Wireless Personal Communications最新文献

In recent years, the rapid advancement of technology has paved the way for innovative solutions aimed at enhancing personal safety and security. Among these, wearable Internet of Things (IoT) devices have emerged as a significant development, particularly in safeguarding vulnerable groups such as women and children. This paper introduces a smart security solution that leverages wearable IoT systems to provide real-time monitoring and protection. The increasing incidence of crimes against women and children highlights the urgent need for effective safety measures. Traditional security approaches often fall short in offering immediate assistance or preventive measures. However, wearable IoT devices, equipped with sensors and connectivity features, offer a proactive approach to security. These devices can monitor various physiological and environmental parameters, detect potential threats, and trigger timely alerts to guardians or authorities Our proposed smart security solution integrates advanced IoT technologies with user-friendly wearable devices designed specifically for women and children. This system encompasses several critical components, including GPS tracking, real-time communication, health monitoring, and emergency alert mechanisms. By harnessing the power of IoT, this solution aims to provide continuous protection, enhance situational awareness, and facilitate rapid response in case of emergencies. In this paper, we will explore the design, functionality, and potential impact of wearable IoT devices in improving the safety and security of women and children. We will also discuss the challenges and considerations in implementing such systems, including privacy concerns, data security, and the need for reliable connectivity. Through this comprehensive examination, we aim to demonstrate the viability and importance of IoT-based wearable technology in fostering a safer environment for vulnerable populations.

Non-orthogonal multiple access (NOMA) can be a desirable method since it can utilize resources efficiently to provide larger capacity. Similarly, optical transmission is also becoming popular due to the availability of licence-free large bandwidth and low-cost transceiver implementation. Although optical NOMA system can be promising for long range wireless systems, investigation of its reliability performance is essential for different channel models. In this study, outage probability, channel capacity, symbol error rate expressions, diversity and coding gains for arbitrary number of users are obtained for downlink-NOMA over free space optical links modeled with Málaga distribution. Theoretical results are verified by numerical examples for various scenarios providing useful background for future analyses and designs.

The understanding of how users in a network update their opinions based on their neighbours’ opinions has attracted a great deal of interest in the field of network science, and a growing body of literature recognises the significance of this issue. In this work, we propose a new dynamic model of opinion formation in directed networks. In this model, the opinion of each node is updated as the weighted average of its neighbours’ opinions, where the weights represent social influence. We define a new centrality measure as a social influence metric based on both influence and conformity. We measure this new approach using two opinion formation models: (i) the Degroot model and (ii) our own proposed model. Previously studies have not considered conformity, and have only considered the influence of the nodes when computing the social influence. In our definition, nodes with low in-degree and high out-degree that were connected to nodes with high out-degree and low in-degree had higher centrality. As the main contribution of this research, we propose an algorithm for finding a small subset of nodes in a social network that can have a significant impact on the opinions of other nodes. Experiments on real-world data demonstrate that the proposed algorithm significantly outperforms previously published state-of-the-art methods.

Accurate signal path loss models for predictions are crucial in current cellular communication networks. Recently, numerous path loss estimation methods have been presented to improve the efficiency of networks. However, most of these existing models do not include spatial data such as land use/land cover, terrain elevation, building height, and the effect of topography. To address this issue, this study proposes a GeoAI-based technique for path loss estimation in cellular communication networks, addressing existing models’ lack of spatial data integration. Support Vector Regression, K-Nearest Neighbor, Random Forest, and multi-layer perceptron (MLP) artificial neural network models are evaluated using field measurements in an urban, suburban area in Van, Turkey, across various frequencies. Among the models, MLP with three hidden layers, nine input variables, hyperbolic tangent activation function, and Adam optimization method performs best. At 900 MHz, MLP has been observed with MSE, RMSE, MAE, and R values of 0.22 dB, 0.47 dB, 0.46 dB, and 0.99 dB, respectively. Lastly, a comparison of the developed model to the Free space, COST 231, Ericsson, and SUI models revealed that the GeoAI-based path loss models outperformed the empirical models regarding prediction accuracy and generalization. This study underscores the significance of integrating spatial data into path loss prediction, particularly in diverse urban and suburban environments, for optimizing cellular communication networks.

In recent times, Vehicular Ad hoc Network (VANET) has been the focal point of the research community to devise efficient smart transportation systems. VANET provides the key advantage of providing cautionary measures and safety to passengers and drivers. With the evolution of fifth-generation (5G) network technology and rapid growth in vehicles, it becomes challenging for conventional VANET to manage large-scale dynamic heterogeneous networks due to their limited flexibility and scalability features. Moreover, the dynamic nature of VANET makes it vulnerable to malicious attacks. Software Defined Networking (SDN) is a technology that provides an integrated improvement over the conventional VANETs. SDN architecture is flexible, programmable, scalable, and provides globally the knowledge of the network. However, its centralized nature makes SDN based VANETs a prime target of attackers, which may adversely impact the VANETs causing life-threatening consequences. To address these issues, this paper presents two novel schemes. Firstly, this paper presents a trusted routing scheme named Jellyfish Chimp Optimization Algorithm (JChOA) for SDN based VANETs. JChOA is designed by amalgamation of the Jellyfish Search Optimization algorithm (JS) and Chimp Optimization algorithm (ChOA). Secondly, this paper presents an attack detection and mitigation scheme named JChOA_RideNN for SDN based VANETs. This attack detection scheme utilizes the Rider Optimization Algorithm based neural network (RideNN) architecture at the SDN controller, where the weighting parameters of RideNN tunned through the use of JChOA. The effectiveness of JChOA routing is evaluated based on the metrics energy and trust value where the performance of JChOA_RideNN is assessed using precision and recall. Moreover, the JChOA routing algorithm attained greater performance with a maximum of 0.947 J energy and 0.462 trust value and JChOA_RideNN attained with a maximum of 93.9% precision, and 93.1% recall than other traditional approaches. The results of the experiments clearly show the effectiveness of the proposed defensive schemes for SDN based VANETs.

A novel compact quad-band multiple-input-multiple-output antenna (MIMO) with high isolation is presented for universal mobile telecommunications systems (UMTS), wireless local area network (WLAN), and 5G: sub-6 GHz wireless communication applications. The proposed antenna is simulated, fabricated on low cost FR4-epoxy substrate of overall size 25 × 50 × 0.8 mm³. The proposed antenna comprises of two orthogonally placed radiators on top of substrate and ISI-shaped defected ground structure (DGS) on the bottom side. High isolation of above 20 dB is achieved with DGS and orthogonal arrangement of antenna elements. The proposed antenna is fabricated and results are tested. The measured results are well matched with simulated results. The antenna resonates at 1.98 GHz (UTMS), 2.75 GHz (WLAN), 3.37 GHz (5G/n78) and 4 GHz (5G/n77) bands with high gain and radiation efficiency. The simulated and measured results demonstrate that the proposed structure is well suitable for wireless communication applications.

Search and rescue counts as a prominent sector, and its importance is magnified by the recent increase in natural calamities caused due to global warming. Though a lot of new technologies have been integrated into the present search and rescue architecture, there are still many obstacles. These reduce the efficiency of this integration. Edge computing is embodied as a subdivision of artificial intelligence. It endeavors to decentralize existing computing from a central server and bring it closer to the edge. Search and rescue is a unique field and has few special operation constraints and difficulties. They arise due to the conditions under which the operations are carried out. Edge computing is an ideal fit for the search and rescue scenario. Many of edge computing’s key advantages align well with the requirements of the search and rescue venture. This article reviews the scope of implementing edge computing into a search and rescue procedure. It also elaborates on the various problems that can be resolved using edge computing while illustrating the present literature available on the topic. The article discerns open research issues in this field. Doing so proposes a future direction for investigation in the application of edge data processing in search and rescue.

In the field of wireless sensor networks, node localization is a key research issue. As a classical range-free localization scheme, the localization accuracy of distance vector-hop (DV-Hop) algorithm needs to be further improved. Therefore, an improved DV-Hop location algorithm based on variable communication radius (VCR IDV-Hop) is proposed in this paper. Firstly, by changing the communication radius of the anchor nodes, hop counts between nodes are refined from integer to decimal, which improves the accuracy of estimated distance between nodes. Secondly, the calculation of the average hop size of anchor nodes is abstracted into a combinatorial optimization problem, and the binary bat algorithm (BBA) is applied to solve it. Finally, when the unknown node is located, only part of anchor nodes with smaller hop counts from the unknown node are selected to participate in the localization. Simulation results show that VCR IDV-Hop greatly improves the localization accuracy of nodes compared with other excellent localization algorithms.

In this paper, a compact 2-port MIMO antenna for New Radio (NR) FR-1 5G sub-6 GHz mid-band applications is proposed. This antenna contains a simple united circular patch and rectangular patch, feedline, and parasitic elements on top followed by a simple stepped T-shaped slot embedded in the ground at the bottom of the substrate flame retardant-4. The optimized dimensions of 0.7(lambda _0) (times) 0.5(lambda _0) (times) 0.0267(lambda _0). A Defective Ground Structure is used to attain return loss at −10 dB with an impedance bandwidth of 80% radiating from 3 to 7 GHz. and two parasitic elements are placed between antenna elements to improve the isolation between port to port with a minimum value of (< -)15 dB. The radiation characteristics of the antenna, stable patterns, acceptable cross-polarization, high gain, and higher efficiency are verified and better results are attained. The MIMO antenna diversity parameters are evaluated in terms of ECC (<0.025), CCL (<0.022 bps/Hz), TARC (<10 dB), and MEG ((<-)3 dB). The simulated and measured results are within the limits and achieve better performance. Hence, the proposed antenna design can be envisaged for NR 5G Sub-6 GHz FR-1 mid-band (5G NR bands: N77, n78, n79; Wi-Fi bands: Wi-Fi 5, Wi-Fi-6 and V2X/DSRC) wireless applications.

As the demand for high-speed communication in 5G increases, this article presents a development breakthrough in millimeter-wave spectrum solutions. The focus is on designing an ultra-wideband (UWB) circular patch antenna for 5G millimeter-wave applications. To address the problem of limited bandwidth and efficiency in existing designs, a UWB antenna operating in the 20–45 GHz range with a compact form factor of (4 times 4.8 times 0.508 ,,{hbox {mm}}^{3}) has been developed. A radial basis function neural network (RBFNN) was employed to analyze and optimize the antenna’s bandwidth characteristics. The resulting antenna exhibits a wide bandwidth of 25 GHz, a gain of 5.75 dB, and an impressive efficiency of 99%. To extend the capabilities of the design, a (4 times 4) MIMO antenna system was developed, incorporating four copies of the proposed UWB single antenna, achieving an extended bandwidth of 25 GHz. The MIMO system, with dimensions of (17.5 times 17.5 times 0.508,,{hbox {mm}}^{3}), demonstrates excellent performance with isolation exceeding 30 dB, a gain of 6 dB, and high efficiency. Rigorous measurements validate the designs, affirming their practical viability for future 5G mmWave applications. In conclusion, the proposed UWB antenna and MIMO system offer significant advancements in 5G mmWave communication, providing high performance in bandwidth, gain, and efficiency, supported by comprehensive simulations and measurements.