Wireless Information Technology Research Articles

Security Performance Analysis of Full-Duplex UAV Assisted Relay System Based on SWIPT Technology

In this paper, a new methodology is developed for modeling and analyzing a full-duplex UAV-assisted relay system to facilitate solving the problems of UAV energy constraints and the vulnerability of UAVs to eavesdropping in the air. Combining simultaneous wireless information and power transfer (SWIPT) technology, we model the downlink UAV eavesdropping channel and propose a secure transmission protocol for a full-duplex UAV-assisted relay system. Using this transmission protocol, we analyze and derive the connectivity and security of the entire communication link, including connection probability and lower bounds on secrecy outage probability. A key intermediate step in our analysis is to derive the signal-to-digital noise ratio of the destination and eavesdropping nodes of the full-duplex UAV relay link. The analyses show that the power allocation factor λ is a trade-off between system connectivity and security, while greater eavesdropping interference needs to be sacrificed for an equal magnitude of security performance improvement under high security demand conditions.

Multi-hop clustering routing protocol design based on simultaneous wireless information and power transfer technology and imperfect spectrum sensing for EH-CRSNs

Existing clustering routing protocols for multi-hop energy harvesting-cognitive radio sensor networks (EH-CRSNs) generally assume perfect spectrum sensing, which is not aligned with the practical spectrum sensing capabilities of nodes in real networks. Additionally, the severe imbalance in residual energy among cluster heads (CHs) negatively affects the successful data delivery. To resolve these problems, this paper introduces a simultaneous wireless information and power transfer (SWIPT)- and imperfect spectrum sensing-based multi-hop clustering routing protocol (ES-ISSMCRP). ES-ISSMCRP makes full use of downlink EH and intra-cluster SWIPT technologies to replenish and equalize the remaining energy among nodes, further extending network lifespan while maintaining network surveillance capabilities. Specifically, to reduce the adverse impact of imperfect spectrum sensing on network performance and improve energy utilization, this paper proposes an EH-based energy level function and associated selection criteria for CHs and relays, facilitating distributed cluster formation and multi-hop routing selection between clusters. To equalize the residual energy among nodes within a cluster, ES-ISSMCRP protocol enables cluster members (CMs) to decide whether employ SWIPT technology with a power splitting (PS) receiver architecture to transmit energy to their CH while sending data. The actual energy value transmitted by CMs using SWIPT technology is deduced by calculating the PS ratio and the expected energy expenditure of nodes for data transmission. Simulation results show that ES-ISSMCRP protocol offers significant improvements over other comparative protocols in terms of extending network lifespan and enhancing network surveillance capabilities.

A Simultaneous Wireless Information and Power Transfer-Based Multi-Hop Uneven Clustering Routing Protocol for EH-Cognitive Radio Sensor Networks

Clustering protocols and simultaneous wireless information and power transfer (SWIPT) technology can solve the issue of imbalanced energy consumption among nodes in energy harvesting-cognitive radio sensor networks (EH-CRSNs). However, dynamic energy changes caused by EH/SWIPT and dynamic spectrum availability prevent existing clustering routing protocols from fully leveraging the advantages of EH and SWIPT. Therefore, a multi-hop uneven clustering routing protocol is proposed for EH-CRSNs utilizing SWIPT technology in this paper. Specifically, an EH-based energy state function is proposed to accurately track the dynamic energy variations in nodes. Utilizing this function, dynamic spectrum availability, neighbor count, and other information are integrated to design the criteria for selecting high-quality cluster heads (CHs) and relays, thereby facilitating effective data transfer to the sink. Intra-cluster and inter-cluster SWIPT mechanisms are incorporated to allow for the immediate energy replenishment for CHs or relays with insufficient energy while transmitting data, thereby preventing data transmission failures due to energy depletion. An energy status control mechanism is introduced to avoid the energy waste caused by excessive activation of the SWIPT mechanism. Simulation results indicate that the proposed protocol markedly improves the balance of energy consumption among nodes and enhances network surveillance capabilities when compared to existing clustering routing protocols.

Multi-objective optimization for energy efficient cooperative communication in energy-constrained overlay Cognitive Radio Networks

With the rapid proliferation of wireless devices, energy efficiency and addressing spectrum scarcity have become critical global concerns. To address these challenges, this paper explores radio-frequency energy harvesting in Cognitive Radio Networks (CRNs) as a solution which can significantly extend the battery life of mobile devices. In this setup, energy-constrained secondary users (SUs) use Simultaneous Wireless Information and Power Transfer (SWIPT) technology to harvest energy from primary signals and aid primary transmission. We propose a joint time-switching and power-splitting technique to maximize energy harvesting, achieving a 97.7% accurate sub-optimal solution compared to the optimal (benchmark) result. Furthermore, we investigate optimal power allocation during cooperative communication and secondary transmission, resulting in a near-optimal solution with 98.5% accuracy. We also introduce a cooperative communication framework using the Hedonic game concept, enabling SUs to establish preferred partnerships with suitable primary users (PUs). Numerical results indicate that this cooperative framework enhances the secondary network’s overall utility, average SU satisfaction, and SU participation when compared to the non-cooperative approach.

Unlocking Synergy: Solar Cell Integration with Radio Waves for AI, IT, and Business Advancements

Combining radio waves and solar cells is a ground-breaking technological convergence that has significant ramifications for wireless communication, energy production, and a wide range of other uses. This study investigates the underlying concepts, applications, prospects, and challenges of solar cell radio wave integration, covering a broad range of topics. We start with a summary of solar cells and their various uses before delving into the photovoltaic effect, solar cell varieties, and how they power buildings for homes and businesses, solar farms, off-grid systems, and even space exploration. Since their invention, solar cells have advanced significantly, and they are now essential to the world's transition to renewable energy sources. Modern technology relies heavily on radio waves, the unsung heroes of our globalized society. We reveal the role that radio waves play in wireless communication, covering everything from radar systems, satellite communication, and the Internet of Things (IoT) to broadcasting and wireless communication networks. Combining these two technologies results in better energy harvesting, sustainability, wireless device power, energy independence, cost savings, and dependability. Solar cells use radiation from the environment and sunshine. Nevertheless, there are drawbacks to this integration as well, including compatibility, efficiency, cost concerns, and regulatory compliance. The paper then looks at actual case studies that show how solar cell radio wave integration can be implemented successfully. These examples show the many and revolutionary uses of this technology, from off-grid communication and smart building energy efficiency to IoT environmental monitoring in remote locations and solar-powered wearables. We investigate future directions for solar cell radio wave integration advances. These include improved energy harvesting, incorporation into commonplace items, wearable medical and health technology, smart cities and infrastructure, satellite technology and space exploration, environmental monitoring and conservation, emergency response and disaster recovery, and microgrids for energy resilience. Finally, this research shows how solar cell radio wave integration can change the world by revealing its intricate workings. The convergence of these technologies is transforming wireless communication, artificial intelligence (AI), information technology (IT), and corporate operations in addition to altering how we produce and utilize energy. Sustainable, effective, and networked systems have the potential to build a more resilient and sustainable world in the future.

Residual energy maximization for NOMA-enabled UAV-assisted data collection network: trajectory optimization and resource allocation

In this paper, we concentrate on a non-orthogonal multiple access (NOMA)-enabled UAV data collection network for Internet of Things devices (IoTDs), where a unmanned aerial vehicle (UAV) is deployed as an aerial base station. During its flight period, the UAV can collect data from IoTDs and take advantage of the simultaneous wireless information and power transfer technology to charge the batteries of IoTDs. With the aid of NOMA, spectrum efficiency has been improved. We aim to prolong the lifetime of the IoT network, via jointly optimizing the UAV trajectory, the time allocation for information communication and wireless power transfer, the IoTDs’ transmit power, as well as the IoTDs’ group scheduling for NOMA. Then, we use the block coordinate decent and successive convex approximation techniques to tackle the non-convexity of the formulated problem. Numerical results show that the proposed solution increases the residual energy of the IoTDs, thus prolonging the lifetime of the network.

Resource Allocation of UAV-Assisted IoT Node Secure Communication System

To balance the information security and energy harvest for massive internet-of-things (IoT) devices, an unmanned aerial vehicle (UAV)–assisted secure communication model is proposed in this paper. We extend the secure transmission model with physical layer security (PLS) to simultaneous wireless information and power transfer (SWIPT) technology and optimize the UAV trajectory, transmission power, and power splitting ratio (PSR). The nonconvex object function is decomposed into three subproblems. Then a robust iterative suboptimal algorithm based on the block coordinate descent (BCD) method is proposed to solve the subproblems. Numerical simulation results are provided to show the effectiveness of the proposed method. These results clearly illustrate that our resource allocation schemes surpass baseline schemes in terms of both transmit power and ratio of harvesting energy, while maintaining an approximately instantaneous secrecy rate.

Resource Allocation for a Secure SWIPT Network Based on a Quantitative Energy Harvesting Mechanism.

Simultaneous wireless information and power transfer (SWIPT) technology can effectively extend the lifecycle of energy-constrained networks. In order to improve the energy harvesting (EH) efficiency and network performance in secure SWIPT networks, this paper studies the resource allocation problem based on the quantitative EH mechanism in the secure SWIPT network. Based on a quantitative EH mechanism and nonlinear EH model, a quantified power-splitting (QPS) receiver architecture is designed. This architecture is applied in the multiuser multi-input single-output secure SWIPT network. With the goal of maximizing the network throughput, the optimization problem model is established under the conditions of meeting the legal user's signal-to-interference-plus-noise ratio (SINR), EH requirements, the total transmit power of the base station, and the security SINR threshold constraints. Due to the coupling of variables, the problem is a nonconvex optimization problem. To deal with the nonconvex optimization problem, a hierarchical optimization method is adopted. Firstly, an optimization algorithm based on the optimal received power of EH circuit is proposed, and a power mapping table is constructed through the optimization algorithm, from which the optimal power ratio to meet the user's EH requirements is obtained; then, the nonconvex problem is transformed into a convex problem by using variable substitution, semidefinite relaxation, dichotomous optimization, etc. The simulation results show that compared with the power splitting receiver architecture, the input power threshold range of the QPS receiver architecture is larger, which can avoid the EH circuit falling into the saturated working area and maintain high network throughput.

Joint Resource Allocation in a Two-Way Relaying Simultaneous Wireless Information and Power Transfer System

Simultaneous wireless information and power transfer (SWIPT) technology provides an efficient solution to energy-limited communication terminals in a wireless network. However, in the current application scenario of SWIPT technology, relays use all the collected energy forwarding to assist communication between source nodes, while ignoring the fact that relays can accumulate and store energy. This is of great practical significance in collaborative communication. By using a transmission scheme of a time-division broadcast for the direct transmission link, improvement of the system diversity gain through combining the technology at the receiver can be realized. Based on the above, we propose a two-way relay energy accumulation communication system, which is extended from a single relay system to a multi-relay system. The instantaneous transmission rate of the system link and the system equivalent profit are optimized by jointly optimizing the relay selection, time slot allocation factor, power splitting factor and relay transmit power. Compared with the comparison algorithm, the proposed algorithm shows a significant improvement in the performance of the system.

Proportional fairness secrecy beamforming for massive MIMO-SWIPT systems with low-resolution ADCs

Simultaneous wireless information and power transfer (SWIPT) technology is one of the solutions to the energy shortage problem in Massive multiple-input and multiple-output (MIMO) systems, while the low-resolution analog-to-digital convertor (ADC) is a potential way to significantly reduce the power consumption of radio frequency circuits in Massive MIMO enabled SWIPT systems. In this paper, we focus on the secrecy transmission maximization problem for Massive MIMO-SWIPT systems over Nakagami-m fading channels, where a low-resolution ADC quantization model and a non-linear energy harvester are exploited. By considering proportional fairness, a joint beamforming design and power allocation problem are proposed to achieve the sum logarithmic secrecy rates. To tackle the non-convex maximization problem, the suboptimal solutions of the beamforming design and power allocation are respectively obtained based on a successive convex approximation and a semidefinite relaxation. Numerical results demonstrate the effectiveness of the proposed joint optimization scheme.

Joint Trajectory Planning, Time and Power Allocation to Maximize Throughput in UAV Network

Due to the advantages of strong mobility, flexible deployment, and low cost, unmanned aerial vehicles (UAVs) are widely used in various industries. As a flying relay, UAVs can establish line-of-sight (LOS) links for different scenarios, effectively improving communication quality. In this paper, considering the limited energy budget of UAVs and the existence of multiple jammers, we introduce a simultaneous wireless information and power transfer (SWIPT) technology and study the problems of joint-trajectory planning, time, and power allocation to increase communication performance. Specifically, the network includes multiple UAVs, source nodes (SNs), destination nodes (DNs), and jammers. We assume that the UAVs need to communicate with DNs, the SNs use the SWIPT technology to transmit wireless energy and information to UAVs, and the jammers can interfere with the channel from UAVs to DNs. In this network, our target was to maximize the throughput of DNs by optimizing the UAV’s trajectory, time, and power allocation under the constraints of jammers and the actual motion of UAVs (including UAV energy budget, maximum speed, and anti-collision constraints). Since the formulated problem was non-convex and difficult to solve directly, we first decomposed the original problem into three subproblems. We then solved the subproblems by applying a successive convex optimization technology and a slack variables method. Finally, an efficient joint optimization algorithm was proposed to obtain a sub-optimal solution by using a block coordinate descent method. Simulation results indicated that the proposed algorithm has better performance than the four baseline schemes.

Transmit Power Adaptation for D2D Communications Underlaying SWIPT-Based IoT Cellular Networks

Device-to-device (D2D) communications and simultaneous wireless information and power transfer (SWIPT) technologies are key to Internet of Things (IoT) to achieve massive connectivity and to prolong battery lifetime, respectively. In this article, we propose novel schemes for transmit power adaptation to maximize the average data rate and to minimize the outage probability of D2D communications over fast and slow-fading channels, respectively, where the D2D network coexists with a SWIPT-based IoT cellular network operating with the time-switching protocol. Also, different from the existing works, circuit power consumption for information decoding is taken into account in this article. To solve the formulated nonconvex power adaptation problems, we first derive tractable lower bound and upper bound on the average data rate and outage probability of cellular user (CU), respectively. Then, based on the conservative approximation, power adaptation solutions are determined. Intriguingly, we show that in the proposed schemes, the performance tradeoff between information decoding and energy harvesting at the CU is not degraded despite the reception of the D2D signals (i.e., interfering signals). Furthermore, deriving and analyzing closed-form bounds on the D2D performance, we obtain useful insights into the D2D performance improvement by the proposed power adaptation schemes. Numerical results demonstrate that the proposed schemes outperform the baseline scheme, and verify the obtained insights.

Distance and Efficiency Enhancement With Aspherical Retroreflectors for Resonant Beam SWIPT

The resonant beam system (RBS) with double spherical retroreflectors presents a potential mobile simultaneous wireless information and power transfer (SWIPT) technology without any tracking control. However, the movement distance and performance are limited due to the effect of spherical aberration. To improve mobility performance in RBS, including movement distance and output power, we adopt an aspherical lens as the focusing mirror in a retroreflector. By shifting the beam phase distribution, the aspherical lens focuses all passing beams, particularly edge beams, on the focal mirror, enhancing energy concentration in the resonant cavity. The beam field propagation through cat’s-eye retroreflectors, gain medium, and air is studied for analyzing the transfer efficiency and output power, and we demonstrate that the axial movement distance in the aspherical resonator is about 7 m, which is more than twice as far away as the spherical resonator. Within a field of view of 3° at a distance of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1~\rm {m}$ </tex-math></inline-formula> , the output power of the aspherical resonator is greater than that of the spherical resonator with the same movement angle, up to two times. The maximum output electric power and spectral efficiency are approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4~\rm {W}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$12~\rm {bps/Hz}$ </tex-math></inline-formula> , respectively.

Research on Multi-Terminal’s AC Offloading Scheme and Multi-Server’s AC Selection Scheme in IoT

Mobile Edge Computing (MEC) technology and Simultaneous Wireless Information and Power Transfer (SWIPT) technology are important ones to improve the computing rate and the sustainability of devices in the Internet of things (IoT). However, the system models of most relevant papers only considered multi-terminal, excluding multi-server. Therefore, this paper aims at the scenario of IoT with multi-terminal, multi-server and multi-relay, in which can optimize the computing rate and computing cost by using deep reinforcement learning (DRL) algorithm. Firstly, the formulas of computing rate and computing cost in proposed scenario are derived. Secondly, by introducing the modified Actor-Critic (AC) algorithm and convex optimization algorithm, we get the offloading scheme and time allocation that maximize the computing rate. Finally, the selection scheme of minimizing the computing cost is obtained by AC algorithm. The simulation results verify the theoretical analysis. The algorithm proposed in this paper not only achieves a near-optimal computing rate and computing cost while significantly reducing the program execution delay, but also makes full use of the energy collected by the SWIPT technology to improve energy utilization.

Wireless powered cognitive radio networks with multiple antenna sources and hardware impairments

In this paper, a radio-frequency (RF) energy harvesting enabled cognitive radio network (CRN) is considered in the presence of transceiver hardware impairments (HIs). Herein, one of the secondary nodes (SNs) exploits simultaneous wireless information and power transfer (SWIPT) technology to harvest energy from the primary signal and provides relay assistance for the primary transmission. We consider multiple antennas at the primary nodes (PNs) to ensure better link reliability and spectrum sharing to mitigate the spectrum scarcity. In the first phase, relaying SN uses non-linear energy harvester circuit to harvest energy from the RF signals received from PN using the power splitting approach. In the second phase, the same SN adds its own signal intended for the other SN along with the primary signal and broadcasts the combined signal. Assuming the network to operate in a Nakagami-m fading environment, the performance of the considered CRN is evaluated in terms of outage probability and system throughput. Also, we formulate two optimization problems to minimize the OP and maximize the system throughput. The Karush–Kuhn–Tucker conditions are used to obtain the closed-form solution of the constrained convex optimization. Numerical results are provided to examine the performance impact concerning different system and channel parameters.

The Construction of English Smart Classroom Teaching Mode Based on Deep Learning.

Deep learning has an increasingly far-reaching impact on classroom teaching and is an important trend driving the application of educational technology in schools. In the traditional lecture-style teaching process, students are mostly in a passive listening and memorizing state. Simple memorization and repeated training have a certain hindering effect on promoting the transfer and application of the learner's knowledge, and it is not suitable to exert the learner's subjectivity. This research uses the current rapidly developing wireless communication technology to transmit data to the English teaching management platform, so as to realize the information exchange between the English classroom monitoring terminal and the English teaching management platform. The monitoring terminal of the system is mainly responsible for data collection of information, such as student campus card information, the location of the monitoring terminal, and terminal equipment parameters, and uses wireless communication information technology to upload it to the English teaching management platform according to the communication protocol agreed between the terminal and the platform, and the English teaching management platform can issue instructions to the monitoring terminal, so as to realize the control and management functions of the monitoring terminal. The design of the English teaching management platform of this system is a Web system designed based on B/S architecture. The interface of the system is diverse, and English teachers can easily view the monitoring data on the platform through this system. The main function of the English teaching management platform is to receive the data collected from the monitoring terminal, parse the information, and display the processing results to the English teacher in the form of a page. In order to facilitate the storage of data, MySQL database is used for the background data storage of the English teaching management platform. Through the design of the hardware terminal module and the development of the English teaching management platform, a deep learning-based English smart classroom management prototype system is realized.

Secure Beamforming for IRS-Assisted Nonlinear SWIPT Systems With Full-Duplex User

Physical layer security of wireless communication network with intelligent reflecting surface (IRS) is investigated in this letter. At the access point (AP) transmission power and user nonlinear energy harvest constraints, maximum secrecy rate of full-duplex (FD) user which employs simultaneous wireless information and power transfer (SWIPT) technology is achieved by jointly optimizing transmit beamformer of AP, IRS phase shift, and artificial noise power of FD user. Due to its undesirable properties, such as coupling of multiple optimization variables and non-convex objective function, original optimization problem is hard to be handled. We solved this problem by an alternating optimization algorithm consisting of semi-definite relaxation, Charnes-Cooper transform and continuous phase shifting discretization techniques to obtain a feasible suboptimal solution. Simulation results demonstrate that although may only guarantee to convergence a local optimal, proposed algorithm still achieves the best security rate comparing to the benchmark algorithms with the computational efficiency sacrificing.

Performance Analysis of Cognitive SWIPT Ergodic Capacity Based on Different Selection Policies

The advent of 5G era and the increase of terminal’s numbers have led to increasing demand for spectrum resources and energy simultaneously. Therefore, this paper studies how to combine the cognitive radio (CR) and the Simultaneous Wireless Information and Power Transfer (SWIPT) technology effectively in a multiuser scenario, in which the spectrum utilization and energy efficiency are both improved. Firstly, the system model is designed of above cognitive SWIPT system, in which the cognitive users (CU) can choose spectrum access policy based on the amount of data transmission of licensed user. And then, according to cognitive users’ channel conditions and forwarding power, a concept of trust value and different relay selection policies is proposed. Subsequently, the according system ergodic capacity is analyzed. Finally, simulation results of system performance are provided to validate the analytical results. It shows that cognitive SWIPT technology can improve the system ergodic capacity and the spectrum access opportunities of cognitive users effectively, thereby improving the efficiency of energy and spectrum utilization.

Information Harvesting for Far-Field Wireless Power Transfer

In today's smart world, the Internet of Things (IoT) offers a very large scale of technologies and use cases. An IoT system comprises a huge amount of low-power IoT network elements, sensors, and smart devices connected to each other. For these devices, it is important to have a sufficient level of energy resource for communication and to receive software/firmware updates periodically. In this aspect, wireless power transfer is a popular paradigm to tackle energy limitations. Therein, the battery of IoT devices can be remotely replenished by means of radio-frequency-radiated signaling, referred to as far-field wireless power transfer. Furthermore, harvesting energy from ambient communication signals available in the environment introduces simultaneous wireless information and power transfer technology. These systems face the trade-off between information capacity and energy harvesting efficiency. Accordingly, various signaling design frameworks have been proposed to comply with different system preferences between power and information. In this work, aside from existing trends, we propose a novel concept, information harvesting (IH), which introduces a novel protocol that lies in transmitting information on top of the existing wireless power transfer mechanism. Considering the diversity of IoT networks and the availability of wireless power transfer infrastructure, the proposed IH principle may turn out to be a pivotal methodology that combines physical layer security with wireless power transfer, particularly for cases where a large number of IoT devices require software/firmware updates along with periodical battery recharging needs.

Wireless information technology competency and transformational leadership in supply chain management: implications for innovative capability

PurposeThe present study conceptualizes and examines the interplay of transformational leadership, ambidexterity and wireless information technology (IT) competency for enhancing innovative capability.Design/methodology/approachDrawing primarily on the knowledge-based and dynamic capabilities view theory, the present study explored supply chains of a large global apparel company and their effect on innovative capability through a mixed methods approach.FindingsThe results show that transformational leaders strongly influence the development of ambidexterity and enhance radical innovative capability through wireless IT competency.Research limitations/implicationsThe results of this study suggest that supply chain integration through transformational leadership and wireless IT competency can promote simultaneous exploration and exploitation to enhance innovation.Practical implicationsThe growth of cloud and/or virtual supply chains facilitated by digital wireless communications and Internet technology is advancing logistics and supply chain innovations. With increasing global competition, digitalized supply chains and ever-growing environmental uncertainty, leadership traits, especially transformational leadership and ambidextrous leaders, can be major contributing factors for successful development of wireless IT competency to support innovative capability.Originality/valueWireless IT competency facilitates knowledge integration particularly for combining prior internal knowledge of exploitative innovation with new external knowledge to develop explorative innovation.