The fourth Industrial Revolution is expected to lead to an era of technological innovation and digitization that would require connectivity by the users, anywhere and anytime. The fifth generation of wireless communication systems and the technologies therein are being explored to cater to high connectivity needs that encompass high data rates, very low latencies, energy-efficient systems, etc. A multiuser

Cell-free massive distributed antenna system (CF-MDAS) can further reduce the access distance between mobile stations (MSs) and remote access points (RAPs), which brings a lower propagation loss and higher multiplexing gain. However, the interference caused by the overlapping coverage areas of distributed RAPs will severely degrade the system performance in terms of the sum-rate. Since that clustering

The randomness of public health events requires that the cloud-native architecture, as the mainstream architecture of the new generation of the public health information system, has the appropriate flexibility to meet the needs of environmental change. The flexible acquisition of cloud-native architecture requires organizations to invest additional resources. How to plan and formulate resource input

In order to improve the training level of Sanda movement, this article uses an image analysis method to reconstruct the detailed characteristics of the movement and apply them to the actual training process. Since the traditional wavelet reconstruction method is affected by the accuracy of the decomposition scale, this paper proposes an improved method of Sanda action based on 3D image reconstruction

It is necessary to recognize the target in the situation of military battlefield monitoring and civilian real-time monitoring. Sparse representation-based SAR image target recognition method uses training samples or feature information to construct an overcomplete dictionary, which will inevitably affect the recognition speed. In this paper, a method based on monogenic signal and sparse representation

Considering the ongoing development of various devices and rich applications in intelligent Internet of Things (IoT) systems, it is a crucial issue to solve secure transmission of legitimate signals for massive data sharing in the systems. Cooperative jamming-based physical layer security is explored to be a complement of conventional cryptographic schemes to protect private information. Yet, this

Resampling is an operation to convert a digital speech from a given sampling rate to a different one. It can be used to interface two systems with different sampling rates. Unfortunately, resampling may also be intentionally utilized as a postoperation to remove the manipulated artifacts left by pitch shifting, splicing, etc. To detect the resampling, some forensic detectors have been proposed. Little

Existing greedy reconstruction algorithms require signal sparsity, and the remaining sparsity adaptive algorithms can be reconstructed but cannot achieve accurate sparsity estimation. To address this problem, a blind sparsity reconstruction algorithm is proposed in this paper, which is applied to compressed sensing radar receiver system. The proposed algorithm can realize the estimation of signal sparsity

In the current age of advanced technologies, there is an escalating demand for reliable wireless systems, catering to the high data rates of mobile multimedia applications. This article presents a novel approach to the concept of Self-Concatenated Convolutional Coding (SECCC) with Sphere Packing (SP) modulation via Differential Space-Time Spreading- (DSTS-) based smart antennas. The two transmitters

Many rural areas along Spain do not have access to the Internet. Despite the huge spread of technology that has taken place during recent years, some rural districts and isolated villages have a lack of proper communication infrastructures. Moreover, these areas and the connected regions are notably experiencing a technological gap. As a consequence of this, the implementation of technological health

An important goal of indoor positioning systems is to improve positioning accuracy as well as reduce power consumption. In this paper, we propose an indoor positioning method based on the received signal strength (RSS) fingerprint. The proposed method used a certain criterion to select fixed access points (FPs) in an offline phase instead of an online phase for location estimation. Principal component

Content-centric networks (CCNs) have become a promising technology for relieving the increasing wireless traffic demands. In this paper, we explore the scaling performance of mobile content-centric networks based on the nonuniform spatial distribution of nodes, where each node moves around its own home point and requests the desired content according to a Zipf distribution. We assume each mobile node

Now, it is common for patients and medical institutions to outsource their data to cloud storage. This can greatly reduce the burden of medical information management and storage and improve the efficiency of the entire medical industry. In some cases, the group-based cloud storage system is also very common to be used. For example, in an medical enterprise, the employees outsource the working documents

Recently, in order to extend the computation capability of smart mobile devices (SMDs) and reduce the task execution delay, mobile edge computing (MEC) has attracted considerable attention. In this paper, a stochastic optimization problem is formulated to maximize the system utility and ensure the queue stability, which subjects to the power, subcarrier, SMDs, and MEC server computation resource constraints

In recent years, deep learning has been used for Wi-Fi fingerprint-based localization to achieve a remarkable performance, which is expected to satisfy the increasing requirements of indoor location-based service (LBS). In this paper, we propose a Wi-Fi fingerprint-based indoor mobile user localization method that integrates a stacked improved sparse autoencoder (SISAE) and a recurrent neural network

With the maturity of modern science and technology, such as networks and computers, Internet of Things has been widely used in various fields of industry, opening up a new situation for the development of the industry and creating a broader development platform. This paper systematically analyzes the characteristics and changes of the commodity structure, regional structure, market structure, and main

Downlink transmission techniques for multiuser (MU) multiple-input multiple-output (MIMO) systems have been comprehensively studied during the last two decades. The well-known low complexity linear precoding schemes are currently deployed in long-term evolution (LTE) networks. However, these schemes exhibit serious shortcomings in scenarios when users’ channels are strongly correlated. The nonlinear

With the increasing development of our country and the world, the importance of English as an international language is self-evident. But we have difficulty in English translation, especially the vocabulary and translation of business English letters, not only because we have different living habits but also because we have different ways of speaking. Based on the research of functional equivalence

As an information carrier, face images contain abundant sensitive information. Due to its natural weak privacy, direct publishing may divulge privacy. Anonymization Technology and Data Encryption Technology are limited by the background knowledge and attack means of attackers, which cannot completely content the needs of face image privacy protection. Therefore, this paper proposes a face image publishing

In the future, the tactical edge is far away from the command center, the resources of communication and computing are limited, and the battlefield situation is changing rapidly, which leads to the weak connection and fast changes of network topology in a harsh and complex battlefield environment. Thus, to meet the needs of communication and computing to build a new generation of computing architecture

With the trend of low emissions and sustainable development, the demand for hybrid electric vehicles (HEVs) has increased rapidly. By combining a conventional internal combustion engine with one or more electric motors powered by a battery, HEVs have the advantages over traditional vehicles in better fuel economy and lower tailpipe emissions. Nevertheless, the power management strategies (PMSs) for

Person reidentification (re-id) suffers from a challenging issue due to the significant inconsistency of the camera network, including position, view, and brands. In this paper, we propose a deep camera-aware metric learning (DCAML) model, where images on the identity-level spaces are further projected into different camera-level subspaces, which can explore the inherent relationship between identity

The main target of this article is to propose a simple Received Signal Strength Indicator- (RSSI-) based adaptive Physical Layer (PHY) selection approach for Bluetooth Low Energy 5.0 (BLE 5) and compare the performance of adaptive PHY selection with the performance of individual PHY. This article also validates the simulation results acquired from the in-house developed Ray Tracing (RT) tool with the

The frequency stability of multi-microgrids is easily affected by random load fluctuations and intermittent renewable resources. Additionally, geographically distributed generation equipment usually cannot adopt the “point-to-point” dedicated communication scheme to realize the information exchange considering the construction and computation costs. Therefore, a H∞-switching frequency control strategy

In wireless sensor networks for the Internet of Things (WSN-IoT), the topology deviates very frequently because of the node mobility. The topology maintenance overhead is high in flat-based WSN-IoTs. WSN clustering is suggested to not only reduce the message overhead in WSN-IoT but also control the congestion and easy topology repairs. The partition of wireless mobile nodes (WMNs) into clusters is

The existing cloud storage methods cannot meet the delay requirements of intelligent devices in the power distribution Internet of Things (IoT), and it is difficult to ensure the data security in the complex network environment. Therefore, a data Security Storage method for the power distribution IoT is proposed. Firstly, based on the “cloud tube edge end” power distribution IoT structure, a cloud

In recent years, there has been keen interest in the area of Internet of Things connected underground, and with this is the need to fully understand and characterize their operating environment. In this paper, a model, based on the Peplinski principle, for the propagation of waves in soils that takes into account losses attributable to the presence of local inhomogeneity is proposed. In the work, it

Wi-Fi-based indoor localization has received extensive attention in wireless sensing. However, most Wi-Fi-based indoor localization systems have complex models and high localization delays, which limit the universality of these localization methods. To solve these problems, a depthwise separable convolution-based passive indoor localization system (DSCP) is proposed. DSCP is a lightweight fingerprint-based

Considering the increasing importance of user experience and the influence of gamification techniques in the online business environment. This research explores the antecedents and outcomes of user experience in the context of website features. We proposed a multimediation conceptual framework integrating several constructs to test the user response about online gamification. This study used PLS-SEM

Wireless Sensor Networks (WSNs) have gained global attention in recent times due to their vast applications in various fields. These networks can face the disruption of data transmission due to sensor node failures when placed in harsh, inaccessible, and adverse environments such as battlefields or monitoring in enemy territory. The specific tasks performed by the collaboration among the sensor nodes

With the development of Internet technology, especially the application of mobile Internet technology in people’s daily lives, people’s lifestyles and production methods have changed, and they have brought huge economic benefits to society. In order to improve the development quality of agricultural e-commerce and expand the integration model of e-commerce, the paper analyzes the development and changes

Communication-Based Train Control (CBTC) system is a critical signal system to ensure rail transit’s safe operation. Compared with the train-ground CBTC system, the train control system based on train-to-train (T2T) communication has the advantages of fast response speed, simple structure, and low operating cost. As the core part of the train control system based on T2T communication, the reliability

Free space optical (FSO) communication systems provide wireless line of sight connectivity in the unlicensed spectrum, and wireless optical communication achieves higher data rates compared to their radio frequency (RF) counterparts. FSO systems are particularly attractive for last mile access problem by bridging fiber optic backbone connectivity to RF access networks. To cope with this practical deployment

The authorization mechanism of smart devices is mainly implemented by firmware, yet many smart devices have security issues about their firmware. Limited research has focused on securing the firmware of smart devices, although increasingly more smart devices are used to deal with the very sensitive applications, activities, and data of users. Thus, research on smart device firmware security is of growing

With the outbreak of COVID-19, people’s demand for using the Internet of Medical Things (IoMT) for physical health monitoring has increased dramatically. The considerable amount of data requires stable, reliable, and real-time transmission, which has become an urgent problem to be solved. This paper constructs a health monitoring-enabled IoMT network which is composed of several users carrying wearable

An excellent dialogue system needs to not only generate rich and diverse logical responses but also meet the needs of users for emotional communication. However, despite much work, these two problems have not been solved. In this paper, we propose a model based on conditional variational autoencoder and dual emotion framework (CVAE-DE) to generate emotional responses. In our model, latent variables

As a representative technology of artificial intelligence, 3D reconstruction based on deep learning can be integrated into the edge computing framework to form an intelligent edge and then realize the intelligent processing of the edge. Recently, high-resolution representation of 3D objects using multiview decomposition (MVD) architecture is a fast reconstruction method for generating objects with

Massive multiple-input multiple-output (MIMO) systems operating at millimeter-wave (mmWave) frequencies promise to satisfy the demand for higher data rates in mobile communication networks. A practical challenge that arises is the calibration in amplitude and phase of these massive MIMO systems, as the antenna elements are too densely packed to provide a separate calibration branch for measuring them

Industrial control systems (ICS) involve many key industries, which once attacked will cause heavy losses. However, traditional passive defense methods of cybersecurity have difficulty effectively dealing with increasingly complex threats; a knowledge graph is a new idea to analyze and process data in cybersecurity analysis. We propose a novel overall framework of data-driven industrial control network

With the development of deep learning, trackers based on convolutional neural networks (CNNs) have made significant achievements in visual tracking over the years. The fully connected Siamese network (SiamFC) is a typical representation of those trackers. SiamFC designs a two-branch architecture of a CNN and models’ visual tracking as a general similarity-learning problem. However, the feature maps

In the tropical regions, when a signal is transmitted from a transmitter to a receiver, the signal gets highly attenuated because of heavy rainfall. By using different diversity techniques, this signal attenuation is minimized. The multiple-input multiple-output (MIMO) system is an antenna diversity technique, and in this paper, this technique has been applied to the proposed communication link model

In this research work, we have presented an iterative joint source channel decoding- (IJSCD-) based wireless video communication system. The anticipated transmission system is using the sphere packing (SP) modulation assisted differential space-time spreading (DSTS) multiple input-multiple output (MIMO) scheme. SP modulation-aided DSTS transmission mechanism results in achieving high diversity gain

To cope with an exponentially increasing demand on mobile data traffic in cellular network, proximity-based opportunistic vehicular communications can be exploited as a complementary mean to offload and reduce the load of cellular network. In this paper, we propose a two-phase approach for mobile data traffic offloading, which exploits opportunistic contact and future utility with user mobility. The

In the era of the Internet of Things (IoT), connected objects produce an enormous amount of data traffic that feed big data analytics, which could be used in discovering unseen patterns and identifying anomalous traffic. In this paper, we identify five key design principles that should be considered when developing a deep learning-based intrusion detection system (IDS) for the IoT. Based on these principles

The electrocardiogram (ECG) signal can easily be affected by various types of noises while being recorded, which decreases the accuracy of subsequent diagnosis. Therefore, the efficient denoising of ECG signals has become an important research topic. In the paper, we proposed an efficient ECG denoising approach based on empirical mode decomposition (EMD), sample entropy, and improved threshold function

5G applications face security risks due to the new technology used and the performance requirements of the specific application scenario. This paper analyzes the security requirements and presents hierarchical solutions for stakeholders to build secure 5G applications. First, we summarize the technical characteristics and typical usage scenarios of 5G. Then, we analyze the security and privacy risks

The Industrial Internet of Things (IIoT), as a special form of Internet of Things (IoT), has great potential in realizing intelligent transformation and industrial resource utilization. However, there are security and privacy concerns about industrial data, which is shared on an open channel via sensor devices. To address these issues, many searchable encryption schemes have been presented to provide

Here, a high-precision mutual coupling coefficient estimation method is proposed that is more suitable for adaptive beamforming than traditional algorithms. According to the relationship between the designed transition matrix and the signal, the proposed algorithm selects the transition matrix corresponding to the high-power signal. The high-precision estimation of the mutual coupling coefficient is

The traditional classroom has been impacted by the digital teaching resources. Students are no longer satisfied with the traditional teaching mode of teacher teaching and student learning. Combined with the characteristics of a virtual reality-interactive classroom, the design of a virtual reality-interactive classroom based on the deep learning algorithm is proposed. This paper divides the teaching

In order to accurately predict the channels and prices of the e-commerce market, and thereby control the cost of the e-commerce market, this paper studies the channel model and price dispersion of the e-commerce market from the perspective of suppliers. First, this paper establishes a model to analyze the price dispersion structure under different proportions of informed consumers and theoretically

The farmers of agricultural farms manage and monitor different types of livestock. The manual inspection and monitoring of livestock are tedious since the cattle do not stay at fixed locations. Fencing many cattle requires a considerable cost and involves farmers’ physical intervention to keep an eye to stop them from crossing beyond the access points. Visual tracking of livestock and fencing is a

The development of Internet of Things (IoT) and Mobile Edge Computing (MEC) has led to close cooperation between electronic devices. It requires strong reliability and trustworthiness of the devices involved in the communication. However, current trust mechanisms have the following issues: (1) heavily relying on a trusted third party, which may incur severe security issues if it is corrupted, and (2)

With the increasing number of smart mobile devices, applications based on mobile network take an indispensable role in the Internet of Things. Due to the limited computing power and restricted storage capacity of mobile devices, it is very necessary to design a secure and lightweight authentication scheme for mobile devices. As a lightweight cryptographic primitive, the hash chain is widely used in

To accurately detect small defects in urine test strips, the SK-FMYOLOV3 defect detection algorithm is proposed. First, the prediction box clustering algorithm of YOLOV3 is improved. The fuzzy C-means clustering algorithm is used to generate the initial clustering centers, and then, the clustering center is passed to the K-means algorithm to cluster the prediction boxes. To better detect smaller defects

In recent years, the number of web services grows explosively. With a large amount of information resources, it is difficult for users to quickly find the services they need. Thus, the design of an effective web service recommendation method has become the key factor to satisfy the requirements of users. However, traditional recommendation methods often tend to pay more attention to the accuracy of

Aiming at the shortcomings of some existing interval-valued intuitionistic fuzzy entropy, this paper proposes an interval-valued intuitionistic fuzzy entropy, which contains not only the interval distance between membership and nonmembership but also the average hesitancy information. On this basis, the impact evaluation of microblog users is studied. Through the multilevel decomposition of user influence

The visual recognition of Android malicious applications (Apps) is mainly focused on the binary classification using grayscale images, while the multiclassification of malicious App families is rarely studied. If we can visualize the Android malicious Apps as color images, we will get more features than using grayscale images. In this paper, a method of color visualization for Android Apps is proposed

In this paper, a sparse recovery algorithm based on a double-pulse FDA-MIMO radar is proposed to jointly extract the angle and range estimates of targets. Firstly, the angle estimates of targets are calculated by transmitting a pulse with a zero frequency increment and employing the improved -SVD method. Subsequently, the range estimates of targets are achieved by utilizing a pulse with a nonzero frequency

Deep learning has become the most mainstream technology in artificial intelligence (AI) because it can be comparable to human performance in complex tasks. However, in the era of big data, the ever-increasing data volume and model scale makes deep learning require mighty computing power and acceptable energy costs. For electrical chips, including most deep learning accelerators, transistor performance

In this paper, a novel digital video resolution enhancement algorithm based on adaptive directional interpolation is proposed, where the directionality of the edge structure and the nonlocal self-similarity prior within the current frame as well as its adjacent frames are both considered. First, we establish the regularization equation that conforms to the prior model of a video frame and then take