Wireless Communication Environment Research Articles

Ordinary Differential Equation-Based CNN for Channel Extrapolation Over RIS-Assisted Communication

The reconfigurable intelligent surface (RIS) is considered as a promising new technology for reconfiguring wireless communication environments. To acquire the channel information accurately and efficiently, we only turn on a fraction of all the RIS elements, formulate a sub-sampled RIS channel, and design a deep learning based scheme to extrapolate the full channel information from the partial one. Specifically, inspired by the ordinary differential equation (ODE), we set up connections between different data layers in a convolutional neural network (CNN) and improve its structure. Simulation results are provided to demonstrate that our proposed ODE-based CNN structure can achieve faster convergence speed and better solution than the standard CNN.

Modeling of the Schemes for Organizing a Session of Person–System Interactions in the Information System for Critical Use Which Operates in a Wireless Communication Environment

In this article, for the first time, a new mathematical model of the schemes for organizing a session of person–system interactions between the registration center server of the information system for critical use (ISCU) and the terminal of the person-user in a wireless communication environment are presented. In contrast to the existing literature, this article uses the mathematical apparatus of queuing systems to describe the schemes of organizing the stochastic process of a session of person–system interaction in discrete or continuous time, namely, models of the type Geo/Geo/1 with group arrival and ordinary service for the case of discrete representation of time and models of the type M/G/1 for the case of continuous time representation. The use of the mathematical apparatus of queuing systems in the studies made it possible to obtain analytical expressions for comparing formalized schemes for organizing the person–system interaction according to such functional characteristics as the average time of downloading a finite number of data blocks into the terminal of the target person-user (average time that the request spent the server of the information system).

A Compact Quasi-Yagi Antenna with High Gain by Employing the Bent Arms and Split-Ring Resonators

A compact quasi-Yagi antenna with bent arms and split-ring resonators (SRRs) is proposed. Compared with traditional quasi-Yagi antennas employing straight arms, the resonant frequency of the proposed antenna could be always consistent with its center frequency, and there is no obvious frequency shift under the process of its miniaturization. The SRRs are adopted in the proposed compact antenna for a high gain of 6.58 dBi. The reliability verification of the proposed antenna radiation characteristics is further experimentally proved with the prototype measurement. The proposed quasi-Yagi antenna has an adjustable compact structure and low frequency offset and could be used in the precise point-to-point wireless communication environment.

Double-IRS Assisted Multi-User MIMO: Cooperative Passive Beamforming Design

Intelligent reflecting surface (IRS) has emerged as an enabling technology to achieve smart and reconfigurable wireless communication environment cost-effectively. Prior works on IRS mainly consider its passive beamforming design and performance optimization without the inter-IRS signal reflection, which thus do not unveil the full potential of multi-IRS assisted wireless networks. In this paper, we study a double-IRS assisted multi-user communication system with the \emph{cooperative} passive beamforming design that captures the multiplicative beamforming gain from the inter-IRS channel. Under the general channel setup with the co-existence of both double- and single-reflection links, we jointly optimize the (active) receive beamforming at the base station (BS) and the cooperative (passive) reflect beamforming at the two distributed IRSs (deployed near the BS and users, respectively) to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of all users. Moreover, for the single-user and multi-user setups, we analytically show the superior performance of the double-IRS cooperative system over the conventional single-IRS system in terms of the maximum signal-to-noise ratio (SNR) and multi-user effective channel rank, respectively. Simulation results validate our analytical results and show the practical advantages of the proposed double-IRS system with cooperative passive beamforming designs.

Performance study of path loss models at 14, 18, and 22 GHz in an indoor corridor environment for wireless communications

The critical rule to achieve extremely high peaks of data transmission is the availability of a tremendous amount of bandwidth. The super high frequency (SHF) and the millimeter-wave (mmWave) frequency bands are the candidates for the deployment of the 5G cellular system and for satisfying future needs due to their massively available blocks of contiguous raw bandwidth that is capable of supporting additional data traffic for multimedia services. This research paper presents propagation measurements at three frequencies above 6 GHz, which are 14, 18, and 22 GHz frequency bands. The measurements were carried out or both line-of-sight (LOS) and non-line-of-sight (NLOS) communication scenarios in an indoor corridor environment to present frequency- and distance-dependent wireless channel models. Moreover, this study presents, investigates, and compares the performance of two well-known path loss prediction models; the single frequency close-in (CI) free space reference distance model and the single frequency floating intercept (FI) model. The LOS comparison study shows that the CI and FI models provide comparable and accurate estimates that fit the real measured data for the frequency bands selected. Furthermore, the study investigates the behavior of the path loss exponent (PLE) and the FI model parameters as a function of the reception angle of arrival (AoA) in the NLOS scenario. It is observed from this work that the path loss models' parameters exhibit symmetrical behavior around 180° AoA. The FI model provides the same standard deviation values as the CI model in the LOS scenario. In contrast, the FI model offers a notable reduction(up to 2.84 dB) compared to the CI model in the NLOS scenario. Finally, the LOS and NLOS results reveal that the CI and FI models can be trusted as good path loss models for corridor environments and exhibit stable behavior over measured distances and frequencies.

An Effective Data Sharing Scheme Based on Blockchain in Vehicular Social Networks

Vehicular social networks (VSNs) are the vehicular ad hoc networks (VANETs) that integrate social networks. Compared with traditional VANETs, VSNs are more suitable to serve a group of vehicles with common interests. In VSNs, vehicles can upload the necessary data in the cloud service provider (CSP) and other vehicles can query the data they are interested in through CSP, which enables VSNs to provide more user-friendly services. However, due to the wireless network communication environment, the data sent by the vehicle can easily be monitored. Adversaries are able to violate the privacy of the vehicle based on the collected data, thereby threatening the security of the entire network. In addition, if a vehicle shares malicious or false data with other vehicles, it is easy to mislead drivers and even cause serious traffic accidents. This paper proposes an effective data sharing scheme based on blockchain in VSNs. By integrating an identity based signature mechanism and pseudonym generation mechanism, we first propose an anonymous authentication mechanism as the basis for establishing trust relationships before data transmission between entities in VSNs. Then, a data sharing scheme based on blockchain is described, in which the signature mechanism and the consensus mechanism guarantee the security and traceability of data. The result of the performance analysis and the simulation experiment indicate that VAB can achieve a favourable performance compared with existing schemes.

Retracted] Analysis of the Needs of English‐Chinese Translation Courses and Research on Teaching Strategies under the Background of Wireless Communication and Big Data

The development of wireless communication technology and the widespread application of big data has accelerated the degree of globalization. Both English and Chinese are widely used languages internationally, and the cultural exchanges between the two occupy a very important proportion in the world. The society’s demand for English‐Chinese translation talents has increased, and colleges and universities have also taken measures to improve students’ English‐Chinese translation ability. This article analyzes the English‐Chinese translation course under the environment of wireless communication and big data, discusses the influence of the development of wireless communication and big data on the teaching of English‐Chinese translation, the problems existing in the teaching of English‐Chinese translation in colleges and universities, and gives solutions to the existing problems. Finally, using the method of online survey to investigate the current situation of English‐Chinese translation teaching in colleges and universities in the province, 245 valid questionnaires were recovered, only 87 of which indicated that their majors offered separate English translation courses, accounting for 35.51% of the total; 158 indicated their majors. There are no English translation courses, accounting for 64.49% of the total. Such a ratio does not match the overall demand for cultural exchanges in the context of the rapid development of wireless technology and big data. Therefore, the convenience brought by new technologies should be actively used to promote the development of the English‐Chinese translation teaching system in colleges and universities.

Retracted] Innovation and Development of University Education Management Informationization in the Environment of Wireless Communication and Big Data

The development of information technology has spawned a new type of demand and management analysis model of big data. The value of data is vividly reflected in the contemporary era, and all walks of life have devoted great energy to the construction and use of informatization. The object of college education and management is the group of college students who are most closely connected with contemporary trends. Their thoughts are active, their state is changeable, and they are very sensitive to external stimuli. Such an educational situation has greatly increased the difficulty of educational management in colleges and universities. This article takes the big data research as the breakthrough point, focuses on the promotion and innovation of contemporary college education management informatization, and strives to improve the college education management informatization system by solving existing problems. The innovation of this research is to use big data technology as the starting point for improving the current stage of the education informatization work of colleges and universities, through the combination of data analysis and the latter, to realize the comprehensive informatization innovation of education management. The study used questionnaire surveys to investigate and interview some students and related managers in 5 universities in the province and conducted an objective assessment of the construction of educational management informatization in these universities and found that these five universities have common problems in this field. Research experiments have found that among the five representative universities in the province, the service awareness of education administrators is not above the fifth level. This shows that in the big data environment, the quality of education administrators cannot be ignored.

A Combining Method for Wireless Protocol Conformance Testing: A Empirical Case

Ensuring the consistency of protocol implementation and protocol specification is the basic premise of wireless communication. With the application of wireless communication in more and more fields, the wireless communication environment becomes more and more complex, and the fault coverage of wireless protocol conformance testing is also facing more and more challenges. To solve this problem, this paper uses Finite State Machine (FSM) as a formal description tool for wireless protocols and presents a combining test method based on two test methods with complementary characteristics in the test technologies based on structural coverage and state identification. Then, the paper evaluates the effectiveness of the method based on 14 empirical cases. The experimental results show that the fault coverage of each empirical case can be effectively improved to 100% when the average test cost is only increased by 17.99%.

A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET

SummaryVehicular ad hoc network (VANET) is a part of the intelligent transportation system (ITS) that provides safety and nonsafety applications. The high mobility of vehicles and the wireless communication environment in VANET makes it vulnerable to various attacks. One among them is the Sybil attack, where a Sybil attacker creates multiple fake identities called Sybil nodes that disrupt the functionality of VANET. Most of the existing solutions in the literature discuss identifying the Sybil nodes (virtual); very few works exist to determine the Sybil attacker (source node that generates Sybil nodes). In this paper, we propose a computation less heuristic approach that focuses on detecting the Sybil attacker and its Sybil nodes using signal strength measurements and Euclidean distance as the detection parameters. The central VANET server, Road Side Units (RSUs), and vehicles collaborate in the detection process, which improves the accuracy of our approach. The core of the approach is a reward‐based system, where the vehicle rewards are determined by collecting RSUs' feedback about the vehicle behavior. From simulation experiments, it is evident that our proposed approach achieves a maximum detection rate of 99.89% and a false positive rate of 0.012% than the existing techniques.

Block Data Record-Based Dynamic Encryption Key Generation Method for Security between Devices in Low Power Wireless Communication Environment of IoT

The Internet of Things uses low-power wireless communication for wireless connectivity and efficient energy. Low-power wireless communication is applied to IoT for wireless connection and efficient energy consumption in various areas such as wearable devices, smart homes, and power plants in order to send and receive data and control the environment. Security is becoming more important because the Internet of Things controls real physical systems. For the security of the Internet of Things, the encryption key is important to identify and authenticate devices that are trusted. The static encryption key method used for devices is likely to be calculated in reverse through the value of the key and is vulnerable to exploitation attacks. This requires the application of dynamic encryption keys that generate keys periodically. However, in the case of low-power wireless communication, the asynchronous communication method and the packet loss make it difficult to apply existing dynamic encryption key technologies. In this paper, we proposed dynamic encryption key method that applies the mechanism of the block chain to solve these problems. Based on the history of sensor data between devices, encryption keys are dynamically generated. The proposed method is to generate the same encryption key between devices with only one step of asynchronous communication considering packet loss. The proposed method is also validated in terms of availability and security in the Internet of Things low-power wireless communication.

Ray Tracing Acceleration Using Total Variation Norm Minimization for Radio Map Simulation

In this letter, a ray tracing (RT) acceleration method based on the total variation norm minimization (TVNM) scheme is presented. RT is a general tool used to analyze wireless communication environments. However, the simulation is time consuming because of the large number of ray calculations. This letter focuses on radio map interpolation as an acceleration approach. For radio map interpolation, we adopt TVNM, which is a representative edge-preserving interpolation method in the field of image processing. We regard the non-line-of-sight and line-of-sight region boundary as the edge of the radio map and use TVNM to achieve accurate interpolation. Furthermore, we consider known position selection to enhance the interpolation accuracy of TVNM. A computational simulation using commercial RT software revealed that the interpolation accuracy of the proposed method was better than those of other radio map interpolation methods and that RT simulation can be accelerated with an acceptable interpolation error.

Cooperative Beam Routing for Multi-IRS Aided Communication

Intelligent reflecting surface (IRS) has been deemed as a transformative technology to achieve smart and reconfigurable environment for wireless communication. This letter studies a new IRS-aided communication system, where multiple IRSs assist in the communication between a multi-antenna base station (BS) and a remote single-antenna user by multi-hop signal reflection. Specifically, by exploiting the line-of-sight (LoS) link between nearby IRSs, a multi-hop cascaded LoS link between the BS and user is established where a set of IRSs are selected to successively reflect the BS's signal, so that the received signal power at the user is maximized. To tackle this new problem, we first present the closed-form solutions for the optimal active and cooperative passive beamforming at the BS and selected IRSs, respectively, for a given beam route. Then, we derive the end-to-end channel power, which unveils a fundamental trade-off in the optimal beam routing design between maximizing the multiplicative passive beamforming gain and minimizing the multi-reflection path loss. To reconcile this trade-off, we recast the IRS selection and beam routing problem as an equivalent shortest simple-path problem in graph theory and solve it optimally. Numerical results show significant performance gains of the proposed algorithm over benchmark schemes and also draw useful insights into the optimal beam routing design.

Secrecy Analysis of Cognitive Radio Networks over Generalized Fading Channels

At present, the fifth generation (5G) communication networks are in the time of large-scale deployment principally because its characteristics consists of large bandwidth, fast response, and high stability. As a partner of 5G, the Internet of Things (IoT) involves billions of devices around the world, which can make the wireless communication environment more intelligent and convenient. However, the problem that cannot be ignored is the physical layer security of 5G-IoT networks. Based on this, we perform a security analysis of cognitive radio networks (CRN) for IoT, where the CRN is the single-input multiple-output (SIMO) model experiencing κ-μ shadowed fading with multiple eavesdroppers. To analyze the confidentiality of the system under consideration, we analyze the security performance for the considered IoT systems with the help of the derived secure outage probability (SOP) and probability of strictly positive secrecy capacity (SPSC). As a verification of the theoretical formula, Monte Carlo simulation is also provided. The results of great interest are the factors that can produce better security performance in high SNRs region which consist of smaller M, smaller k, and larger N, and larger μ, smaller IP, and smaller Rth.

Network resource optimization with reinforcement learning for low power wide area networks

As the 4th industrial revolution using information becomes an issue, wireless communication technologies such as the Internet of Things have been spotlighted. Therefore, much research is needed to satisfy the technological demands for the future society. A LPWA (low power wide area) in the wireless communication environment enables low-power, long-distance communication to meet various application requirements that conventional wireless communications have been difficult to meet. We propose a method to consume the minimum transmission power relative to the maximum data rate with the target of LoRaWAN among LPWA networks. Reinforcement learning is adopted to find the appropriate parameter values for the minimum transmission power. With deep reinforcement learning, we address the LoRaWAN problem with the goal of optimizing the distribution of network resources such as spreading factor, transmission power, and channel. By creating a number of deep reinforcement learning agents that match the terminal nodes in the network server, the optimal transmission parameters are provided to the terminal nodes. The simulation results show that the proposed method is about 15% better than the existing ADR (adaptive data rate) MAX of LoRaWAN in terms of throughput relative to energy transmission.

Overcoming the Communication Challenges in Wireless Sensor and Actuat or Networks Isolated using DTN T echnologies

Wireless Sensor and Actuator Networks (WSAN) have represented a significant advance in wireless communication environments and their convergence with the phenomenon called the Internet of Things (IoT). One of the challenges studied in the WSAN field is to propose communication mechanisms to interconnect wireless sensor networks in isolated areas. Various studies have revealed the difficulty of achieving connectivity in this type of network. In this sense, we address the challenge of interconnecting isolated WSANs, which do not have end-to-end connection, with the Internet network infrastructure. For this, we consider the following characteristics of these environments, disruptive communications, long delays; devices with limited resources, very short transfer times and in contexts of mobility. We propose an integrated architecture that allows us to offer a service management framework based on the capabilities provided by WSAN, through an infrastructure based on cloud technologies. The functionalities that characterize service architectures in telecommunication networks and the integration of WSAN with cloud-based architectures are analyzed. Architectural capabilities such as Machine-to-Machine (M2M) and Machine Type Communication (MTC) are considered. The proposed architecture allows deliver applications and services can be reachable and shared with any host connected to Internet. WSAN data, hosted at remote sites or with limited communications, can be processed, stored and analyzed in the cloud, or locally by components of the architecture. The communication with the sensor network and actuators, is iterant, because of architecture provides support for long-delayed and disruptive tolerant services.

Energy Consumption Analysis of Beamforming and Cooperative Schemes for Aircraft Wireless Sensor Networks

In this paper, the eight schemes for aircraft wireless sensor networks are investigated, which are single-hop array beamforming schemes (including analog beamforming (ABF), and digital beamforming (DBF)), non-cooperative schemes (including single-hop and multi-hop schemes), cooperative schemes (including amplify and forward (AF), decode and forward (DF)), and incremental cooperative schemes (incremental decode and forward (IDF), and incremental amplify and forward (IAF)). To set up the aircraft wireless communication environment, we design the aircraft channel model by referring to the experimental parameters of the ITU (International Telecommunication Union)-R M.2283, which is composed of path loss, shadowing fading, and multi-path fading channel responses. To evaluate the performance, the conditions energy consumption and throughput analysis are performed. Through simulation results, the incremental cooperative scheme outperformed by 66.8% better at spectral efficiency 2 than the DBF scheme in terms of the energy consumption metric. Whereas, in terms of throughput metric, overall SNR (signal-to-noise ratio) ranged from −20 to 30 dB the beamforming scheme had the best performance in which the beamforming scheme at SNR 0 dB achieved 85.4% better than the multi-hop scheme. Finally, in terms of normalized throughput metric in low SNR range between −20 and 1 dB the ABF scheme had the best performance over the others in which the ABF at SNR 0 dB achieved 75.4% better than the multi-hop scheme. Whereas, in high SNR range between 2 and 30 dB the IDF scheme had the best performance in which the IDF at SNR 10 dB achieved 62.2% better than the multi-hop scheme.

Gesture recognition smart home

Different from the traditional smart home control method, this article uses the PAJ7620U2 chip gesture recognition to add to the smart home system.PAJ7620U2 gesture recognition can recognize 9 different gestures. Based on this performance, a simulated smart home system based on gesture recognition is designed. It contains home intelligent electronic photo frames, audio and video entertainment modules, intelligent security monitoring, ZigBee wireless communication environment detection, and light control. The experimental results show that the system is simple to operate and powerful, and is integrated into the traditional smart home control method without gaps.

Robust resource allocation in two-tier NOMA heterogeneous networks toward 5G

This paper proposes a framework of users association and power allocation in the two-tier heterogeneous networks with nonorthogonal multiple access (NOMA). Taking account of practical wireless communication environment, the channel uncertainties are considered and described in the form of probability constraint. In order to maximize the total energy efficiency of the system and reduce the intra-cell and inter-cell interference, the joint optimization problem is formulated with the uncertain channel gain. The probability constraint is transformed to the deterministic one based on the integral transformation. With the aid of relaxation variable and successive convex approximation method, the original integer non-convex optimization problem is divided into two solvable convex subproblems. The user association algorithm and power control algorithm are presented to determine the optimal resource allocations. The simulation results show that the proposed algorithm is effective and robust to the dynamic communication environment.

A Scalable Multi-Data Sources Based Recursive Approximation Approach for Fast Error Recovery in Big Sensing Data on Cloud

Big sensing data is commonly encountered from various surveillance or sensing systems. Sampling and transferring errors are commonly encountered during each stage of sensing data processing. How to recover from these errors with accuracy and efficiency is quite challenging because of high sensing data volume and unrepeatable wireless communication environment. While Cloud provides a promising platform for processing big sensing data, however scalable and accurate error recovery solutions are still need. In this paper, we propose a novel approach to achieve fast error recovery in a scalable manner on cloud. This approach is based on the prediction of a recovery replacement data by making multiple data sources based approximation. The approximation process will use coverage information carried by data units to limit the algorithm in a small cluster of sensing data instead of a whole data spectrum. Specifically, in each sensing data cluster, a Euclidean distance based approximation is proposed to calculate a time series prediction. With the calculated time series, a detected error can be recovered with a predicted data value. Through the experiment with real world meteorological data sets on cloud, we demonstrate that the proposed error recovery approach can achieve high accuracy in data approximation to replace the original data error. At the same time, with MapReduce based implementation for scalability, the experimental results also show significant efficiency on time saving.