Design Of Wireless Networks Research Articles

Error performance of DF cooperative SMTs with I/Q imbalance over Beckmann fading channels

The direct down-conversion principle, which has generally been used in the design of multiple-input multiple-output (MIMO) schemes, including space modulation techniques (SMTs), is attractive to researchers because of its low cost, low power consumption with fewer components, flexible and simple structure. However, hardware imperfections such as in-phase (I) and quadrature-phase (Q) imbalance (IQI) negatively affect the performance of the systems with direct down-conversion in practice. On the other hand, cooperative communication is a promising technology that can be utilized in the design of future wireless networks due to its significant advantages such as increasing system reliability, extending network coverage, reducing channel degradation, and providing high quality of service. In this study, SMT-based methods are integrated into cooperative systems, and a flexible and comprehensive model is presented that is applicable to many channel structures. Specifically, the error performance analysis of space shift keying (SSK), spatial modulation (SM), and quadrature SM (QSM) systems in the presence of IQI in decode-and-forward (DF) cooperative communication is carried out by analytical derivations and computer simulations over generalized Beckmann fading channels. The obtained results show that the performance of SMT-based DF cooperative systems is superior to the conventional schemes, and the effects of receiver IQI can be eliminated by optimal detector designs.

Regulatory and spectrum policy challenges for combined airspace and non-terrestrial networks

The recent advancements in the aviation and space industries facilitate new types of users in the sky, e.g., electrical vertical take-off and landing (eVTOL) aircraft. To unlock the full potential of these innovations, it is crucial to create interconnected three-dimensional networks that integrate airspace and non-terrestrial networks (NTNs) with their terrestrial counterparts, also known as Combined Airspace and Non-Terrestrial Networks (ASN). Combined ASN needs a flexible and adaptive network architecture with multiple, and partly converging technologies, such as air-to-ground, satellite, and high-altitude platforms, with a focus to cover both ground and aerial users. In addition to technical challenges, spectrum policy and regulatory aspects will affect the wireless network design and management schemes in three-dimensional space. Hence, this paper introduces regulatory and spectrum policy challenges posed by the development of combined ASN. This paper investigates a hypothetical urban air mobility use case with an eVTOL aircraft that operates as a flying taxi.

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.

Stability Analysis through a Stability Factor Metric for IQRF Mesh Sensor Networks Utilizing Merged Data Collection.

This paper introduces a novel stability metric specifically developed for IQRF wireless mesh sensor networks, emphasizing flooding routing and data collection methodologies, particularly IQRF's Fast Response Command (FRC) technique. A key feature of this metric is its ability to ensure network resilience against disruptions by effectively utilizing redundant paths in the network. This makes the metric an indispensable tool for field engineers in both the design and deployment of wireless sensor networks. Our findings provide valuable insights, demonstrating the metric's efficacy in achieving robust and reliable network operations, especially in data collection tasks. The inclusion of redundant paths as a factor in the stability metric significantly enhances its practicality and relevance. Furthermore, this research offers practical ideas for enhancing the design and management of wireless mesh sensor networks. The stability metric uniquely assesses the resilience of data collection activities within these networks, with a focus on the benefits of redundant paths, underscoring the significance of stability in network evaluation.

Post Study Design of Wireless Network for the Water Dilemma in the city of Rujban

Providing water for daily life usage is one of the biggest obstacles facing the growth and development of cities not only in Libya but in many countries of the world. The city of Rujban faces this crisis despite the passage of more than five decades in trying to resolve this issue. We did some deep research and study on the water system operation problem which we divided into three parts: Karthoom Automated Control System (KACS), Idref Automated Control System 1(IACS1), Idref Automated Control System 2 (IACS2) because water is pumped on 3 different stages. The IACS1 consists of two main parts: transmitter/collector tank on one side and receiver / pumps on the other side. The transmitter end consists of a microcontroller, three stage level sensor, two water flow sensors and an RF transmitter. The other end consists of two water pumping pump and an RF receiver. The system will be automated by the use of a microcontroller in which each level of the collector tank will be designed to turn on just one or both pumps of in the case there is certain amount of water, which can be determined by water level sensor, in Karthom collection tank. A crucial part of this coordination is the flow meter which will indicate if the pump is operational or not and detect whether or not there is water leakage, all of which will be demonstrated on an LCD screen. In this paper, we will design a wireless communication network for IACS1.

Nominal GSM-R Radio Network Design for Signalling and Train Control Systems: Case Study Dar-Moro Electrified SGR Line in Tanzania

The recent development of High-Speed Trains (HST) operations requires real-time information transfer, high network capacity, and reliable communication for train signalling and control purposes. Rail operators face challenges as the high-speed railroad traffic grows. In a high-speed driving profile, the communication must be able to overcome fast handover, large Doppler shift, high penetration losses, limited visibility in tunnels, and the harsh electromagnetic environment. Global System for Mobile Communications for Railway (GSM-R) is still a standard-bearer for railway signalling communications. The link capacity and coverage prediction of the predefined Base Transceiver Station (BTS) locations are simulated using the Radio Planner RF planning tool and Matlab®. The terrain map and the signal levels along the railway corridor are observed. The analysis of the GSM-R for a fast-moving train is performed. Signal level coverage prediction, Doppler-shift effect and the received carrier frequencies due to Doppler shift along Dar–Pugu stations have been presented. The critical sites (locations) with weak signals of the first three BTSs have been identified. It is also observed that the Doppler effect may limit the proposed speed.

Multitier scalable clustering wireless network design approach using honey bee ratel optimization

Wireless sensor networks (WSNs) have emerged as a one of the most fascinating areas of lookup in the past few years principally due to its massive quantity of workable applications. However limited energy, node deployment strategy, routing techniques has considerable impact on the overall performance of network. This paper proposes sustainable honey bee ratel based hybrid wireless sensor network (SHHWSN) layering framework for improving load balancing and scalability issues in network. In SHHWSN tessellated hexagonal shape clusters are formed to cover entire geographical region without any gaps. Hybrid routing schema constrained with redundant data identification policy used in this, seeks to optimize energy utilization. The proposed SHHWSN was evaluated and validated by simulation, and the results were compared with earlier schematics where mostly one sided stochastic node deployments were followed. The experimental results show that SHHWSN has superior performance in terms of network alive nodes, delay, energy and throughput. The proposed SHHWSN obtained values of 50 nodes is 3, 0.061, 0.14, 0.89, 100 nodes is 3,0.037, 0.19, 0.551, 150 nodes is 13, 0.081, 0.23, 0.415, and 200 nodes is 23, 1.01, 0.25, 0.356, which is significantly more effective than current techniques.

Resource allocation of cognitive relay networks under continuous transmission mechanism

This paper considers the joint power allocation, path selection and subcarrier pairing design of cognitive radio cooperative networks, where the transmission power of secondary users is limited by its own power budget and the tolerable interference threshold of primary users. In particular, a continuous transmission mechanism rather than intermittent emission, leading to severe signal interference between primary and secondary users, as well as mutual interference between secondary users, is taken into account. This cooperative cognitive radio network is seen as an improvement in the sense that the source transmitter can continuously transmit symbols without silence. Although traditional cooperative network technology has long been applied to the cognitive radio field and it has been proposed to allow continuous transmission signals by source transmitter, the deployment of such improved cooperative behavior in cognitive radio networks has not been reported yet. This improvement assumption may render serious mutual interference between the relay station and the destination receiver, and the signal interference borne by the primary user will also exceed the threshold value, if there is no elaborate signal design and resource scheduling. In order to make full use of the available resources, this paper presents the closed-form solution of the power allocation, the decision criteria of the path selection and the subcarrier pairing technique for the problem of maximization of the sum rate of secondary users in such networks under the dual constraints of the power budget and the interference threshold. Simulation results show that the continuous transmission behavior at the source significantly outperforms the traditional switching back and forth between on and off.

Some Characterizations of Total Outer-connected Domination in Graphs

This research related to total outer-connected dominance regarding graphs aids in revealing significant insights. Theoretical analysis establishes connections with tree-like structures, emphasizing the relationship with outer planarity. Effective algorithms, integrating the linear-time algorithm for trees and the genetic algorithm for general graphs, show effectiveness in locating minimal total outer-connected dominating sets. Practical implications aid in enlightening applications in wireless sensor networks, social networks, and network design, focusing on the benefits of defect tolerance and information dissemination. This research study aids in contributing towards the increased level of understanding, delivering the practical algorithms, suggesting real- world applications, and providing guidance to future research directions for total outer-connected dominance within the graph.

Artificial Intelligence in 6G Wireless Networks: Opportunities, Applications, and Challenges

Wireless technologies are growing unprecedentedly with the advent and increasing popularity of wireless services worldwide. With the advancement in technology, profound techniques can potentially improve the performance of wireless networks. Besides, the advancement of artificial intelligence (AI) enables systems to make intelligent decisions, automation, data analysis, insights, predictive capabilities, learning, and adaptation. A sophisticated AI will be required for next-generation wireless networks to automate information delivery between smart applications simultaneously. AI technologies, such as machines and deep learning techniques, have attained tremendous success in many applications in recent years. Hances, researchers in academia and industry have turned their attention to the advanced development of AI-enabled wireless networks. This paper comprehensively surveys AI technologies for different wireless networks with various applications. Moreover, we present various AI-enabled applications that exploit the power of AI to enable the desired evolution of wireless networks. Besides, the challenges of unsolved research in this area, which represent the future research trends of AI-enabled wireless networks, are discussed in detail. We provide several suggestions and solutions that help wireless networks be more intelligent and sophisticated to handle complicated problems. In summary, this paper can help researchers deeply understand the up-to-the-minute wireless network designs based on AI technologies and identify interesting unsolved issues to be pursued in their research in a fast way.

Optimizing energy efficiency in heterogeneous networks: An integrated stochastic geometry approach with novel sleep mode strategies and QoS framework.

The quest for energy efficiency (EE) in multi-tier Heterogeneous Networks (HetNets) is observed within the context of surging high-speed data demands and the rapid proliferation of wireless devices. The analysis of existing literature underscores the need for more comprehensive strategies to realize genuinely energy-efficient HetNets. This research work contributes significantly by employing a systematic methodology, utilizing This model facilitates the assessment of network performance by considering the spatial distribution of network elements. The stochastic nature of the PPP allows for a realistic representation of the random spatial deployment of base stations and users in multi-tier HetNets. Additionally, an analytical framework for Quality of Service (QoS) provision based on D-DOSS simplifies the understanding of user-base station relationships and offers essential performance metrics. Moreover, an optimization problem formulation, considering coverage, energy maximization, and delay minimization constraints, aims to strike a balance between key network attributes. This research not only addresses crucial challenges in creating EE HetNets but also lays a foundation for future advancements in wireless network design, operation, and management, ultimately benefiting network operators and end-users alike amidst the growing demand for high-speed data and the increasing prevalence of wireless devices. The proposed D-DOSS approach not only offers insights for the systematic design and analysis of EE HetNets but also systematically outperforms other state-of-the-art techniques presented. The improvement in energy efficiency systematically ranges from 67% (min side) to 98% (max side), systematically demonstrating the effectiveness of the proposed strategy in achieving higher energy efficiency compared to existing strategies. This systematic research work establishes a strong foundation for the systematic evolution of energy-efficient HetNets. The systematic methodology employed ensures a comprehensive understanding of the complex interplay of network dynamics and user requirements in a multi-tiered environment.

Cross-Layer Energy Efficient (CLEE) Routing Algorithm for Mobile Ad-Hoc Networks

Ad-hoc routing algorithms in Wireless Sensor Networks (WSN) rely on nodes’ position awareness by regularly updating routing data of neighbouring nodes. Meanwhile, the transmission energy usage is not optimised as a result of this repeated updates and routing table deployment. Therefore, it is very critical to consider techniques of optimising or conserving energy in the design of wireless sensor networks (WSNs) in order to prolong the lifetime of the individual nodes. One of these techniques is the Cross-layer design which, is considered as an efficient method for addressing this challenge with WSNs. In this paper, we propose a Cross-Layer Energy Efficient (CLEE) routing algorithm to establish an optimal route from the source node to the destination node by selecting candidate nodes from neighbouring nodes based on the distance between these nodes and the rate of energy consumption by a possible candidate node. Then to select a designated node from the candidate nodes, the algorithm further computes the Signal Strength Quality (SQS) and the Link Lifetime (LL) as well as the Throughput (TH) rate of selected nodes. The proposed algorithm was simulated with a network size of 600 X 600 on Network Simulator 3 (NS3) in order to analyse its performance. An evaluation of the performance of the proposed CLEE protocol with existing similar protocols such as Ad-hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) reveals that CLEE outperformes AODV and DSR by conserving about 44% of available energy.

Causal CSI-Based Trajectory Design and Power Allocation for UAV-Enabled Wireless Networks under Average Rate Constraints: A Constrained Reinforcement Learning Approach

Causal CSI-Based Trajectory Design and Power Allocation for UAV-Enabled Wireless Networks under Average Rate Constraints: A Constrained Reinforcement Learning Approach

Towards Programmable Backscatter Radio Design for Heterogeneous Wireless Networks

Towards Programmable Backscatter Radio Design for Heterogeneous Wireless Networks

Модель процесса информационного обмена между абонентами сети ПРС с общим каналом связи

Purose: To analyse the quality of operation of the PRC network, enabling the evaluation of time of guaranteed delivery of data packets to the subscribers of the network in bad radio-electronic conditions. Methods: To address the problem, methods from the general theory of systems, probability theory, queuing theory, as well as the method of topological transformation of stochastic networks (TTSN) have been used. Results: The developed model allows us to estimate the quality of functioning of the packet radio communications network, which allows us to determine the main directions to improve the interference immunity of PRC networks from the effects of random and intentional interference. Practical significance: The obtained results can be used in the design of mobile radio networks of the ALE standard, as well as in the development of methods to improve the interference immunity of radio networks, multi-parameter adaptation systems.

Real-time automatic integrated monitoring of barn environment and dairy cattle behaviour: Technical implementation and evaluation on three commercial farms

Due to increasing herd sizes and automation on dairy farms there is an important need for automated monitoring of cow production, health, and welfare. Despite much progress in automatic monitoring techniques, there is still a need to integrate data from multiple sources to create a comprehensive overview and accurate diagnosis of a cow’s state. To aid the technological development of data integration, a prototype of an open and customizable automatic system that integrates data from multiple sensors relating to barn environment and cow behaviour was developed. The system integrates data from sensors that measure barn climate (e.g., temperature, humidity, wind speed), air quality (e.g., CO2 concentration), water use and temperature, the moisture and temperature of the litter and cow behaviour (e.g., lying, eating, ruminating). An external weather system and video recording system are also included. The system’s architecture consists of four main elements: sensors, nodes, gateways, and backend. The data are recorded by sensors, then locally processed on custom-developed sensor nodes, and then transmitted via radio channels to local gateways that combine the data from multiple nodes and transmit them to distributed digital storage (“the cloud”) via a 3G/4G cellular network. On the cloud, the data are further processed and stored in a database. The data are then presented to the user continuously and in real time on a dashboard that can be accessed via the internet. In the design of the local wireless network, care was taken to avoid data packet collision and thus to minimize data loss. To test the system’s performance, the system was installed and operated on three commercial dairy cattle farms for one year. The system provided high data stability with minimal loss and outliers, showing that the system is reliable and suitable for long term application on commercial dairy farms. The system’s architecture, communication network, and data processing and visualization applications form an open framework for research and development purposes, allowing it to be customized and fine-tuned before being deployed as a management assistant on commercial dairy farms. Missing elements that should be added in the future are the integration of the data from the milking parlour and cow identification. Algorithms to integrate information from multiple sensors can be added to provide a comprehensive system that monitors all aspects related to cow welfare, health, and production automatically, remotely and in real time, thereby supporting farmers in important management decision-making.

Transformer-Empowered 6G Intelligent Networks: From Massive MIMO Processing to Semantic Communication

It is anticipated that 6G wireless networks will accelerate the convergence of the physical and cyber worlds and enable a paradigm-shift in the way we deploy and exploit communication networks. Machine learning, in particular deep learning (DL), is expected to be one of the key technological enablers of 6G by offering a new paradigm for the design and optimization of networks with a high level of intelligence. In this article, we introduce an emerging DL architecture, known as the transformer, and discuss its potential impact on 6G network design. We first discuss the differences between the transformer and classical DL architectures, and emphasize the transformer's self-attention mechanism and strong representation capabilities, which make it particularly appealing for tackling various challenges in wireless network design. Specifically, we propose transformer-based solutions for various massive multiple-input multiple-output (MIMO) and semantic communication problems, and show their superiority compared to other architectures. Finally, we discuss key challenges and open issues in transformerbased solutions, and identify future research directions for their deployment in intelligent 6G networks.

Optimal Placement of Base Stations in Integrated Design of Wireless Networks

Optimal Placement of Base Stations in Integrated Design of Wireless Networks

Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology

AbstractThe sixth generation (6G) represents the next evolution in wireless communication technology and is currently under research and development. It is expected to deliver faster speeds, reduced latency, and greater capacity compared to the current 5G wireless technology. 6G is envisioned as a technology capable of establishing a fully data‐driven network, proficient in analyzing and optimizing end‐to‐end behavior and handling massive volumes of real‐time data at rates of up to terabits per second (Tb/s). Moreover, 6G is designed to accommodate an average of 1000+ substantial connections per person over the course of a decade. The concept of a data‐driven network introduces a new service paradigm, which offers fresh opportunities for applications within 6G wireless communication and network design in the future. This paper aims to provide a survey of existing applications of 6G that are based on deep learning techniques. It also explores the potential, essential technologies, scenarios, challenges, and related topics associated with 6G. These aspects are crucial for meeting the requirements for the development of future intelligent networks. Furthermore, this work delves into various research gaps between deep learning and 6G that remain unexplored. Different potential deep learning applications for 6G networks, including privacy, security, environmentally friendly communication, sustainability, and various wireless applications, are discussed. Additionally, we shed light on the challenges and future trends in this field.This article is categorized under: Technologies > Computational Intelligence Fundamental Concepts of Data and Knowledge > Explainable AI Technologies > Machine Learning

Location Based Power Reduction Cloud Integrated Social Sensor Network

It is great to hear about the advancements in wireless sensor networks and their applications, as well as the integration of cloud computing to enhance data analysis and storage capabilities. Indeed, these technologies have opened up numerous possibilities across various fields, including infrastructure tracking, environmental monitoring, healthcare, and more. The concept of a social sensor cloud, as you mentioned, brings an interesting dimension to this technology landscape by focusing on knowledge-sharing and connecting like-minded individuals or organizations. This could potentially lead to more collaborative and efficient solutions across a wide range of domains. Energy efficiency is a critical consideration in the design and operation of wireless sensor networks and the cloud infrastructure that supports them. The limited battery life of sensors necessitates careful management of energy consumption to ensure optimal functionality and longevity. Sleep scheduling methods are a common technique used to manage energy consumption in these networks. By coordinating when sensors are active and when they are in a low-power sleep mode, energy consumption can be significantly reduced without compromising the network's overall effectiveness. In the context of the Social Sensor Cloud, managing energy efficiency becomes even more crucial due to the shorter battery life of the sensors involved. This is particularly relevant given the growing concerns about environmental sustainability and the need to reduce energy consumption across technological systems. It's clear that your research paper addresses these challenges head-on, by exploring energy-efficient techniques for the Social Sensor Cloud. Sleep scheduling is just one of the many strategies that researchers and engineers are working on to strike a balance between functionality and energy consumption. Other methods might include optimizing data transfer protocols, developing energy-harvesting mechanisms, and enhancing sensor hardware efficiency. As technology continues to evolve, the integration of wireless sensor networks, cloud computing, and social networks will likely pave the way for innovative solutions and transformative applications. Addressing energy efficiency concerns will undoubtedly play a crucial role in ensuring the long-term viability and positive impact of these technologies.