Implementation Of Wireless Network Research Articles

Cellular traffic forecasting based on inverted transformer for mobile perception dual-level base station sleep control

Due to the extensive implementation of the fifth generation wireless communication networks (5 G), numerous base stations are being strategically deployed in densely inhabited areas to address the escalating need for network traffic. Within wireless cellular networks, over 80% of energy consumption is primarily concentrated on the side of the base station. In comparison to 4 G base stations, the 5 G base stations exhibit notable enhancements in terms of bandwidth, peak rate, and transmission power. Nonetheless, they suffer from limited signal coverage and extensive resource consumption. To address this challenge effectively, the present study introduces a Mobile Perception Dual-Level (MPDL) base station sleep control strategy based on cellular traffic forecasting. The strategy aims to satisfy the demands for reduced power consumption and enhanced service quality by monitoring both the current network traffic of the base station and the user's mobility, consequently placing the base station into two different sleep states. Specifically, we first designed an inverted Transformer (iTransformer) model to accurately forecast cellular traffic. The model is capable of effectively capturing both the spatial and temporal attributes of cellular traffic. It also takes into account the impact of geographical features, such as Points of Interest (POIs) and the quantity of Base Stations (BSs), on the forecasting outcomes. Consequently, it attains precise predictions of the cellular traffic. Based on the forecasting outcomes of cellular traffic, this study presents a mobility perception dual-level sleep strategy. This strategy proposal differentiates sleep into deep sleep and light sleep, while also taking into account the mobility attributes of users. It incorporates considerations for Quality of Service (QoS) and energy consumption. We assess the performance and application impacts of cellular traffic forecasting and base station sleep strategy in real-world datasets. Several experiments and validations have confirmed that the MPDL, as proposed in this paper, effectively decreases power consumption by a range of 22% to 41% when compared to baselines.

Wireless quantum key distribution at terahertz frequencies: Opportunities and challenges

AbstractQuantum key distribution (QKD) is one of the major applications of quantum information technology. It can provide ultra‐secure key distribution with security guaranteed by the laws of quantum physics. Quantum key distribution is necessary to protect data transmission from quantum computing attacks in future communication networks. The laws of quantum mechanics dictate that as opposed to microwave frequencies, quantum coherence is preserved at room temperatures for terahertz (THz) frequencies. This makes the THz band a promising solution for room‐temperature QKD implementation in future wireless communication networks. The authors present the principles of continuous variable QKD (CV‐QKD) systems and review the latest developments in the design and analysis of CV‐QKD systems operating at microwave and THz frequencies. The authors also discuss how multiple‐input multiple‐output transmission can be incorporated into the quantum communications framework to improve the secret key rates and increase the coverage distances of the THz CV‐QKD system. Furthermore, major hardware challenges that must be surmounted to practically realise THz CV‐QKD systems are highlighted.

Change Management and Advanced Wireless Network Implementation: Detection of Monetization Opportunities and Challenges

This study focuses on the interconnection between two topics: change management and advanced wireless networks. Advanced wireless networks can generate turmoil at the deepest level of all sectors of activity by offering the possibility of new connectivity through these networks&#x2019; assets, which would require new business models and introduce novel features into purchasing processes and consumer experiences. In addition, telecommunications companies play a fundamental role in developing and implementing these new technologies to ensure they fulfil their promise. Change management practices are critical to ensuring successful advanced wireless network implementation, especially at a strategic and operational level. This research sought to contribute to a more holistic view of the interconnections between these two topics. The multiple-criteria decision analysis approach was used to conduct analyses of the relationships between the associated monetization opportunities and challenges, which included applying the decision-making trial evaluation laboratory technique to clarify their cause-effect links. A multidisciplinary expert panel was recruited to facilitate the method&#x0027;s application. The insights obtained during two panel meetings allowed the proposed process-oriented approach to assist decision makers in analyzing monetization opportunities and challenges related to advanced wireless network adoption according to the following five clusters: <i>service offer</i>; <i>vendor value proposition</i>; <i>operational management</i>; <i>strategic management</i>; and <i>external factors</i>. Contributions and limitations are also examined.

Implementation of Novel Block and Convolutional Encoding Circuit Using FS-GDI

A novel implementation of Block and Convolutional encoding circuits approach using Gate Input Diffusion-Full Swing (FS-GDI) and Complementary Metal Oxide Semiconductor (CMOS) logic styles has been presented. Performance analysis of the proposed encoding circuits has been performed using Cadence Virtuoso (CV) S/W package. The performance metrics of FS-GDI-based encoding circuits have been compared with traditional CMOS-based designs. The proposed encoding circuits involve Block Hamming (15, 11), Convolutional (2, 1, 3), and Recursive Systematic Convolutional (2, 1, 2) encoding circuits; these presented circuits are simulated and tested using a word length of 11 bits. The simulation experiments revealed that the proposed implemented circuits achieve delay time improving by 27.91% and 33.27% for Hamming (15, 11) and Convolutional (2, 1, 3) codes, respectively. The simple proposed RSC encoder performs better than the Convolutional (2, 1, 3) due to shorter constraint length and less H/W complexity. On the other hand, the Transistor Count-Hardware (TC-H/W) is enhanced by 50% for the Block and Convolutional encoding based on employing area-efficient FS-GDI-XOR gate. From the analysis of the results, the proposed designs achieve efficient power and delay optimization of Hamming and Convolutional encoding utilizing the FS-GDI logic style. Also, it is clear that the characteristics of the proposed encoding circuits are vital and effective in the digital signal processing circuits and encoding/decoding schemes implementation in low-power wireless networks.

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.

ANALYSIS MODEL FOR NON-PREDICTIVE PATTERNS OF NON-IONIZING RADIATIONS

Non-ionizing radiations have been, and still are, a problem whose approach arouses great social interest, due to its controversial implications for human health and the interest of telecommunications companies in the development and implementation of technologies wireless networks based on the propagation of electromagnetic waves. The recurring question generated from society is related to the possibility that said radiation affects health in some way. The present study is based on the hypothesis that, if there is any degree of affectation, it could be due to an effect found regarding non-predictive patterns of propagation of electromagnetic waves and punctual concentration of radiation in very small areas, generating differentials in the level of density of immission. A field work has been carried out looking for the elements of the urban and suburban environment that facilitate and/or enhance the concentration of radiation at a point and were analyzed with qualitative statistical models with binary logistic regression and association analysis, to develop a prediction pattern. possibility of existence of a point of high density of electromagnetic immersion depending on elements of the environment.

Editorial para el Número Especial del Taller Andino de Comunicaciones Inalámbricas y sus Aplicaciones

Nowadays, wireless communications are present in the daily activities of modern society and leverage the fast growth of new services, and this trend is likely to increase for the foreseeable future. However, wireless networks have become more complex because of the number of different services that must support. Therefore, research is more important than ever to ensure the successful deployment and implementation of wireless networks and related services. This special issue includes the papers presented at the second Andean workshop on wireless communications and its applications, which show the research carried out in the Andean region to develop this important telecommunications area.

Improving Performance of Association Control in IEEE 802.11ah-Based Massive IoT Networks

With the rise of massive Internet-of-Things (mIoT) applications, the IEEE 802.11ah standard is gaining more attention for implementation in wireless networks. Unbalanced distribution of the traffic load among the access points (APs) is a problem that results in performance degradation of such networks, including packet loss and delay, which are essential for some mission-critical applications. In this article, we present a novel solution for user-AP association in IEEE 802.11ah networks. Assuming that the network is carrying complex traffic, we limit the number of devices associated with each AP to keep the blocking probability under the desired value. Also, two mechanisms are proposed to limit the delay of packets by restricting the number of stations associated with an AP and to determine the transmission range of APs for covering a specific number of stations. Our simulations demonstrate that the proposed method can enhance the throughput and energy efficiency in the network and also limit the blocking probability and delay of packets in the network by restricting the number of IoT devices associated with an AP. As a result, the proposed method facilitates ultrareliable low-latency communications (URLLCs) by limiting the number of associated stations in IEEE 802.11ah networks.

Towards edge intelligence in the automotive scenario: A discourse on architecture for database-supported autonomous platooning

Edge intelligence is one of the key paradigms related to the efficient implementation of future wireless networks. In this context, the surrounding telecommunication infrastructure is intended to support the functioning of the wireless system. Thus, it is necessary to offload some computational efforts to the system edge, allowing the infrastructure to learn and make prospective decisions. However, for the reliable realization of the edge intelligence concept, the wireless system architecture should be designed properly to minimize both storage cost and induced latency. In this paper, we compare three architecture proposals (centralized, distributed, and hybrid) tailored to the autonomous driving use case, being one of the key vertical scenarios in contemporary and future wireless networks. We evaluate the performance of an autonomous platooning system, where the operating frequency is selected dynamically with the support of infrastructure to minimize the overall interference level in the whole band. Extensive computer simulations have been carried out to analyze the impact of the induced delay in signal processing and storage efficiency.

Implementation of abstract MAC layer under jamming

In the past decades, with the widespread implementation of wireless networks, such as the Internet of Things, an enormous demand for designing relative algorithms for various realistic scenarios has arisen. However, with the widening of scales and deepening of network layers, it has become increasingly challenging to design such algorithms when the issues of message dissemination at high levels and the contention management at the physical layer are considered. Accordingly, the abstract medium access control (absMAC) layer, which was proposed in 2009, is designed to solve this problem. Specifically, the absMAC layer consists of two basic operations for network agents: the acknowledgement operation to broadcast messages to all neighbors and the progress operation to receive messages from neighbors. The absMAC layer divides the wireless algorithm design into two independent and manageable components, i.e., to implement the absMAC layer over a physical network and to solve higher-level problems based on the acknowledgement and progress operations provided by the absMAC layer, which makes the algorithm design easier and simpler. In this study, we consider the implementation of the absMAC layer under jamming. An efficient algorithm is proposed to implement the absMAC layer, attached with rigorous theoretical analyses and extensive simulation results. Based on the implemented absMAC layer, many high-level algorithms in non-jamming cases can be executed in a jamming network.

Схемы NOMA с обработкой на уровне символов

Requirements for KPI in 6G networks are significantly higher than in 5G networks. Non-orthogonal multiple access (NOMA) technology has been proposed as a solution to meet the requirements of future communication networks. NOMA technology aims to improve the spectral efficiency of wireless communication systems and support the simultaneous operation of large number of subscribers (especially in mMTC scenarios) and provide flexible resource use. This article discusses the popular symbol-level processing NOMA schemes recently proposed as part of the 3GPP standardization, such as SCMA, PDMA, WSMA, MUSA, and other varieties of NOMA. The main advantages and principles of non-orthogonal access technology are illustrated using the NOMA system with division in power domain (PD-NOMA) for uplink and downlink. Characteristics of various symbol-level processing NOMA schemes, their advantages and disadvantages, as well as problems in the way of their implementation in future wireless networks are analyzed. In addition, this article discusses block diagrams of NOMA systems and mathematical models illustrating the formation of baseband signals in such systems. In conclusion, the noise immunity characteristics of the most popular NOMA schemes with symbol-level processing are given for various loading factors. From the analysis performed, it follows that no NOMA scheme has yet been proposed that is effective in various scenarios of future wireless communication systems and has an acceptable processing complexity in combination with flexible resource allocation for mass connection of subscriber devices.

Antennas and Propagation Aspects for Emerging Wireless Communication Technologies

The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks [...]

Implementation and Design of Wireless IoT Network using Deep Learning

The Internet of Things (IoT) is a technology and plays a key role in just this process. In designing better cities,embedded devices include this new technology, which the internet is similar to everybody. IoT solutions are spread through different regions, such as agriculture, healthcare, the motor industry, education, and home automation, etc. wireless communication (WC) is now becoming an efficient role for incorporating wireless communicationenvironment, computers, organizations, and governments. WC is a budding technology in IoT, and it involves further learning. This dilemma motivates the authors to suggest a standardized IoT WC system. The formation is subdivided into four tiers, according to the IoT architecture. The initial two steps concentrate on the design of Sensors and gateways; cloud integration is identified in the third stage, the server configuration is discussed in the fourth stage, and cloud integration is listed in the third stage user interface is seen in the fifth stage. Proposed, hence, the solution enables the IoT application developer's work. The design using the clean energy consumption case study. Sensors and Raspberry pi are used in the application to quantify and then provide electricity usage using wireless communication between the devices consumed by the home or building. This provides the client with a rising knowledge of the pattern of power consumption and the usage of electricity using Recurrent Neural Network(RNN).

Improving Efficiency By Using Synchronised Parallel Data Transmission Over Wsn

As the data transmission speed and the efficiency over the wireless network depend on the network or transfer device bandwidth. After physical implementation of wireless network which is difficult to dynamically control transfer in order to get high or low data transfer rate. Dedicating the fixed network for such a dynamic requirement network is not feasible. Many researchers are trying to enhance the wireless network speed by joining the transfer speed of multiple lines which will result in to asynchronous data transfer and data leakage. Hence the proposed system is to design and implements a dynamically controllable wireless network using the multiple radio frequency wireless devices. Here the proposed system will use multiple wireless devices and transfer data over multiple line depending upon the user configuration and synchronize the data over the receiving end. It will let the user control the wireless data transmission speed as per the requirement.

Бездротова локальна мережа класу Smart Home на базі модулів сплітерів-репітерів

The purpose of the article is develop a wireless local area network for residential use. The article contains a description of the created channel splitter modules. The module also acts as a repeater. On the basis of repeater splitter module designed network modules hubs and switches. The hub and switch has two versions: wired and wireless. The wired version is used in conditions of a large amount of interference and a large signal attenuation. Smart Home wireless LAN is built on the splitters-repeaters modules basis, hubs and switches. The network does not support the MQTT protocol. The network is divided into clusters and segments and supports packet routing. The protocol stack is minimized. The functionality of the host and the network object is completely separated. The topology of the mobile network is not deterministic, amorphous and changes when the network objects move in space. In this case, some connections are lost and others arise. The routing tables are constantly updated. The network in accordance with the laid down algorithm, is able to build the necessary topology and organize the necessary connections in order to complete the task with a many objects. The network is capable of building packet retransmission chains for remote network objects. Thus, the wireless network implementation at its low cost allows solving a certain range of tasks. The performer can be either a separate object associated with the operator through a many repeaters. In order to increase the efficiency of the formation of routing tables and minimize the cluster structures in a wireless network. The local wireless network is designed to control an Internet of Things objects.

An Adaptive Hybrid Beamforming Approach for 5G-MIMO mmWave Wireless Cellular Networks

Hardware complexity reduction is a key concept towards the design and implementation of next generation broadband wireless networks. To this end, the goal of the study presented in this paper is to evaluate the performance of an adaptive hybrid analog-digital beamforming approach in fifth-generation (5G) massive multiple input multiple output (MIMO) millimeter wave (mmWave) wireless cellular orientations. In this context, generated beams are formed dynamically according to traffic demands, via an on-off analog activation of radiating elements per vertical antenna array, in order to serve active users requesting high data rate services without requiring any expensive and mechanical complex steering antenna system. Each vertical array, which constitutes a radiating element of a circular array configuration, has a dedicated radio frequency chain (digital part). The performance of our proposed approach is evaluated statistically, by executing a sufficient number of independent Monte Carlo simulations per MIMO configuration, via a developed system-level simulator incorporating the latest 5G-3GPP channel model. According to the presented results, the adaptive beamforming approach can improve various key performance indicators (KPIs) of the wireless orientation, such as total downlink transmission power and blocking probability. In particular, when studying/analyzing a MIMO configuration with 15 vertical antenna arrays and 10 radiating elements per array, then, depending on the tolerable amount of transmission overhead, the proposed adaptive algorithm can significantly reduce the number of active radiating antenna elements compared to the static grid of beams case. In the same context, when keeping the number of radiating elements constant, then the total downlink transmission power as well as the blocking probability can be significantly reduced. It is important to note that all the KPIs have been extracted when deploying the developed array configuration in complex cellular orientations (two tiers of cells around the central cell).

WITHDRAWN: An extensive survey on cognitive radio based spectrum sensing using different algorithms

Abstract Latest technical developments also emerged in the implementation of wireless networks which consisting of self-organizing devices which can be distributed without finding for infrastructure. Usually these devices having small form factor and also stored with embedded devices, ability of communication and processing. The licensing of wireless spectrum is highly developed over large global locations on a basis of long-term. The FFC was recently implemented the usage of unlicensed devices in licensed bands in order to overcome the significant problems of spectrum scarcity. Dynamic spectrum access (DSA) strategies are therefore suggested to address the existing issues of spectrum inefficiency. In order to further boost spectrum quality; this new research area has recognized the creative network called Cognitive Radio (CR). The fundamental principle of CR network is that the unlicensed network (secondary users) must vacate the band until the licensed network (primary user) is sensed. However, due to the high variations which are available in the spectrum and (QoS) criteria, the CR network will able to face different challenges.

Development of 32-GBaud DP-QPSK free space optical transceiver using homodyne detection and advanced digital signal processing for future optical networks

Free space optical (FSO) communication provides the capacity to deliver high-speed digital data links into the far off and rural factions where topography, set-up cost or groundwork safety pose acute barriers to deployment. The challenges in any FSO system are the transmission impairments and space loss which deteriorate the link performance. This article deals with the design and analysis of a single channel Gray-coded dual polarization-quadrature phase shift keying (DP-QPSK) based FSO communication system with balanced homodyne detection (BHD) and digital signal processing (DSP). We have implemented a series of high-level digital impairment compensation algorithms strategically between the BHD and signal retrieval stages to mitigate the amplitude and phase noise, and compensate for free-space loss. The proposed system exhibits a 3 dB greater receiver sensitivity using optical homodyne detection compared to heterodyne detection. The system performance has been numerically evaluated with regard to bit error rate (BER $$\le 2\times {10}^{-3},$$ i.e. FEC limit), error vector magnitude (EVM), and constellation diagram based on OptiSystem V.16 photonic software. Furthermore, we investigate the joint BER and EVM performance of the proposed system under the influence of launched optical power, laser linewidth, and beam divergence. We obtain the transmission of 32 GBaud DP-QPSK data bearing optical signal up to a link distance of 2.65 km at 128-Gb/s data rate, and an optical signal-to-noise ratio penalty lower than 2.5 dB compared to the back-to-back case. The outcomes of this research demonstrate direct practical relevance and could therefore form the basis for the implementation of next-generation optical wireless networks.

Wireless Powered Mobile Edge Computing: Offloading Or Local Computation?

Mobile-edge computing (MEC) and wireless power transfer are technologies that can assist in the implementation of next generation wireless networks, which will deploy a large number of computational and energy limited devices. In this letter, we consider a point-to-point MEC system, where the device harvests energy from the access point's (AP's) transmitted signal to power the offloading and/or the local computation of a task. By taking into account the non-linearities of energy harvesting, we provide analytical expressions for the probability of successful computation and for the average number of successfully computed bits. Our results show that a hybrid scheme of partial offloading and local computation is not always efficient. In particular, the decision to offload and/or compute locally, depends on the system's parameters such as the distance to the AP and the number of bits that need to be computed.

An All-wireless SDN Framework for BLE Mesh

The Internet of Things (IoT) paradigm combines the interconnection of massive amounts of battery-constrained and low-computational-power devices with low-latency and high-reliability network requirements. Additionally, diverse end-to-end services and applications with different Quality of Service (QoS) requirements are expected to coexist in the same network infrastructure. Software-defined Networking (SDN) is a paradigm designed to solve these problems, but its implementation in wireless networks and especially in the resource-constrained IoT systems is extremely challenging and has seen very limited adoption, since it requires isolation of data and control plane information flows and a reliable and scalable control plane. In this work, Bluetooth Low Energy (BLE) mesh is introduced as an adequate technology for an all-wireless SDN-BLE implementation, which is a technology that has become the de-facto standard for IoT. The proposed SDN-BLE framework uses a routing network slice for the data plane information flow and a flooding network slice for the control plane information flow, ensuring their isolation while still being transmitted over the wireless medium. The design and implementation of all the classical SDN layers on a hybrid BLE mesh testbed is given, where the data plane is formed by the BLE nodes and the control plane can be centralized on a server or distributed over several WiFi gateways. Several controllers are described and implemented, allowing the framework to obtain end-to-end network knowledge to manage individual nodes over the air and configure their behavior to meet application requirements. An experimental characterization of the SDN-BLE framework is given, where the impact of the different parameters of the system on the network reliability, overhead, and energy consumption is studied. Additionally, the distributed versus centralized control plane operation modes are experimentally characterized, and it is shown that the distributed approach can provide the same performance as the centralized one when careful system design is performed. Finally, a proof of concept for the SDN-BLE framework is presented, where a network congestion is automatically detected and the nodes responsible of such congestion are identified and reconfigured over the air, bypassing the congested links, to resume regular network performance.