Power Wireless Communication Research Articles

Modified hybrid fruit fly-based salp swarm optimization strategy for energy efficient optimization in MIMO Wireless Powered Communication Networks

A potential way to handle the future requirements of wireless data traffic is the Massive Multiple Input Multiple Output (MIMO) antenna systems. The most effective method to satisfy the demand for wireless data traffic is to enhance the Spectral Efficiency of the existing spectrum since the wireless spectrum is a limited resource. In the MIMO network, cell-free, energy-efficient, and user-centric are considered as most important parameters to achieve effective communication. Therefore, a new energy efficiency optimization scheme is developed in a massive MIMO system to improve the system’s capacity and spectral efficiency. The multi-channel optimization problem is effectively rectified with the help of this newly designed energy efficiency optimization scheme. Here, the “Singular Value Decomposition (SVD)” method is utilized for the implementation of a sub-channel grouping scheme, where the sub-channels are arranged in descending order based on the results attained from SVD. After arranging the sub-channels, the sub-channel grouping is carried out, and then the energy efficiency optimization is provided with the help of Integrated Fruit Fly with Salp Swarm Optimization (IFFSSO). This energy-efficient algorithm improves the system capacity and spectral efficiency. The experimental outcome is revealed through various conventional models to ensure the energy efficiency of the recommended model.

Magnetoelectrics for Implantable Bioelectronics: Progress to Date.

ConspectusThe coupling of magnetic and electric properties manifested in magnetoelectric (ME) materials has unlocked numerous possibilities for advancing technologies like energy harvesting, memory devices, and medical technologies. Due to this unique coupling, the magnetic properties of these materials can be tuned by an electric field; conversely, their electric polarization can be manipulated through a magnetic field.Over the past seven years, our lab work has focused on leveraging these materials to engineer implantable bioelectronics for various neuromodulation applications. One of the main challenges for bioelectronics is to design miniaturized solutions that can be delivered with minimally invasive procedures and yet can receive sufficient power to directly stimulate tissue or power electronics to perform functions like communication and sensing.Magnetoelectric coupling in ME materials is strongest when the driving field matches a mechanical resonant mode. However, miniaturized ME transducers typically have resonance frequencies >100 kHz, which is too high for direct neuromodulation as neurons only respond to low frequencies (typically <1 kHz). We discuss two approaches that have been proposed to overcome this frequency mismatch: operating off-resonance and rectification. The off-resonance approach is most common for magnetoelectric nanoparticles (MENPs) that typically have resonance frequencies in the gigahertz range. In vivo experiments on rat models have shown that MENPs could induce changes in neural activity upon excitation with <200 Hz magnetic fields. However, the neural response has latencies of several seconds due to the weak coupling in the off-resonance regime.To stimulate neural responses with millisecond precision, we developed methods to rectify the ME response so that we could drive the materials at their resonant frequency but still produce the slowly varying voltages needed for direct neural stimulation. The first version of the stimulator combined a ME transducer and analog electronics for rectification. To create even smaller solutions, we introduced the first magnetoelectric metamaterial (MNM) that exhibits self-rectification. Both designs have effectively induced neural modulation in rat models with less than 5 ms latency.Based on our experience with in vivo testing of the rectified ME stimulators, we found it challenging to deliver the precisely controlled therapy required for clinical applications, given the ME transducer's sensitivity to the external transmitter alignment. To overcome this challenge, we developed the ME-BIT (MagnetoElectric BioImplanT), a digitally programmable stimulator that receives wireless power and data through the ME link.We further expanded the utility of this technology to neuromodulation applications that require high stimulation thresholds by introducing the DOT (Digitally programmable Overbrain Therapeutic). The DOT has voltage compliance up to 14.5 V. We have demonstrated the efficacy of these designs through various in vivo studies for applications like peripheral nerve stimulation and epidural cortical stimulation.To further improve these systems to be adaptive and enable a network of coordinated devices, we developed a bidirectional communication system to transmit data to and from the implant. To enable even greater miniaturization, we developed a way to use the same ME transducer for wireless power and data communication by developing the first ME backscatter communication protocol.

IRS-assisted UAV wireless powered communication network for sustainable federated learning

Intelligent reflective surface (IRS) and unmanned aerial vehicle (UAV) communication are indispensable potential technologies in the future sixth-generation mobile communication technology (6 G). Utilizing the high beamforming gain of IRS and the high mobility of UAV can achieve ubiquitous network coverage and ensure a high-quality communication environment. Wireless Powered Communication Network (WPCN) is an emerging green communication technology network that converts received radio frequency (RF) signals into electrical energy to power Federated Learning (FL) users. FL users perform local computing and model transmission through the collected energy, ensuring the sustainability of FL. In order to solve the problems of complex communication environment, privacy protection, and energy constraints on terminal devices, we design an FL system based on an IRS-assisted UAV wireless power communication network, which minimizes the UAV transmission energy by jointly optimizing UAV location, IRS phase shift, and resource allocation strategies. We use a low-complexity iterative algorithm to solve this complex non-convex problem. The simulation results show that the performance of the proposed algorithm is obviously better than that of other benchmark schemes, indicating that joint optimization plays an essential role in improving the performance of the system.

Ambient Backscatter-Based User Cooperation for mmWave Wireless-Powered Communication Networks with Lens Antenna Arrays

With the rapid consumer adoption of mobile devices such as tablets and smart phones, tele-traffic has experienced a tremendous growth, making low-power technologies highly desirable for future communication networks. In this paper, we consider an ambient backscatter (AB)-based user cooperation (UC) scheme for mmWave wireless-powered communication networks (WPCNs) with lens antenna arrays. Firstly, we formulate an optimization problem to maximize the minimum rate of two users by jointly designing power and time allocation. Then, we introduce auxiliary variables and transform the original problem into a convex form. Finally, we propose an efficient algorithm to solve the transformed problem. Simulation results demonstrate that the proposed AB-based UC scheme outperforms the competing schemes, thus improving the fairness performance of throughput in WPCNs.

Joint Optimization of Trajectory and Resource Allocation for Multi-UAV-Enabled Wireless-Powered Communication Networks

Joint Optimization of Trajectory and Resource Allocation for Multi-UAV-Enabled Wireless-Powered Communication Networks

Dual-Functional Cross-Meandering Resonator for Power Frequency Electromagnetic Shielding and Wireless Sensing Communication.

The research on MEMS wireless sensing technology adapted to strong power frequency electromagnetic field environments is of great significance to our energy security, economic society, and even national security. Here, we propose a subwavelength cross-meandering resonator (0.49λ0 × 0.49λ0) to simultaneously achieve power frequency electromagnetic field shielding and wireless communication signal transmission. The element size of the resonator is only λ0/11, which is much smaller than that of previous works. In the resonator, a resonance mode with the significant near-field enhancement effect (about 180 times that at f = 1 GHz) is supported. Based on the self-made shielding box experimental setup, the measured shielding effectiveness of the resonator sample can reach more than 33 dB. Moreover, by integrating the cross-meandering resonator with the MEMS sensor, a wireless communication signal can be successfully transmitted. A dual-function cross-meandering resonator integrated with sensors may find potential applications in many military and civilian industries associated with strong power frequency electromagnetic fields.

Energy Consumption Minimization with SNR Constraint for Wireless Powered Communication Networks.

The article addresses the energy consumption minimization problem in wireless powered communication networks (WPCNs) and proposes a time allocation scheme, named DaTA, which is based on the Different Target Simultaneous Wireless Information and Power Transfer (DT-SWIPT) scheme such that the wireless station can share the remaining energy after transmission to the Hybrid Access Point (HAP) to those who have not transmitted to the HAP to minimize the energy consumption of the WPCN. In addition to proposing a new frame structure, the article also considers the Signal-to-Noise (SNR) constraint to guarantee that the HAP can successfully receive data from wireless stations. In the article, the problem of minimization of energy consumption is formulated as a nonlinear programming model. We employ the SQP (Sequential Quadratic Programming) algorithm to figure out the optimal solution. Moreover, a heuristic method is proposed as well to obtain a near-optimal solution in a shorter time. The simulation results showed that the proposed scheme outperforms the related work in terms of energy consumption and energy efficiency.

Resource allocation for relaying cognitive network with energy harvesting

This paper investigates a relay-based cognitive wireless-powered communication network with multiple secondary receivers and a secondary relaying network. In the secondary network, a relay adopts an energy model to harvest energy from radio frequency signals of the primary and secondary sources and subsequently utilizes the harvested energy to cooperate with the source for information transmission to multiple Internet-of-things users over time-division multiple access. The research group formulated a novel optimization problem that jointly optimizes the power and time fraction for energy and information transmission to maximize the sum throughput of the secondary network. The authors first converted the non-convex problem to a more computationally tractable problem and then proposed an iterative algorithm in which closed-form solutions are obtained at each iteration. Thus, simulation results verify and demonstrate the effectiveness of the proposed approach.

Smart Wireless Transducer Dedicated for Use in Aviation Laboratories.

Reliable testing of aviation components depends on the quality and configuration flexibility of measurement systems. In a typical approach to test instrumentation, there are tens or hundreds of sensors on the test head and test facility, which are connected by wires to measurement cards in control cabinets. The preparation of wiring and the setup of measurement systems are laborious tasks requiring diligence. The use of smart wireless transducers allows for a new approach to test preparation by reducing the number of wires. Moreover, additional functionalities like data processing, alarm-level monitoring, compensation, or self-diagnosis could improve the functionality and accuracy of measurement systems. A combination of low power consumption, wireless communication, and wireless power transfer could speed up the test-rig instrumentation process and bring new test possibilities, e.g., long-term testing of moving or rotating components. This paper presents the design of a wireless smart transducer dedicated for use with sensors typical of aviation laboratories such as thermocouples, RTDs (Resistance Temperature Detectors), strain gauges, and voltage output integrated sensors. The following sections present various design requirements, proposed technical solutions, a study of battery and wireless power supply possibilities, assembly, and test results. All presented tests were carried out in the Components Test Laboratory located at the Łukasiewicz Research Network-Institute of Aviation.

Wirelessly Powered and Bi-Directional Data Communication System With Adaptive Conversion Chain for Multisite Biomedical Implants Over Single Inductive Link.

A wirelessly powered and data communication system is presented which is implemented as a full system, designed for multisite implanted biomedical applications. The system is capable of receiving wireless power and data communication for each implant separately, using inductive links with different resonance frequencies. To achieve this, dual-band coils are presented in the system. In addition, the system supports bi-directional half-duplex data communication, utilizing amplitude and load shift keying (ASK and LSK) modulation schemes over a single inductive link. The system employs a digitally assisted active rectifier and an automatic resonance tuning system, to improve the power transfer efficiency (PTE) through various coupling coefficients, while minimizing the reverse current and power dissipation. The power control unit enables closed-loop monitoring to prevent high or low power delivery, and it can detect inefficient or excessive wireless power transmission or prevent temperature elevation by limiting the voltage to a safe level. A new structure of self-sampling separated- Vb ASK demodulator is proposed in the paper which is utilized within the data conversion chain, serving both the external and implanted units. The whole system is fabricated using a standard 180-nm 1.8/3.3 V CMOS process with a core area of 0.82 mm[Formula: see text]. The system is tested with coupled multisite inductive links and offers the maximum overall PTE of 31.2%, from the Tx coil to the implant load.

Long-Term Throughput Maximization in Wireless Powered Communication Networks: A Multitask DRL Approach

Long-Term Throughput Maximization in Wireless Powered Communication Networks: A Multitask DRL Approach

Joint Resource Allocation for Maximizing Energy Efficiency in mmWave-Based Wireless-Powered Communication Networks

Joint Resource Allocation for Maximizing Energy Efficiency in mmWave-Based Wireless-Powered Communication Networks

A Collaborative Allocation Algorithm of Communicating, Caching and Computing Resources in Local Power Wireless Communication Network

A Collaborative Allocation Algorithm of Communicating, Caching and Computing Resources in Local Power Wireless Communication Network

Distributed Energy Cooperation in Multicell Wireless Powered Communication Networks

Distributed Energy Cooperation in Multicell Wireless Powered Communication Networks

Medical Data in Wireless Body Area Networks: Device Authentication Techniques and Threat Mitigation Strategies Based on a Token-Based Communication Approach

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a ‘data train’ and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data.

Enhancing Throughput in IoT Networks: The Impact of Active RIS on Wireless Powered Communication Systems

This paper investigates the potential of active reconfigurable intelligent surfaces (RIS) to enhance wireless-powered communication networks (WPCNs), addressing the evolving connectivity needs of the internet of things (IoT). Active RIS, capable of amplifying and reflecting signals, offers a solution to surpass the limitations of passive RIS, such as double-fading attenuation, aiming to significantly improve network throughput and coverage. Our research focuses on exploiting the amplification capabilities of active RIS to boost the overall network sum throughput, engaging in a comprehensive optimization of critical network parameters, including time allocation, reflection coefficients, and phase shift matrices specific to active RIS. The formulated problem is non-convex and highly complex due to the coupling of optimization variables. We employed a successive convex approximation algorithm to solve the throughput maximization problem by converting the non-convex constraints into approximated convex constraints and solving them iteratively. Through extensive simulations, we demonstrate that our active RIS-assisted network substantially outperforms networks facilitated by passive RIS, marking a significant advancement in WPCN performance. These findings underscore the potential of active RIS technology in realizing the full capabilities of IoT connectivity.

Multiobjective Optimization of Wireless Powered Communication Networks Assisted by Intelligent Reflecting Surface Based on Multiagent Reinforcement Learning

Multiobjective Optimization of Wireless Powered Communication Networks Assisted by Intelligent Reflecting Surface Based on Multiagent Reinforcement Learning

Flexible and wearable battery-free backscatter wireless communication system for colour imaging

Wireless imaging, equipped with ultralow power wireless communications and energy harvesting (EH) capabilities, have emerged as battery-free and sustainable solutions. However, the challenge of implementing wireless colour imaging in wearable applications remains, primarily due to high power demands and the need to balance energy harvesting efficiency with device compactness. To address these issues, we propose a flexible and wearable battery-free backscatter wireless communication system specially designed for colour imaging. The system features a hybrid RF-solar EH array that efficiently harvests energy from both ambient RF and visible light energy, ensuring continuous operation in diverse environments. Moreover, flexible materials allow the working system to conform to the human body, ensuring comfort, user-friendliness, and safety. Furthermore, a compact design utilizing a shared-aperture antenna array for simultaneous wireless information and power transfer (SWIPT), coupled with an optically transparent stacked structure. This design not only optimizes space but also maintains the performance of both communication and EH processes. The proposed flexible and wearable systems for colour imaging would have potentially applications in environmental monitoring, object detection, and law enforcement recording. This approach demonstrates a sustainable and practical solution for the next generation of wearable, power-demanding devices.

Trajectory optimization for maximization of energy efficiency with dynamic cluster and wireless power for UAV‐assisted maritime communication

AbstractNowadays, the digital development of marine ranching requires a communication system with wide coverage, high transmission rate and stable communication links. It is known that fixed‐wing unmanned aerial vehicles (UAVs) have great advantages in long‐range applications. They have the potential to serve as low‐altitude communication platforms for maritime communication. In this study, with a developmental perspective, considering the intense growth of marine terminals in the future, a new clustering algorithm applied to cluster nonorthogonal multiple access (C‐NOMA) is proposed and its advantages are investigated. In addition, considering the limited energy of marine terminals, combining the wireless power communication (WPC) technology for the UAV to charge terminals, the charging and communication time are optimized with the Lagrange multiplier method and the bisection search method. After completing the above optimization content of charging and communication, combined with the optimization results, it is found the trajectory that maximizes the energy efficiency of the UAV with the convex optimization technique. Experimental results show that the proposed clustering algorithm has good throughput performance, better fairness and lower algorithm complexity, and the proposed trajectory optimization scheme has better energy efficiency.

Energy Maximization for Wireless Powered Communication Enabled IoT Devices With NOMA Underlaying Solar Powered UAV Using Federated Reinforcement Learning for 6G Networks

Energy Maximization for Wireless Powered Communication Enabled IoT Devices With NOMA Underlaying Solar Powered UAV Using Federated Reinforcement Learning for 6G Networks