Area Of Wireless Communications Research Articles

On the optimal synthesis of sparsely thinned planar array antenna with constraints using meta‐heuristic optimization

SummaryThe investigations related to the planar antenna array have attracted much attention due to their vast applications in the areas of advanced wireless communication and electromagnetics. This article presents an effective synthesis method of a sparsely thinned symmetric planar antenna array using three well‐known meta‐heuristics including symbiotic organism search (SOS) algorithm, moth fly optimization (MFO), and multi‐verse optimization (MVO) algorithms. The main aim of this work is to optimize the positions of the switched‐on antenna elements on the array aperture in order to reduce the value of side‐lobe levels in the radiation field pattern in multiple planes for a desired first null beam width and subsequently to obtain the maximum reduced number of array‐elements in the antenna array. Two different cases are performed to optimize the radiation pattern in different azimuth angles with two different examples. The proposed methods can constrain the total number of array elements, inter‐element distance, and aperture area of the array. The radiation pattern characteristic and computation time linked with each example and each algorithm are recorded and compared with each other as well as with a fully populated planar symmetric rectangular array antenna of same aperture size for arriving at the conclusion. The simulation‐based results demonstrate the effectiveness of the proposed design and the efficiency of the performance using the SOS algorithm.

Tunable reflective tri-band polarization converter based on graphene composite metasurface

A graphene composite metasurface-based reflective tri-band polarization converter working in the terahertz frequency regime is proposed and investigated by CST Microwave Studio software. The polarization converter achieves high polarization conversion ratios (above 99%) for linear-to-linear polarization conversion at 6.21, 9.11, and 11.66 THz, and for linear-to-circular polarization conversion at 5.14 THz, with a fixed Fermi energy level (Ef) of 1.0 ev due to the excitation of localized surface plasmons. Subsequently, the reason for cross-polarization conversion at three resonant frequencies and the incident angle sensitive property of the converter were discussed. Based on the graphene component, a tunable tri-band polarization converter was obtained and investigated; this converter could be applied in the active modulation area of wireless communication.

Impact of Antenna Design, Electromagnetic Propagation, and RF Frequency on the Performance of Wireless Communication Systems in Urban Environments

The design and optimization of antennas, electromagnetic propagation, radio frequency (RF), and channel characterization are vital to the performance of the system in the rapidly developing area of wireless communication. Antennas are electronic components that transform electrical currents into electromagnetic waves and vice versa. They are critical to the operation of any wireless network and their design and optimization are therefore of paramount importance. The goal of this research was to find out how different factors, like antenna type, electromagnetic environment, RF, and channel characteristics, affect the efficiency of a wireless network. Multipath fading of 8 dB, shadow fading of 3 dB, and path loss of 100 dB were used in the study with a microstrip antenna in a suburban propagation scenario at an RF frequency of 5 GHz. Antenna design, electromagnetic propagation scenario, radio frequency (RF), and channel characteristics were all shown to have an impact on the wireless communication system performance. The performance metrics of the wireless sensor network were almost, but not quite, those that were hoped for in a real-world setting. Several avenues for future study are suggested, and the results have important implications for the design and optimization of wireless communication systems.

Recent Advances in Micro-LEDs Having Yellow–Green to Red Emission Wavelengths for Visible Light Communications

Visible light communication (VLC), which will primarily support high-speed internet connectivity in the contemporary world, has progressively come to be recognized as a significant alternative and reinforcement in the wireless communication area. VLC has become more popular recently because of its many advantages over conventional radio frequencies, including a higher transmission rate, high bandwidth, low power consumption, fewer health risks, and reduced interference. Due to its high-bandwidth characteristics and potential to be used for both illumination and communications, micro-light-emitting diodes (micro-LEDs) have drawn a lot of attention for their use in VLC applications. In this review, a detailed overview of micro-LEDs that have long emission wavelengths for VLC is presented, along with their related challenges and future prospects. The VLC performance of micro-LEDs is influenced by a number of factors, including the quantum-confined Stark effect (QCSE), size-dependent effect, and droop effect, which are discussed in the following sections. When these elements are combined, it has a major impact on the performance of micro-LEDs in terms of their modulation bandwidth, wavelength shift, full-width at half maximum (FWHM), light output power, and efficiency. The possible challenges faced in the use of micro-LEDs were analyzed through a simulation conducted using Crosslight Apsys software and the results were compared with the previous reported results. We also provide a brief overview of the phenomena, underlying theories, and potential possible solutions to these issues. Furthermore, we provide a brief discussion regarding micro-LEDs that have emission wavelengths ranging from yellow-green to red colors. We highlight the notable bandwidth enhancement for this paradigm and anticipate some exciting new research directions. Overall, this review paper provides a brief overview of the performance of VLC-based systems based on micro-LEDs and some of their possible applications.

Deep Learning based Wireless Channel Prediction: 5G Scenario

In the area of wireless communication, channel estimation is a challenging problem due to the need for real-time implementation as well as system dependence on the estimation accuracy. This work presents a Long-Short Term Memory (LSTM) based deep learning (DL) approach for the prediction of channel response in real-time and real-world non-stationary channels. The model uses the pre-defined history of channel impulse response (CIR) data along with two other features viz. transmitter-receiver update distance and root-mean-square delay spread values which are also changing in time with the channel impulse response. The objective is to obtain an approximate estimate of CIRs using prediction through the DL model as compared to conventional methods. For training the model, a sample dataset is generated through the open-source channel simulation software NYUSIM which realizes samples of CIRs for measurement-based channel models based on various multipath channel parameters. From the model test results, it is found that the proposed DL approach provides a viable lightweight solution for channel prediction in wireless communication.

Scalable Multi-Agent Reinforcement Learning for Dynamic Coordinated Multipoint Clustering

Reinforcement learning (RL) is a widely investigated intelligent algorithm and proved to be useful in the wireless communication area. However, for optimization problems in large-scale multi-cell networks whose dimension increases exponentially, it is unrealistic to employ a conventional centralized RL algorithm and make decisions for the entire network. Multi-agent RL, which allows distribute decision-making, is expected to solve the scalability problem but with performance issues due to the unknown global information, i.e., non-stationary environment. In this paper, we propose a parameter-sharing multi-agent RL for grouping decisions of coordinated multi-point in a large-scale network, where agents jointly serve users to enhance the cell-edge service. By sharing information via parameters, our theoretical and simulation results show that parameter sharing can largely benefit the multi-agent algorithm with convergence proof and convergence speed analysis. To reduce the effect of biased local heterogeneous experience, we also propose a transfer learning method for the parameter sharing process, whose performance of transfer learning algorithms is verified by the simulation results.

Effectiveness of Video Lessons Using Mobile Learning Technology

Electronics and communication and manufacturing technology are gaining much importance in the new millennium. The advents in electronics and communication technologies have been offering inexpensive, more convenient and more functionality in a single device. The engineering students and teachers can access data and communicate with each other anytime, anywhere, on any device, and any data and network. The researcher has to implement new technology, new ideas, and innovations in the research area of wireless communication and wireless networks. In wireless and mobile communication, to develop these engineering laboratories into virtual labs and study materials in hand (within a Pocket). This research is focused on and related to engineering education research. The quasi-experimental design has been used in this research study to measure the effectiveness of mobile learning using video lessons in engineering education. The questionnaire is used to evaluate the effectiveness of mobile learning for undergraduate engineering students. This paper describes the main study of the research results shows that 506 students of second year engineering students of Electrical and Electronics Engineering (EEE), Electronics and Communication (ECE), and Bio- Medical Engineering (BME) in Chennai, Tamil Nadu, India their usage of wireless communication technology in mobile learning using video lessons. The video lessons used for this study are Electromagnetism which is common for EEE and ECE and Electrocardiography is common for BME and ECE. During the study smart phones, mobile phones and wireless devices, tablet pc, personal digital assistants, etc are used and the duration of the video lesson is 30 minutes. These video lessons can be transmitted using Bluetooth technology in the classroom, library, and corridors during the free hours. Keywords: E-learning, m-learning,

Design of pattern-reconfigurable circularly polarized unidirectional antenna based on quasi-radiator for ISM applications

A pattern-reconfigurable circularly polarized antenna for 2.45 GHz industrial, scientific, and medical (ISM) band applications is designed in this work. The proposed antenna consists of a slotted-stepped monopole connected to a rectangular ground plane via a shorting side-stub. This converts the omnidirectional radiation pattern of the antenna into stable unidirectional radiation. To dynamically steer the realized pattern, two switchable RF PIN diodes are jointly incorporated into the side-stubs to achieve symmetrical radiations in specific operating modes. In this way, the radiation patterns can be simultaneously tuned in the ±y directions by the simple switching of the PIN diodes ON and OFF. The fabricated prototype achieves an S11 smaller than -10dB within the 3dB axial ratio (AR) bandwidth with stable far-field patterns. The antenna maintains a low-profile and compact size of 0.055λ02 which makes it suitable for body-centric wireless communication (BWC) and personal wireless area networks.

An Improved Harmony Search Approach for Block Placement for VLSI Design Automation

Level of knowledge with the field for VLSI IC Design’s Placement and Routing and in the area of Wireless Communication is rapidly evolving; Hence the process designing in the above fields is critical to assimilate a higher quantity of computation elements or nodes into a very compact size in VLSI Area and also the same is applicable in Wireless Communications to cover more number of nodes in a specific area. Prior to completing the placement, the physical and technical arranging of the computation elements or nodes in the chip area is planned, which is nothing more than Placement step and analogous with coverage of nodes in Wireless communication. Floorplanning must be done properly for reduce given placement area in physical ICDie. The proposed work suggests an ImprovisedHarmonySearch-IHS Optimization Algorithm, which is an Sequential combination of the HarmonySearch (HS) Algorithm and the most effective Particle Swarm Optimization (PSO) Algorithm to achieve the major objective of the VLSI Placement approach and applicable to the field of Wireless Communication. The aim at this point is to reduce the gap between the standard area of the benchmark circuit to the obtained area of the corresponding benchmark circuit. The MATLAB code for the ImprovisedHarmonySearch-IHS Algorithm is recreated, and discoveries are tested for better inspection using standard MCNC, or North Carolina Microelectronics Center benchmark circuits and suggest to adopt the corresponding results to the area of Wireless communication.

Metaheuristic Deep Learning-Driven Wireless Communication Security Adaptation Using Multivariate Analysis of Variance (MANOVA)

The implementation of accurate models to improve access technologies, communication transmission, and network slicing is anticipated to play a big part in the edge computing approach, as the demands and needs of individuals are quickly evolving. Deep learning models have tended to deliver more benefits in a wide range of applications; it also assists data providers in demonstrating considerable improvements in tackling complex real-world challenges. While the integration of connected wireless networks and deep learning is still in its infancy, wireless communication networks are increasingly focused on sophisticated technologies to meet the current and future needs of end users. Based on the theoretical and practical aspect that ranges from the basic aspect to future applications of wireless communication, this study is intended in addressing the opportunities of adopting metaheuristic deep learning-driven wireless communication. The researchers intend to apply descriptive design to the study as this enables in understanding the critical aspects of the study in an elaborate manner. The authors use both a primary data sources and a secondary data sources for performing the analysis. The secondary data source is sourced to understand the application of deep learning in the wireless communication area, and primary research is used to gather the data from the respondents to test the hypothesis and provide conclusions based on the analyses. The scope of this work is to utilize a quantitative model to undertake an analysis on evaluating the key parameters in the application of deep learning in wireless communication, which will allow for critical analysis and interpretation based on the findings.

Future Wireless Communication Technology towards 6G IoT: An Application-Based Analysis of IoT in Real-Time Location Monitoring of Employees Inside Underground Mines by Using BLE.

In recent years, the IoT has emerged as the most promising technology in the key evolution of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and many other areas of wireless communication. There is a massively growing number of static and mobile IoT devices with a diversified range of speed and bandwidth, along with a growing demand for high data rates, which makes the network denser and more complicated. In this context, the next-generation communication technology, i.e., sixth generation (6G), is trying to build up the base to meet the imperative need of future network deployment. This article adopts the vision for 6G IoT systems and proposes an IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications. An application-based analysis of industrial positioning systems is also presented.

Implementation of an Intelligent Neonatal Monitoring System Using Raspberry Pi

An incubator is a biomedical apparatus used to keep neonates if they are ill and in need of further investigations. This is also useful for observation and care of newborn babies who were premature or of low birth weight. There will be loss of lives of neonates if the incubator is not appropriately monitored and this may even lead to accidents. In view of these, it has been proposed to implement an Intelligent Monitoring System for Neonatal Intensive Care Unit (NICU). For monitoring the premature infants continuously it requires sensors. It has been learnt that the temperature, breathing rate, body movements, loudness, or cry are some of the features to be monitored in incubator. Hence, in this paper, a wireless communication and body area network based system that constantly examine the vital physiological parameters of the baby kept in the NICU has been discussed. The analog signals from the sensors are processed using a Raspberry Pi. The system has been developed with Raspberry Pi B+ module as the controller. Sensors are used to monitor the physiological parameters and Pi camera is used to detect the baby movements. Global System for Mobile Communications (GSM) module is incorporated in the proposed system to transmit the parameters via a short message service (SMS). Hence, this system offers a suitable method for parents and nurses to monitor premature infants.

Implementation of a Noise-Shaped Signaling System through Software-Defined Radio

Along with the development of electromagnetic weapons, Electronic Warfare (EW) has been rising as the future form of war. Especially in the area of wireless communications, high security defense systems such as Low Probability of Detection (LPD), Low Probability of Interception (LPI), and Low Probability of Exploitation (LPE) communication algorithms are being studied to prevent military force loss. One LPD, LPI, and LPE communication algorithm, physical-layer security, has been discussed and studied. We propose a noise signaling system, a type of physical-layer security, which modifies conventionally modulated I/Q data into a noise-like shape. To suggest the possibility of realistic implementation, we use Software-Defined Radio (SDR). Since there are certain hardware limitations, we present the limitations, requirements, and preferences of practical implementation of the noise signaling system. The proposed system uses ring-shaped signaling, and we present a ring-shaped signaling system algorithm, SDR implementation methodology, and performance evaluations of the system using the metrics of Bit Error Rate (BER) and Probability of Modulation Identification (PMI), which we obtain by using a Convolutional Neural Network (CNN) algorithm. We conclude that the ring-shaped signaling system can perform high LPI/LPE communication functioning because an eavesdropper cannot obtain the correct modulation scheme information. However, the performance can vary with the configurations of the I/Q data-modifying factors.

Distributed and Scalable Uplink Processing for LIS: Algorithm, Architecture, and Design Trade-Offs

The Large Intelligent Surface (LIS) is a promising technology in the areas of wireless communication, remote sensing and positioning. It consists of a continuous radiating surface located in the proximity of the users, with the capability to communicate by transmission and reception (replacing base stations). Despite its potential, there are numerous challenges from an implementation point of view, with the interconnection data-rate, computational complexity, and storage the most relevant ones. In order to address these challenges, hierarchical architectures with distributed processing techniques are envisioned to be relevant for this task, while ensuring scalability. In this work we perform algorithm-architecture codesign to propose two distributed interference cancellation algorithms, and a tree-based interconnection topology for uplink processing. We also analyze the performance, hardware requirements, and architecture trade-offs for a discrete LIS, in order to provide concrete case studies and guidelines for efficient implementation of LIS systems.

A Survey On Wireless Communications : 6g And 7g

One of the fastest growing sectors is wireless technology, which is evolving in all areas of mobile and wireless communications. Wireless technology has increased greatly in the last decade. 7.5 Generation (G) represents the history of wireless technology today. With 6G and 7G, data transmission rates will be higher over Future Generation wireless technology. With new technologies emerging in all fields of mobile and wireless communications, wireless technology continues to emerge as one of the hottest sectors with a high rate of development. Currently, 5G mobile communications systems are just getting started. Our current infrastructure supports a number of technologies, including voice over IP (VoIP), broadband data access over wireless, and more. This paper discusses several generations of wireless technologies from 0G to 7G. Wireless technology is important and beneficial to society. In this paper, we compare all of the generations and explain how each generation uses technology in its execution, application, and usage.

Free-space optical communication: From space to ground and ocean

During the last decade, there has been rapid advancement in the area of mobile broadband and wireless communication. The demand for higher data rates and capacity has continuously increased thanks to the growing need for information exchange. Currently, the data rates of the existing state-of-the-art radio-frequency (RF) or microwave technologies can no longer meet the ever-growing demand.

Federated Learning and Wireless Communications

Federated learning becomes increasingly attractive in the areas of wireless communications and machine learning due to its powerful learning ability and potential applications. In contrast to other machine learning techniques that require no communication resources, federated learning exploits communications between the central server and the distributed local clients to train and optimize a model. Therefore, how to efficiently assign limited communication resources to train a federated learning model becomes critical to performance optimization. On the other hand, federated learning, as a brand-new tool, can potentially enhance the intelligence of wireless networks. In this article, we provide a comprehensive overview of the relationship between federated learning and wireless communications, including basic principles of federated learning, efficient communications for training a federated learning model, and federated learning for intelligent wireless applications. We also identify some research challenges and directions at the end of this article.

Optimization of Spectral Efficiency in Massive MIMO Network for Different Deployment Scenarios

Background: Spectrum efficiency is labelled to be the most discussed area of wireless communication. Today, wireless communication is one of the fastest developing fields due to which there is a tremendous increase in subscribers that leads to the demand for more spectrum. Though the growth in the spectrum is not possible but optimizing it is a good alternative. Methods: This paper provides a detailed study of different methods used for the optimization of spectrum efficiency in massive multiple inputs and outputs. The main goal of this paper is to findout how the spectrum could be used efficiently to meet user demands. It includes the technique of fixing specific parameters like coherent block length, number of reception antennas, pilots reuse factor, signal to noise ratio, and number of users to make more efficient use of the spectrum. This paper also explains the achievement of spectral efficiency under different deployment scenarios i.e., urban, suburban, and rural in ITU-R M.2135 standard. Results: As seen from the results, steep SEs are accomplished by making a schedule of many UE for mutual broadcast, while the SE per UE maybe 1-4 bit/s/Hz. These high-class demonstrations show that massive MIMO e.g an SNR of 0-5 dB with a limited pilot reuse factor of β= 3, and the fast techniques are applied for lessening the distortion noise and instrument damage. According to the simulations, it is found that massive MIMO with M = 100 can produce a 10×gain in SE in the IMT-Advanced requirements of 3 bit/s/Hz/cell. For the bigger sizes of antennas, M = 500 massive MIMO can even give 40×gain over IMT-Advanced. Conclusion: With the advancement of technology, the number of users is increasing tremendously, leading to a shortage of spectrum. Hence, the need of the hour is to make efficient use of the available spectrum while maintaining the Quality of service. Therefore, researchers have proposed specific methods that fulfill this need. The paper realizes the SE approach on different deployment scenarios like urban, suburban and rural in the ITU-R M.2135 standard and proves that under all the three scenarios, P-ZF remained unchanged. As seen from the results, steep SEs are accomplished by making a schedule of many UE for mutual broadcast, while the SE per UE maybe 1-4 bit/s/Hz. These high-class demonstrations show that massive MIMO likes an SNR of 0–5 dB with a limited pilot reuse factor of β= 3, and the fast techniques are applied for lessening the distortion noise from instrument damage. According to the simulations, it is seen that massive MIMO with M = 100 can produce a 10×gain in SE in the IMT-Advanced requirements of 3 bit/s/Hz/cell. For the bigger sizes of antennas, M = 500 massive MIMO can even give 40×gain over IMT-Advanced. The outcomes in this paper suggest the uncorrelated fading, although for decreasing inter-user interference, correlated fading is required, to raise large SE with less β. This study makes SE independent of topography. Furthermore, optimization of energy under different deployment scenarios, along with these simulations, can optimize the spectrum to a greater extent.

Internet of Things and Next Generation Wireless Communication Systems

Next generation wireless communication systems will connect billions of Internet of Thing (IoT) devices and user elements along with billions of people, enable machine-to-ma-chine communications across heterogeneous and dynamic environment, and provide low-latency computing and storage resources on demand at the deep edge as well as in the cloud. Tremendous research and development efforts have already been emphasized on the enabling technologies toward next generation wireless systems to support a variety of critical and personalized services in multiple application domains, including industry use cases, environment, transportation, education, public health and safety, and defense. Wireless communication networks have been greatly advanced by exploiting technologies such as millimeter wave, dynamic spectrum sharing, massive MIMO, beam forming, network slicing and virtualization, and artificial intelligence and machine learning. These technology breakthroughs can empower wireless networks to support extreme high capacity, massive connectivity, and ultra-low latency communications for new use cases identified for next generation wireless systems. In order to design and deploy wireless communication systems with IoT devices across heterogeneous and dynamic environments to provide next generation wireless services, however, there are many critical technical challenges yet to be addressed. In this issue of IEEE Wireless Communications, we are pleased to present two feature topics to bring together researchers, industry practitioners, and individuals working on the related areas to address some of these technical challenges for IoT and next generation wireless systems. One feature topic on “Massive Machine-Type Communications for IoT” includes four articles, and was organized by guest editors W. Ji, T. Ebrahimi, Z. Li, J. Yuan, D. O. Wu, and Y. Xin; the other feature topic on “Emerging Visual IoT Technologies for Future Communications and Networks” includes six articles, and was organized by guest editors L. Liu, E. G. Larsson, P. Popovski, G. Caire, X. Chen, and S. R. Khosravirad. Thanks to the two guest editor teams who did an excellent job in editing these two feature topics for our readers. Please stay tuned for new developments in the research area of IoT and next generation wireless communications and read the editorials and the papers in the feature topics.

Bandpass NGD investigation of O-shape fully distributed structure with S-matrix modelling

PurposeThe aim of this paper is to provide the theoretical conceptualization of a bandpass (BP) negative group delay (NGD) microstrip circuit. The main objective is to provide a theorization of the particular geometry of the microstrip circuit with experimental validation of the NGD effect.Design/methodology/approachThe methodology followed in this work is organized in three steps. A theoretical model is established of equivalent S-parameters model using Y-matrix analysis. The GD analysis is also presented by showing that the circuit presents a possibility to generate NGD function around certain frequencies. To validate the theoretical model, as proof-of-concept (POC), a microstrip prototype is designed, fabricated and tested.FindingsThis work clearly highlighted the modelled (analytical design model), simulated (ADS simulation tool) and measured results are in good correlation. Relying on the proposed theoretical, numerical and experimental models, the BP NGD behaviour is validated successfully with GD responses specified by the NGD centre frequency: it is observed around 2.35 GHz, with an NGD value of about −2 ns.Research limitations/implicationsIt is to be noticed the proposed GD analysis requires limitations of the theoretical NGD model. It is depicted and validated through a POC demonstrating that the circuit presents a possibility to generate NGD function around certain frequencies (assuming constraints around usable frequency and bandwidth).Practical implicationsThe NGD O-shape topology developed in this work could be exploited in the future in the microwave and radiofrequency context. Thus, it is expected to develop GD equalization technique for radiofrequency and microwave filters, GD compensation of oscillators, filters and communication systems, design of broadband switch-less bi-directional amplifiers, efficient enhancement of feedforward amplifiers, design method of frequency independent phase shifters with negligible delay, synthesis method of arbitrary-angle beamforming antennas. The BP NGD behavior may also be successfully used for the reduction of resonance effect for the electronic compatibility (EMC) of electronic devices.Social implicationsThe non-conventional NGD O-circuit theoretical development and validation through experimental POC could be exploited by academic and industrial developers in the area of wireless communications including, but not restricted to, 5-generation communication systems. The use of the remarkable NGD effect is also useful for the mitigation of electromagnetic interferences between electronic devices and more and more complex electromagnetic environment (current development of Internet of Things[ IoT]).Originality/valueThe originality of this work relies on the new NGD design proposed in this work including the extraction of S-matrix parameters of the microstrip novel structure designed. The validation process based upon an experimental POC showed very interesting levels of NGD O-circuit (nanosecond-GD duration).