Solution For Wireless Networks Research Articles

Selecting Outdoor Wireless Solution for Bara Prima Borneo Using Analytic Hierarchy Process

The advancement of wireless communication technology is critical for improving the efficiency, safety, and productivity of mining operations. This study focuses on evaluating and recommending an optimal outdoor wireless network solution for Bara Prime Borneo (BPB) mining operations in East Kalimantan, Indonesia, using the Analytic Hierarchy Process (AHP) for decision-making. The current Wi-Fi infrastructure faces significant challenges, including limited coverage, interference, and scalability issues, which hinder its effectiveness in the demanding mining environment. To address these challenges, the study employs a comprehensive approach to identify stakeholder expectations and value perceptions, explore alternative wireless network designs such as Private LTE and Kinetic Mesh, and systematically select the most suitable solution using AHP. Through discussions with subject matter experts and secondary data collection, the study outlines the strengths, weaknesses, opportunities, and threats (SWOT) associated with the existing Wi-Fi network and potential alternatives. Using AHP, the study prioritizes various criteria such as coverage, reliability, cost, scalability, and security. The recommended design aims to bridge the gap between current capabilities and future needs, ensuring robust and extensive network coverage that supports various digital applications essential for modern mining. By selecting the proposed solution using AHP, BPB can achieve a more reliable and scalable wireless network, enhancing overall operational efficiency and safety while meeting the evolving demands of its mining operations.

An energy-efficient JT-CoMP enabled framework with adaptive OMA/NOMA in HetNets

The increasing demand for higher data rates and improved energy efficiency (EE) in next-generation wireless networks necessitates the optimized selection of multiple-access and coordination techniques. A hybrid joint transmission (JT)-coordinated multi-point (CoMP) enabled orthogonal multiple access (OMA)/non-orthogonal multiple access (NOMA) technique, combining the spectral efficiency (SE) and capacity benefits of CoMP NOMA with the interference mitigation of CoMP OMA, offers a highly adaptable solution for future wireless networks. This paper studies the joint optimization of CoMP/non-CoMP selection, OMA/NOMA selection, power allocation, and user pairing, with the objective of maximizing the EE in the network. A Dynamic CoMP user selection with energy-efficient adaptive multiple access (DCEAMA) algorithm to solve the formulated problem is proposed. Our Monte Carlo simulations show that the DCEAMA surpasses both the pure CoMP OMA and CoMP NOMA schemes in terms of EE, with an average increase of 38% and 26% respectively. We compare our heuristic technique to an exhaustive search strategy to evaluate its efficiency. The findings indicate that our strategy produces comparable EE across various power levels with reduced computational complexity.

Rate splitting with semantics as a generalized multi-access framework for intelligent reflecting surfaces

The rapid advancement of modern communication technologies necessitates the development of generalized multi-access frameworks and the continuous implementation of rate splitting, augmented with semantic awareness. This trend, coupled with the mounting pressure on wireless services, underscores the need for intelligent approaches to radio signal propagation. In response to these challenges, intelligent reflecting surfaces (IRS) have garnered significant attention for their ability to control data transmission systems in a goal-oriented and dynamic manner. This innovation is largely attributed to equitable resource allocation and the dynamic enhancement of network performance. However, the integration of rate-splitting multi-access (RSMA) architecture with semantic considerations imposes stringent requirements on IRS platforms to ensure seamless connectivity and broad coverage for a diverse user base without interference. Semantic communications hinge on a knowledge base-a centralized repository of integrated information related to the transmitted data-which becomes critically important in multi-antenna scenarios. This article proposes a novel set of design strategies for RSMA-IRS systems, enabled by reconfigurable intelligent surface synergizing with semantic communication principles. An experimental analysis is presented, demonstrating the effectiveness of these design guidelines in the context of Beyond 5G/6G communication systems. The RSMA-IRS model, infused with semantic communication, offers a promising solution for future wireless networks. Performance evaluations of the proposed approach reveal that, despite an increase in the number of users, the delay in the RSMA-IRS framework incorporating semantics is 2.94% less than that of a RSMA-IRS system without semantic integration.

Optimal channel selection for tri-band Wi-Fi in a residential scenario

The growing use of Internet of Things devices and the increasing demand for high-speed, reliable, and secure wireless connectivity pose significant challenges for existing wireless networking solutions in modern smart homes. As such, there is an increasing urgency for the development of advanced and effective wireless technologies that can fulfil the new requirements for interconnected devices and services deployed in households. Tri-band Wi-Fi 6E equipment addresses these needs by reducing the network congestion and enhancing the performance across the 2.4 GHz, 5 GHz, and 6 GHz bands. However, improper band management can lead to frequent interference and network issues. As such, this work introduces a dynamic Wi-Fi link orchestration solution that follows a heuristic model. This approach aims to optimize the network layout and channel allocation based on device metrics, utilizing the EasyMesh specification for simplified network setup and management. The model was implemented and tested in a residential environment network, using EasyMesh and tri-band Wi-Fi 6E devices. Results show the effectiveness of the model in improving network capacity and adapting the links to the current traffic, outperforming the initial and base network configuration.

Multifunction Robot for Reducing Sensors Count in Greenhouse Monitoring

Abstract: Over the years, greenhouse systems have been utilized to regulate the ambient conditions of precious crops in an effort to increase agricultural productivity. The crucial elements of a typical greenhouse are the construction of a polyhouse, the placement of artificial lighting, the careful use of vents, watering methods, and the calculated application of insecticides and pesticides, among other things. Numerous factors are crucial for optimum plant development, including soil moisture, temperature, humidity, light intensity, greenhouse layout, and plant spacing. Various monitoring and control methods have been suggested and put into practice for automated greenhouses throughout the years. For parameter monitoring in different plots of a green house, a number of sensors are often needed in green house automation. The interface between these sensors and the monitoring device is crucial. In exchange for a fee, several wired and wireless sensor networking solutions are being tested. This paper focuses on adopting a robotic approach to reduce the sensor count in the automated greenhouse system. The need of multiple sensors is eliminated as the robot can move across the greenhouse to collect data at required locations.

A Comparative Analysis of Energy Consumption in Various Wireless Sensor Network Techniques

The objective of this study is to analyze the energy consumption associated with modern methodologies utilized in wireless sensor networks and to conduct a comparative assessment with Reed Solomon (RS) codes. This paper presents three discrete techniques for wireless sensor networks. The strategies mentioned include the Self-Evolving Sensor System (SESS), the Secure and Adaptive Key Management utilizing Multipath Routing Protocol (SAKM-MRP), and the National Instruments Secure Reference-based Data Aggregation (NI-SRDA). A distinct algorithm was developed for each method to examine the energy use. Based on the experimental results, it has been shown that the RS-codes approach consumes a considerably greater quantity of energy compared to the SESS methods, which, in contrast, exhibit a significantly lower energy consumption. When comparing the efficiency of RS-codes and SESS methods, it is observed that the SAKN-MRP technique exhibits a more significant decrease in energy consumption. Compared to the RS-Codes system, the SESS scheme stands out with a significant 45.5% reduction in energy usage at the maximum delivery node. Similarly, the SAKM-MRP scheme showcases an average decrease of 35.7% in energy consumption. Notably, the NI-SRDA scheme achieves an impressive 60% reduction in energy consumption, underscoring its remarkable impact on energy efficiency. In a broader sense, it can be inferred that the NI-SDRA technique holds promise as an energy-efficient solution for wireless sensor networks in comparison to alternative strategies suggested in the current study.

5G on the Farm: Evaluating Wireless Network Capabilities and Needs for Agricultural Robotics

Global food security is a critical issue today, strained by a wide range of factors including global warming, carbon emissions, sociopolitical and economic challenges, traditional workforce decline and population growth. Technical innovations that address food security, like agricultural robotics, are gaining traction in industry settings, moving from controlled labs and experimental test facilities to real-world environments. Such technologies require sufficient network infrastructure to support in-field operations; thus, there is increased urgency to establish reliable, high-speed wireless communication networking solutions that enable deployment of autonomous agri-robots. The work presented here includes two contributions at the intersection of network infrastructure and in-field agricultural robotics. First, the physical performance of a private 5G-SA system in an agri-robotics application is evaluated and in-field experimental results are presented. These results are compared (using the same experimental setup) against public 4G and private WiFi6 (a newly emerging wireless communication standard). Second, a simulated experiment was performed to assess the “real-time” operational delay in critical tasks that may require quick turnaround between in-field robot and off-board processing. The results demonstrate that public 4G cannot be used in the agricultural domain for applications that require high throughput and reliable communication; that private 5G-SA greatly outperforms public 4G in all performance metrics (as expected); and that private WiFi6, though limited in range, is a fast and very reliable alternative in specific settings. While a single wireless solution does not currently exist for the agricultural domain, multiple technologies can be combined in a hybrid solution that meets the communications requirements.

TD3-Based Optimization Framework for RSMA-Enhanced UAV-Aided Downlink Communications in Remote Areas

The need for reliable wireless communication in remote areas has led to the adoption of unmanned aerial vehicles (UAVs) as flying base stations (FlyBSs). FlyBSs hover over a designated area to ensure continuous communication coverage for mobile users on the ground. Moreover, rate-splitting multiple access (RSMA) has emerged as a promising interference management scheme in multi-user communication systems. In this paper, we investigate an RSMA-enhanced FlyBS downlink communication system and formulate an optimization problem to maximize the sum-rate of users, taking into account the three-dimensional FlyBS trajectory and RSMA parameters. To address this continuous non-convex optimization problem, we propose a TD3-RFBS optimization framework based on the twin-delayed deep deterministic policy gradient (TD3). This framework overcomes the limitations associated with the overestimation issue encountered in the deep deterministic policy gradient (DDPG), a well-known deep reinforcement learning method. Our simulation results demonstrate that TD3-RFBS outperforms existing solutions for FlyBS downlink communication systems, indicating its potential as a solution for future wireless networks.

Application of corporate image integrating Zigbee technology in brand APP interface design using IoT technology

In modern social APP interface design, how to effectively improve the corporate image and create the connotation of corporate culture is a significant key problem. With the emergence of APP, a growing number of people use them, increasing communication energy usage and slowing network operation. To improve app compatibility and speed, it is necessary to combine it with the most advanced and dependable technology, such as ZigBee, which is regarded as the best solution for wireless sensor networks. The ZigBee protocol is primarily used to incorporate working and data transmission in wireless sensor networks that are based on ZigBee technology. As a result, incorporating ZigBee technology into APP interface design in the Internet of Things (IoT) domain can significantly improve brand APP interface design’s network operation efficiency. This paper presents a novel approach to enhance the performance and corporate image of brand mobile applications (APPs) by integrating ZigBee technology. The primary objective is to improve the operating efficiency and user experience of the brand APPs. The study involves a comparison between 10 brand APPs that have not integrated ZigBee technology and 10 brand APPs that have adopted ZigBee technology. The experimental results indicate that the operating efficiency of the brand APPs incorporating ZigBee technology is 97%, while the efficiency of the brand APPs without ZigBee technology is 85%, resulting in a notable difference of 12%. To assess the effectiveness of ZigBee technology integration, the study conducted experiments with 100 users, randomly assigned to interact with both types of brand APPs. The user feedback and observations revealed that brand APPs integrated with ZigBee technology exhibit significantly higher operating efficiency, contributing to a 12% improvement over their counterparts lacking ZigBee integration. Moreover, 90 out of 100 users reported a preference for the brand APPs integrated with ZigBee technology due to their superior user experience. The integration of ZigBee technology in brand APPs not only enhances the user experience but also contributes to the improvement of the company’s corporate image. Adopting ZigBee technology in brand APPs is a valuable strategy that can facilitate the long-term development and success of the company.

A variable damping vibration energy harvester based on Half-Wave flywheeling effect for freight railways

The vibrational energy, often considered a negative factor, is abundant in everyday life. Especially in railway systems, the negatively impacted track vibrations resulting from moving trains can be captured to provide a practical power supply solution for wireless sensor networks. This paper proposed a variable damping vibration energy harvester with a half-wave flywheel for a freight train-based railway. A double-sided rack as the input member converts the track vibration into the opposite rotation of the two pinions, which are then transmitted to the two parallel shafts respectively. According to the work characteristics of the one-way bearing, the upper and lower vibrations can be collected separately and output a one-way rotation to the generator module. The proposed harvester with a half-wave flywheel features a larger damping force for vibration reduction during the downward track vibration and a smaller damping force conducive to returning the track's original state during the upward track vibration. The experimental results achieve a maximum output power of 10.247 W and a maximum mechanical efficiency of 74.49%. Both simulations and experiments have verified that the proposed system with a half-wave flywheel can increase the damping force in the vibration reduction process and reduce the damping force in the reset process, which is characteristic of improving its power generation performance with a good vibration reduction effect. The VEH with the half-wave flywheel achieved an average power of 5.321 W at the train speed of 90 km/h under random vibration testing, which verifies the feasibility of self-powered wireless sensor networks in railway environments.

Design methodology for reconfigurable multi-radio platform for future generation wireless systems

Owing to the continuous development of technology, the future generation of wireless communication systems is increasingly becoming more complex to support a spectrum of new and existing services and standards. Consequently, the need for flexible and adaptable radios has become more prominent. Radio signals can be modulated using various methods. Radio modulation recognition refers to a series of processes for acquiring information regarding modulation types of non-cooperative received signals. It plays an important role as a pre-demodulation process required to ensure accuracy, safety, and effectiveness in recovering information. This study proposed a reconfigurable multi-radio platform comprising a reconfigurable antenna and receiver board. The antenna was reconfigurable to facilitate operation in different frequency bands controlled via the receiver board using bias voltages. The receiver board was programmable using custom-built software. Moreover, it can detect the modulation scheme and accurately demodulate signals that are modulated in one of three common modulation schemes: amplitude modulation, frequency modulation, and phase modulation. This solution offers the advantages of reduced size, cost, and power consumption because it uses one hardware system as opposed to the deployment of several individual radios. Moreover, the platform presents an adaptable, cost-effective solution for future-generation wireless networks and a flexible and robust terminal that can operate under changing communication environments.

Automatic Spike Neural Technique for Slicing Bandwidth Estimated Virtual Buffer-Size in Network Environment

The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modified to achieve QoS using Artificial Intelligence (AI) and machine learning (ML). Developing an intelligent decision-making system for network management and reducing network slice failures requires reconfigurable wireless network solutions with machine learning capabilities. Using Spiking Neural Network (SNN) and prediction, we have developed a 'Buffer-Size Management' model for controlling network load efficiency by managing the slice's buffer size. To analyze incoming traffic and predict the network slice buffer size; our proposed Buffer-Size Management model can intelligently choose the best amount of buffer size for each slice to reduce packet loss ratio, increase throughput to 95% and reduce network failure by about 97%.

The Diverse Technology of MANETs: A Survey of Applications and Challenges

In recent years, mobile ad hoc networks (MANETs) have shown much potential in providing wireless network solutions for a variety of situations. MANETs are made up of a variety of devices (both mobile and internet of things (IoT)) which form a wireless network that provides wireless network functionality and cloud services and can be used to provide wireless services to devices in areas where fixed infrastructure is not accessible. Although it is not necessary for a node to be connected to fixed wireless or cellular infrastructure for the network, even a single node connected to infrastructure opens up a wide range of new research opportunities and applications. Due to the variety of compatible devices, MANETs are the perfect technology for a wide variety of scenarios, such as: military, search and rescue operations, and more. Our contribution is a complete survey of the applications of MANETs, which to our knowledge has not been previously documented. This survey will discuss the industries MANETs are used in (e.g. education, smart city, etc.), the benefits and services they can provide users, and will also explore the challenges this technology still experiences

Backscatter‐assisted Non‐orthogonal multiple access network for next generation communication

AbstractNon‐orthogonal multiple access (NOMA) technique introduces spectrum cooperation among different users and devices, which improves spectrum efficiency significantly. Energy‐limited devices benefit from the backscatter (BAC) technique to transmit signals without extra energy consumption. The combination of NOMA and BAC provides a promising solution for Internet of Things (IoT) networks, where massive devices simultaneously transmit and receive signals. This study investigates a system model with two NOMA downlink users and an uplink device. The aim is to maximise the data rate of the uplink device by optimising the power allocation coefficient and the backscattering coefficient. Meanwhile the quality of service requirements of two NOMA users are guaranteed. The closed‐form solution of two optimisation variables is derived, and an alternating algorithm is also proposed to solve the formulated optimisation problem efficiently. The proposed system verifies the feasibility of IoT devices being added into existing networks and provides a promising solution for wireless communication networks in the future.

IoT-based Hybrid Wireless Network for Tourist Boat Tracking towards Smart Cities

Moving and transporting by canoe and boat on rivers and canals is a cultural feature of the Mekong Delta and plays an important role in the economy and society. However, the management and use of equipment to support the monitoring of waterway transport vehicles in this area has yet to receive adequate investment and attention. Given the complicated evolution of the COVID-19 epidemic, it is critical to strengthen oversight of inland waterway management, as well as freight and passenger transportation. This paper presents the design and implementation of an IoT-based support system for managing and monitoring passenger ships and tourism activities in smart cities. This study proposes a hybrid wireless communication network solution that takes advantage of the strengths of LoRa and Zigbee wireless communication technologies, as well as telecommunication networks, to ensure that the system has a wide operating range of several kilometers, low power consumption, and can be deployed in areas where telecommunications are not available. Aside from tracking the journey and managing information about vehicles, drivers, and passengers, the system also aids in the collection of environmental parameters along river routes according to the travel route. An experimental evaluation of the system's operation was carried out for the tourist boat route between two famous tourist sites, Ninh Kieu Key and Cai Rang floating market in Can Tho city, Vietnam.

Genetic algorithm‐based partial charging schedule of rechargeable sensor networks

SummaryThe use of rechargeable sensors is a promising solution for wireless sensor networks. On this type of network, mobile charging vehicles (MC) are used for charging sensors using wireless energy transfer (WET) technology. In on‐demand charging, a sensor transmits a charging request to the service station, and the MC visits the sensor to transfer energy. The key disadvantages of utilizing MC‐based WET are its high energy expenditure rate due to mobility, long service time, and slow charging rate. Because of these reasons, sensors deplete their energy and become dead before the MC reaches the requesting nodes to recharge. We have adapted a genetic algorithm‐based partial charging scheme to serve the charging requests. Our objective is to improve the survival ratio of the network. Using comprehensive simulations, we analyze the performance of our proposed method and compare it to two other existing approaches. The simulation results demonstrate that our proposed algorithm improves the survival ratio by up to 20 % by developing a dynamic energy threshold function for transmitting charging requests from the sensors and a partial charging schedule using a genetic algorithm.

Unmanned-Aerial-Vehicle-Assisted Wireless Networks: Advancements, Challenges, and Solutions

The rapid development of communication and computing techniques enables unmanned aerial vehicles (UAVs) to provide reliable and cost-effective wireless communication and computing services from the air. Compared to the conventional fixed infrastructure, UAVs have attractive attributes, such as high flexibility and operability, and, as a result, on-demand line-of-sight connection links. Therefore, UAV-assisted wireless networks have been envisioned as a promising paradigm to achieve enhanced coverage and connectivity for future wireless communications. Meanwhile, achieving high levels of energy efficiency, sensing, communication, and computing capacities, and security and privacy are critical to the success of UAV-assisted wireless networks. In order to improve the performance of UAV-assisted wireless networks, some frameworks and mechanisms have been developed in the past few years. In this article, we provide a comprehensive survey of these developments. Specifically, we conduct a brief overview for the architecture of UAV-assisted wireless networks from four domains (i.e., framework-related, technology-related, challenge-related, and solution-related) and four aspects (i.e., sensing-related, communication-related, computing-related, and application-related). Then, the integrated sensing, communication, and computing for UAV-assisted wireless networks is introduced, followed by the characteristics and requirements. We also provide the implementation and applications of UAV-assisted wireless networks. Next, we discuss the challenges and the state-of-the-art solutions for UAV-assisted wireless networks. Finally, the advanced technologies for UAV-assisted communication and computing networks are exploited, followed by the potential research directions.

Development of a search and rescue robot system for the underground building environment

AbstractThe underground building environment plays an increasingly important role in the construction of modern cities. To deal with possible fires, collapses, and so on, in underground building space, it is a general trend to use rescue robots to replace humans. This paper proposes a dual‐robot system solution for search and rescue in an underground building environment. To speed up rescue and search, the two robots focus on different tasks. However, the environmental perception information and location of them are shared. The primary robot is used to quickly explore the environment in a wide range, identify objects, cross difficult obstacles, and so on. The secondary robot is responsible for grabbing, carrying items, clearing obstacles, and so on. In response to the difficulty of rescue caused by unknown scenes, the Lidar, inertial measurement unit and multiview cameras are integrated for large‐scale 3D environment mapping. The depth camera detects the objects to be rescued and locate them on the map. A six‐degree‐of‐freedom manipulator with a two‐finger gripper is equipped to open doors and clear roadblocks during the rescue. To solve the problem of severe signal attenuation caused by reinforced concrete walls, corners and long‐distance transmission, a wireless multinode networking solution is adopted. In the case of a weak wireless signal, the primary robot uses autonomous exploration for environmental perception. Experimental results show the robots' system has high reliability in over‐the‐horizon maneuvering, teleoperation of the door opening and grasping, object searching, and environmental perception, and can be well applied to underground search and rescue.

Deep Learning-Based Channel Estimation for Double-RIS Aided Massive MIMO System

Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for future wireless communication networks due to its fast and low-cost configuration. In this letter, we consider the estimation of cascaded channels in a double-RIS aided massive multiple-input multiple-output system, which is a critical challenge due to the large number of antennas equipped at the base station and passive RIS elements. To tackle this challenge, we propose a skip-connection attention (SC-attention) network that utilizes self-attention layers and skip-connection structure to improve the channel estimation performance from the noisy pilot-based observations. Simulation results compare the proposed SC-attention network with other benchmark methods and show that SC-attention network can effectively improve the accuracy performance on normalized mean square error (NMSE) for cascaded links in a double-RIS aided system.

Smart Governing System Based on Mesh Algorithm for Industrial Gas and Flame Detection with Alert System

The paper proposes a Wireless Sensor Network (WSN) solution for monitoring environmental parameters during industrial fires. The system includes sensors that collect real-time data on temperature ,humidity, and gas emissions. When the system detects a fire orgas out break ,it generates alerts and presents the data on a single webpage for easy visualization by first responders. The solution aims to provide near real time alerting, enabling prompt response to minimize the impact of industrial fires. The paper also presents experimental analysis of sensor node behavior during a fire in a test set-up, which demonstrated the effectiveness of the system in detecting fire outbreaks and generating alerts promptly. The proposed system has the potential to reduce the impact of industrial fires, including loss of human lives, vegetation, economic loss ,and environmental pollution.