the system to recognise which sensor has a greater energy dissipation rate and then instantly moves data fusion work to a more energy-efficient node. This allows the system to save energy. This approach, based on thresholds, enable a sensor to act as a cluster head up until it reaches its threshold remnant energy and then as a member node once it exceeds threshold residual energy. In other words, it may play both roles simultaneously. It is possible to fulfil both of these responsibilities at the same time. The findings have been mathematically modelled using a standard radio-energy model, which has enhanced the robustness of the findings, which is highly positive. The results were encouraging because of the increased robustness of the findings. Compared to the benchmark previously established for energy-efficient strategies, the proposed system demonstrates higher performance in terms of its ability to communicate while using less energy. In contrast to LEACH, the recommended system's findings reveal an almost fifty percent decrease in energy consumption, and at the same time, a reduction in the amount of time required to carry out the operation..

A Portable Device of Air Pollution Measurement Due to Highway Exhaust Emissions Using LabVIEW Programming

A multisensory gas device integrated with myRIO module to measure air pollution has been established. This device is programmed using the LabVIEW programming language and can measure CO2, CO, NOX, and HC pollution on roads due to motor vehicle exhaust emissions. The device and the display system are made separately using wireless network communication to make this tool portable. Exhaust Gas Analyzer (EGA) was chosen for device calibration, obtaining 3.62% on the average error after performing 30 tests. The tests for measuring CO, CO2, NOX, and HC gas levels were conducted in several locations in Padang City and performed in the morning, afternoon, and evening. The result showed that the system properly measured CO2, CO, NOX and HC pollution in parks and highways in real-time in parts per million (ppm). It also displayed varied gas measurement results in terms of time and test location with a range of CO gas values at 0.034 – 0.15 ppm, CO2 151.3 – 815.2 ppm, NOX 0.0001 – 0.004 ppm, and HC 0.04 – 0.65 ppm. In addition, the system could perform well in providing warnings by automatically activating the air indicator alert at several measurement places when the gas content on one of the gas elements and compounds at a particular location has exceeded the threshold for the clean air category. Thus, this device can be used as initial research to build a real-time air pollution measurement system using the Internet of Things (IoT).

Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices.

Internet of Medical Things (IoMT) has emerged as an integral part of the smart health monitoring system in the present world. The smart health monitoring deals with not only for emergency and hospital services but also for maintaining a healthy lifestyle. The industry 5.0 and 5/6G has allowed the development of cost-efficient sensors and devices which can collect a wide range of human biological data and transfer it through wireless network communication in real time. This led to real-time monitoring of patient data through multiple IoMT devices from remote locations. The IoMT network registers a large number of patients and devices every day, along with the generation of huge amount of big data or health data. This patient data should retain data privacy and data security on the IoMT network to avoid any misuse. To attain such data security and privacy of the patient and IoMT devices, a three-level/tier network integrated with blockchain and interplanetary file system (IPFS) has been proposed. The proposed network is making the best use of IPFS and blockchain technology for security and data exchange in a three-level healthcare network. The present framework has been evaluated for various network activities for validating the scalability of the network. The network was found to be efficient in handling complex data with the capability of scalability.

Distributed Resource Allocation in RF-Powered Cognitive Ambient Backscatter Networks

Ambient backscatter communications has shown the great potentials to achieve spectrum and energy efficient communications for future wireless networks (e.g., 6G). Besides, to fully exploit the ambient RF environment, backscatter communications can be combined with RF-powered cognitive networks which brings more reliable and flexible communications. In such networks, a cognitive user pair could communicate through active transmission or backscattering existing signals. In this work, we investigate the distributed resource allocation in terms of channel selection and backscatter power allocation in such setting. A unified framework integrating stochastic geometry and evolutionary game is proposed to model and analyze the distributed resource allocation. Specifically, stochastic geometry is used to analyze the average performance for users considering different communication modes. Then with the average performance obtained, evolutionary game theory is used to model the competitive resource allocation, and replicator dynamics is used to capture the dynamic change of user selections. Based on the formulated evolutionary game, a distributed channel selection and backscatter power allocation algorithm is proposed. Simulations have been performed which validate the theoretical analysis. Also the effectiveness of the proposed scheme is verified.

UAV-Assisted Multi-Access Edge Computing: Technologies and Challenges

As the number of end users served by wireless networks continues to grow, modern wireless communication systems have put forward higher requirements for the diversity of wireless network forms. The unmanned aerial vehicle (UAV) wireless network communication system will occupy an important position in the future wireless communication system. With the explosive growth of 5G data traffic and Internet of Things (IoT) devices, computing-intensive, communication-intensive, and delay-sensitive applications have put tremendous pressure on UAV communication systems. Unlike terrestrial communication networks, the inherent characteristics of UAVs make it more troublesome to deal with the above-mentioned difficulties. Multi-access edge computing (MEC) can help mobile devices improve computing and communication capabilities, and its combination with UAVs is also an open subject. This article mainly summarizes the related knowledge and research of MEC and UAV wireless communication systems. We combine the UAV system with MEC technology and try to propose a UAV-assisted MEC wireless communication system. We analyze the key methods to realize this technology and point out a series of possible challenges. This article aims to provide new ideas for the proposed new architecture of aerial computing.

Distributed bare-bones communication in wireless networks

We consider wireless networks operating under the SINR model of interference. Nodes have limited individual knowledge and capabilities: they do not know their positions in a coordinate system in the plane, further they do not know their neighborhoods, nor do they know the size of the network n, and finally they cannot sense collisions resulting from simultaneous transmissions by at least two neighbors. Each node is equipped with a unique integer name, where N as an upper bound on the a range of names. We refer as a backbone to a subnetwork induced by a diameter-preserving dominating set of nodes. Let \(\Delta \) denote a maximum number of nodes that can successfully receive a message transmitted by a node when no other nodes transmit concurrently. We study distributed algorithms for communication problems in three settings. In the single-node-start case, when one node starts an execution and other nodes are awoken by receiving messages from already awoken nodes, we present a randomized broadcast algorithm that wakes up all nodes in \(\mathcal {O}(n \log ^2 N)\) rounds with high probability. For the synchronized-start case, when all nodes start an execution simultaneously, we give a randomized algorithm computing a backbone in \(\mathcal {O}(\Delta \log ^{7} N)\) rounds with high probability. In the partly-coordinated-start case, when a number of nodes start an execution together and other nodes are awoken by receiving messages from the already awoken nodes, we develop an algorithm that creates a backbone in time \(\mathcal {O}(n\log ^2 N +\Delta \log ^{7} N)\) with high probability

A survey on recent contention-free MAC protocols for static and mobile wireless decentralized networks in IoT

Medium Access Control (MAC) protocols for wireless decentralized networks in IoT have attracted a lot of attention in both academic and industrial fields. They aim to coordinate access among IoT devices to the shared wireless medium. More specifically, contention-free MAC protocols are known to be more efficient than contention-based ones in the case of high traffic load and dense networks. To face the main communication challenges between IoT devices such as collisions and conflicts as well as mobility, it is crucial to design an efficient MAC protocol. To do so, several solutions have been proposed in the literature. Among recent proposed solutions, Machine Learning (ML) algorithms and game theory models were used to revolutionize the communication in IoT networks, especially for devices with high mobility degree. In our survey, we first start by studying the challenges and requirements of communication in wireless networks. Then, we provide a comprehensive survey on recent contention-free MAC protocols existing in the literature. Next, we compare these solutions based on important metrics such as QoS, robustness, fairness etc., and discuss the relationship between MAC protocols, network type and network mobility. Finally, we investigate a future research direction to solve a major problem, which is the network disruption and delay tolerance in IoT wireless mobile networks.

URLLC Performance Under Outdated Channel State Information and Generalised-Rician Fading

Under ultra-reliable and low-latency communications (URLLC) for modern and future wireless networks, this work studies block-length-error probability (BLE) over an outdated-channel-state-information (oCSI) relay network deploying maximal ratio combining. Impact of finite-blocklength regimes on hybrid-automatic-repeat-request protocols with a finite pilot length is also studied. The network is operating under a generalised-Rician fading environment, which covers both line-of-sight (LoS) and non-LoS. The BLE is computed as a function of a bandwidth, payload, an oCSI coefficient, a diversity order and LoS power. Reliability-latency trade-off and effects of other parameters to URLLC performance are examined and discussed. Impact of system incoherence on URLLC performance will also be studied.

Research and Control of Underground Pressure Law of Coal Mining Face in Soft Rock Strata Based on Neural Network under the Background of Wireless Network Communication

Our country has a vast territory and rich resources, but it is a country with more coal, less oil, and poor gas. With the increase of our population, the development of society, and the more severe international situation, coal has become more important for our country’s economic development and energy. Security plays an irreplaceable role. Based on the neural network, this paper studies and controls the underground pressure law of the coal mine’s soft rock heading face, aiming at the safe and efficient mining of the first face and providing an experience for the next face. This paper mainly uses BP neural network learning algorithm and support pressure algorithm to measure and study the ground pressure law of coal mine soft rock heading face and establishes the ground pressure online monitoring system, which is used to analyze and summarize the ground pressure abnormal area during the mining of the working face, so as to provide the basis for safe mining of the working face. Through the field measured data, the initial pressure step and periodic pressure step at the upper, middle, and lower parts of the working face, the average working resistance of the support at the working face during pressure, and the dynamic load coefficient of the support are obtained. It is analyzed that the support in the middle of the working face has a large load and the pressure is obvious. The experimental results show that the initial support force of the whole working face is approximately normally distributed, the proportion of the initial support force in the range of 10–30 MPa accounts for more than 85% of the total statistics, and the frequency of the initial support force in the upper, middle, and lower stations at 10–25 MPa is 55%–65%.

Emotional Computing and Emotional Measurement Methods based on Intelligent Algorithms of Wireless Network Communication

Emotion has always been a complex psychological and physiological phenomenon of people. In order to solve the problem of emotional calculation and emotional measurement methods, it will make people's research and understanding of emotion more meaningful in the future. This article aims to study the research of emotional computing and emotional measurement methods based on intelligent algorithms for wireless network communication. This paper proposes a modelling algorithm of physiological signal emotion based on random forest and LDA. After extracting the general features and proprietary features of the signal, the random forest algorithm is used to calculate the importance of these features under different labels, and the effective features are selected from all the features according to the order of importance. This article also realizes the process of establishing a complete emotional material database and physiological emotional database. Through multiple steps such as signal screening, material selection, emotion annotation and physiological data collection, the problem of missing physiological emotion database is solved. Experimental data shows that compared with other low-level feature classification, the recognition rate of the fusion method in this paper is 57.37% higher than other algorithms, the recognition rate of other behaviours is increased by 4.35%.

Integrate the hierarchical cluster elliptic curve key agreement with multiple secure data transfer modes into wireless sensor networks

Since sensor nodes in wireless sensor networks or Internet of things have limited resources, achieving secure data transmissions among nodes is a challenge. Hence, efficient key management schemes with lightweight ciphers are essential. Many asymmetric keys or public key mechanisms have been developed. However, they are unsuitable for secure group communications in wireless sensor networks, because sensor nodes are usually devoid of sufficient memory, CPU and bandwidth to deal with complex operations. In addition, only a few group key agreements are integrated into secure data transmissions. Therefore, a key agreement using the hierarchy-based cluster elliptic curve key agreement named HCECKA is proposed in this study to deal with secure data transmissions in wireless sensor networks. The presented security mechanism relies on elliptic curves instead of logarithmic curves, and utilises a lesser key length to accomplish similar security classification than Diffie-Hellman and Rivest Shamir Adleman cryptosystems. Simultaneously, the proposed scheme provides a rapid, efficient and dynamic group key synchronisation technique in plenty of sensor nodes with no need for reorganising the whole system key if members join or leave wireless sensor networks.

An English Mobile Learning Platform Embedded in GSM-R Wireless Network Communication

English mobile learning platform is affected by external interference signals, resulting in poor remote transmission ability of English information. To solve this problem, a design of the English mobile learning platform based on the GSM-R wireless network communication system is proposed. The overall framework of the English mobile learning platform is designed. MSP430F149 single-chip microcomputer is selected as the hardware microcontrol unit of the platform, and R-C reset circuit is designed. The reset circuit is used to reset the single-chip microcomputer platform to prevent external signal interference. The modem is initialized according to AT instruction, and the main program flow of the single-chip microcomputer of the English mobile learning platform is designed on this basis. GSM-R wireless network communication system is used to plan the course module. After planning, the platform operation management function is designed, the interactive learning environment is established, the user information template is designed, and the platform database is built. The experimental results show that the designed English mobile learning platform can meet the learning needs and improve students’ comprehensive ability after application.

Design of English Mobile Learning Platform Based on GSM-R Wireless Network Communication System

Because the traditional English mobile learning platform has low student satisfaction and a long learning time, an English mobile learning platform based on the GSM-R wireless network communication system is designed. A GSM-R wireless network communication system is built through existing facilities, new facilities, and business-side facilities. Platform function modules are designed based on the communication system, including course resource management module, online examination management module, online Q&A management module, platform management module, and user login. Based on this module, the platform software is designed according to the three steps of database design, platform encryption technology, and learning recommendation algorithm to create the English mobile learning platform. The simulation experiment results show that the application of the designed platform can improve student satisfaction and improve student learning efficiency.

A low‐profile dual‐band multimode patch antenna for wireless local area network and cellular vehicle‐to‐everything communications

In this article, a low-profile dual-band patch antenna for vehicle communication is proposed. With two sets of shorting vias on the hexagonal-shaped patch at different positions and single feed at the center, three different resonant modes are excited, forming two operating bands with omnidirectional and conical beam radiation respectively. The omnidirectional radiation at 2.45 GHz is used for wireless local area network (WLAN) communication while the conical beam radiation is used for cellular vehicle-to-everything (C-V2X) communication. The proposed antenna is fabricated using the printed circuit technique. Both the measured reflection coefficient and radiation pattern match well with the simulations. With the advantage of low profile, dual-band, and dual radiation characteristics, the antenna owns a good potential to be used in vehicle communications.

Network Communication Data Encryption Method Based on Wireless Channel Characteristics

In order to improve the secure transmission capability of wireless transmission network communication data, a network communication data encryption design is required. An encryption and secure transmission method of wireless transmission network communication data based on wireless channel feature detection is proposed. The ECC (Elliptic Curves Cryptography) algorithm analyzes by monitoring single-channel and multi-channel samples separately. The ciphertext protocol for data secure transmission is constructed, the Hash dynamic transmission protocol is used for data access control, the data dynamic symmetric key, the key construction and arithmetic coding design are constructed. Combined with the ellipse linear mapping method, the data is encrypted safely. According to the intensity of the wireless channel feature distribution, the scrambling degree is rearranged for the random scrambling and encryption of the data, and the random linear coding method is used to realize the random scrambling and encryption of the data, so as to realize the secure transmission of network communication data and the secure storage of information. The simulation test results show that using this method to encrypt and transmit wireless transmission network communication data has better security and stronger anti-attack ability, thereby improving the secure transmission performance of network communication data.

Game Theoretic Approach to Enhancing D2D Communications in 5G Wireless Networks

Game Theoretic Approach to Enhancing D2D Communications in 5G Wireless Networks

TD-DAQ: A low-cost data acquisition system monitoring the unsaturated pore pressure regime in tailings dams

Tailings dams are large, often self-contained, storage facilities of mine residue. On self-contained tailings dams the tailings material itself is used to raise the containment embankments holding newly deposited residue. To develop the necessary strength, it is essential that material must dry out sufficiently. Despite substantial advancements in the field of instrumentation, these parameters are rarely measured on tailings dams and their evolution over time is poorly understood. Understanding the role of pore water suction and water content evolution over time can benefit from the installation of sensors and data acquisition systems (DAQ) capable of continuously monitoring these parameters. Such monitoring remains difficult and expensive owing to the challenges of measuring negative water pressures and the often-remote locations and harsh operating environments typical of mining operations. This paper describes the development, testing and validation of a low-cost DAQ for the measurement of the unsaturated pore pressure regime in a platinum tailings dam located in the Limpopo province of South Africa. The Tailings Dam DAQ (referred to as TD-DAQ) is designed to measure the negative pore pressure, moisture content and temperature in fine-grained material over extended periods of time. These measurements are stored on the DAQ and transmitted in parallel using new wireless network communications technologies (Sigfox) suited to remote, battery powered applications. The successful deployment of the TD-DAQ presents a real-time, low-cost instrumentation solution to improve the efficiency of condition monitoring of tailings storage facilities, contributing to a reduction in the probability of failure events.