Improve Transmission Efficiency Research Articles

Evolutionary generative adversarial network based end-to-end learning for MIMO molecular communication with drift system

Molecular communication (MC) is a novel paradigm for nano-communication networks. Compared with diffusion-based single-input single-out (SISO) systems, multiple-input multiple-output (MIMO) MC with drift systems can effectively mitigate the negative effects of inter symbol interference (ISI), inter link interference (ILI) and noise, further improving transmission efficiency. The modeling complexity of MIMO MC systems inspires the application of deep learning (DL) techniques to establish end-to-end architectures for signal recovery. However, training of the entire end-to-end system is limited by the unknown channel and small training sample size. In this paper, aiming at signal recovery of the newly developed mathematical MIMO MC with drift system model, a Kullback–Leibler divergence (KLD) evolutionary generative adversarial network (EGAN)-based end-to-end learning method is proposed. The end-to-end architecture can be trained offline with both the sampled and fake signals generated by KLD EGAN, even with a small training sample size, and then used to recover online transmitted signals directly. Besides, two traditional detection algorithms denoted as the maximum a posterior (MAP) detector and fixed threshold (FT) detector, are proposed as well for theoretical comparison. Experiments of the effect of different model parameters on the system performance have been carried out. Results validate the effectiveness and robustness of our proposed method compared to other DL-based methods, including the deep neural networks (DNN)-based, the original GAN-based, and the original EGAN-based, in terms of transmission accuracy.

Parameter sensitivity analysis and efficiency optimization design of wireless charging system

Electric vehicle (EV) wireless charging technology has recently attracted a lot of attention and has a broad potential for commercial application development. A fundamental performance indicator of wireless charging systems is efficient transmission. Magnetic coupling mechanism design and circuit parameters have the greatest effects on the transmission efficiency of the system. In this study, the output power and efficiency of the wireless power transfer (WPT) circuit were theoretically computed based on the LCC-type resonant network. Simulation studies demonstrate that the transmission efficiency and output gain deviate significantly from the expected value when circuit parameters are changed. To improve transmission efficiency, the optimal impedance configuration was created using a semi-controlled rectifier circuit. Based on electromagnetic field theory and equivalent magnetic circuit model, a new contactless transformer structure was optimized and created, and the new contactless transformer had a higher coupling coefficient. The coil offset had a greater impact on the transmission efficiency. The results indicate that within a certain distance, the coupling coil offset had no impact on transmission efficiency, and beyond that distance, the transmission efficiency was almost non-existent. Both the feasibility of the practical verification and the accuracy of the theoretical study were tested using a low-power wireless charging experimental setup. This paper provides design guidelines for wireless charging systems using circuit parameter sensitivity analysis and contactless transformer optimization design.

Joint Optimization of Relay Selection and Transmission Scheduling for UAV-Aided mmWave Vehicular Networks

To deal with the explosive growth of mobile traffic, millimeter-wave (mmWave) communications with abundant bandwidth resources have been applied to vehicular networks. As mmWave signal is sensitive to blockage, we introduce the unmanned aerial vehicle (UAV)-aided two-way relaying system for vehicular connection enhancement and coverage expansion. How to improve transmission efficiency and to reduce latency time in such a dynamic scenario is a challenging problem. In this paper, we formulate the joint optimization problem of relay selection and transmission scheduling, aiming to reduce transmission time while meeting the throughput requirements. To solve this problem, two schemes are proposed. The first one is the random relay selection with concurrent scheduling (RCS), a low-complexity algorithm implemented in two steps. The second one is the joint relay selection with dynamic scheduling (JRDS), which fully avoids relay contentions and exploits potential concurrent ability, to obtain further performance enhancement over RCS. Through extensive simulations under different environments with various flow numbers and vehicle speeds, we demonstrate that both RCS and JRDS schemes outperform the existing schemes significantly in terms of transmission time and network throughput. We also analyze the impact of threshold selection on achievable performance.

Dual Polarization DQPSK ROF System with Duo Binary Precoding and Hybrid Amplification for Effective Hybrid SMF FSO Transmission Medium

This article demonstrates the utilization of a hybrid amplification technique on the transmission part of the proposed hybrid medium transmission system which includes both using Single Mode Fiber (SMF) with 60 km and Free Space Optic (FSO) with a range between 5 km and 25 km. It has included four weather situations with an investigation of the FSO medium-based system performance. The system uses 64 channels based on Dual Polarization-Differential Quadratic Phase Shift Keying (DP-DQPSK) Dense Wavelength Division Multiplexing (DWDM) for the Radio over Fiber (RoF) system using the Duo Binary coding scheme to improve the system efficiency in general and the cross-talk in particular. The investigations will include using the hybrid amplifiers of Erbium Doped Fiber Amplifier (EDFA) and Optical Amplifier (OA) for transmission. The analysis results show that using the hybrid amplification could improve the transmission to reach 25 km for light air case, meanwhile, for light haze, it could reach up to 20 km. Moderate haze could improve transmission efficiency for a distance of 7 km. Finally, for moderate rain situations, the transmission could be further improved to cover a distance of up to 5 km.

A metamaterial‐incorporated wireless power transmission system for efficiency enhancement

SummaryIn this paper, an efficient wireless power transmission (WPT) system that incorporates a new negative permeability metamaterial is presented. The operating principle of the metamaterial with negative permeability is first analyzed. To improve transmission efficiency of the WPT system at the operating frequency of 13.56 MHz, a new metamaterial with three open rings is designed. By respectively placing a single metamaterial slab and double metamaterial slabs at different positions between transmitting coil and receiving coil, the performance of the proposed WPT system is evaluated by simulation work. The corresponding magnetic field distribution is also analyzed. Besides, comparison is made with the conventional WPT system without metamaterial. It is found that transmission efficiency of the proposed WPT system is obviously improved when incorporating the metamaterial since the designed metamaterial effectively focuses magnetic field towards the receiving coil. Comparing with the conventional system, the results also show that the proposed WPT system is more robust to lateral and angular misalignment of the receiving coil. With the designed metamaterial, it is found that the proposed system with double metamaterial slabs performs better than that with a single metamaterial slab.

An Improved DTN Scheme for Large-Scale LEO Satellite Networks

A large-scale low Earth orbit (LEO) satellite network has the characteristics of a complex link environment, a large number of satellites, and the limited resources of a single satellite. Applying traditional routing algorithms has disadvantages such as high overhead, high end-to-end latency, and low message delivery rate. This paper proposes an improved delay tolerant (DTN) scheme for large-scale LEO satellite networks (LIDTN) to improve transmission efficiency and reduce the resource overhead and end-to-end latency of large-scale satellite networks. This scheme improves the network performance in three aspects: next hop selection, congestion control mechanism, and acknowledgment mechanism. For the next hop selection, we propose an equivalent distance and priori knowledge-based forwarding strategy (EPFS), which has the advantages of low overhead, loop avoidance, and fast convergence. For congestion control, we put forward an emergency function-based bundle drop algorithm (EBDA). For acknowledging, we propose the virtual acknowledgment algorithm (VAA) by combining the characteristics of many path hops and high link disruption rates in large-scale constellations. Finally, we simulate and verify the LIDTN scheme on the OneWeb constellation. The results show that the LIDTN scheme is suitable for large-scale constellations, the EPFS algorithm can reduce the network overhead during data transmission, EBDA can reduce the bundle drop rate, and VAA can reduce the end-to-end latency. LIDTN provides a new solution for large-scale constellation communication.

Investigation of Traffic Classification Applied to an Astronomical Data Transmission Network of the XAO Using Deep Learning

A telecommunication network used for the transmission of astronomical observation data, telescope remote control and other astronomical research purposes is a critical infrastructure. The monitoring and analysis of network traffic, which help improve the network performance and the utilization of network resources, are a challenging task. The accurate identification of the astronomical data traffic will effectively improve transmission efficiency. In this paper, a classification method applied to types of traffic containing astronomical data using deep learning is proposed. The advantages of a convolutional neural network model in image classification are exploited to classify types of traffic containing astronomical data. The objective is to identify the mixed traffic in the network and accurately identify types of traffic containing astronomical data. The effectiveness of the model in improving classification accuracy is also discussed. Actual traffic data captured by Tcpdump and Wireshark are tested, and the experimental results indicate that the proposed method can accurately classify types of traffic containing astronomical data.

Synchronized Control Strategy of UPQC to Mitigate the Sag and Swell of Voltage

AbstractThis paper demonstrates efficacy of the control strategy of Unified Power Quality Conditioner (UPQC) for improvement of three‐phase power quality. UPQC contains a couple of active power filters (APF), one is connected in series and another is shunt. Series APF belongs to the Flexible AC Transmission System (FACTS), it is a promising device for the improvement of transmission efficiency. The Voltage Source Converter (VCS) acts as the brain of series APF while the shunt APF is another part of the UPQC. This series‐connected component injects the compensating voltages that are generated by voltage source inverter (VSI). The entire system of UPQC (series and shunt APF) deals with the voltage dip and voltage swell on the consumer end of the network. Among the major advantages of the system is that this conditioner can captivate or insert true power. It can inject the voltage from 0° to 360° as per the phase angle requirement of the base voltage. It is the major reason why it can work in three different modes. This series APF acts as an active power deliverer for sag condition in the aspect of voltage. The Matlab/Simulink software is used to investigate the analysis and results.

Symbol Error Probability Optimization of OFDM Bidirectional AF Relaying Systems

This paper considers that two transceivers exchange orthogonal frequency division multiplexing (OFDM) signals with the aid of multiple bidirectional amplify and forward (AF) relays. Unlike most researchers who care about sum rate maximization issues to improve transmission efficiency, we formulate a symbol error probability (SEP) minimization problem under total power constraint because high data rate may degrade SEP performance. A joint algorithm of power allocation and relay selection is proposed to study their impact on the SEP performance. The closed-form solution of power allocation is not a form of water filling widely used in the sum rate maximum problem. Both analytical and simulation results clearly demonstrate the superiority of our algorithm.

Computation Offloading and User-Clustering Game in Multi-Channel Cellular Networks for Mobile Edge Computing.

Mobile devices may use mobile edge computing to improve energy efficiency and responsiveness by offloading computation tasks to edge servers. However, the transmissions of mobile devices may result in interference that decreases the upload rate and prolongs transmission delay. Clustering has been shown as an effective approach to improve the transmission efficiency for dense devices, but there is no distributed algorithm for the optimization of clustering and computation offloading. In this work, we study the optimization problem of computation offloading to minimize the energy consumption of mobile devices in mobile edge computing by adaptively clustering devices to improve the transmission efficiency. To address the optimization problem in a distributed manner, the decision problem of clustering and computation offloading for mobile devices is formulated as a potential game. We introduce the construction of the potential game and show the existence of Nash equilibrium in the game with a finite enhancement ability. Then, we propose a distributed algorithm of clustering and computation offloading based on game theory. We conducted a simulation to evaluate the proposed algorithm. The numerical results from our simulation show that our algorithm can improve offloading efficiency for mobile devices in mobile edge computing by improving transmission efficiency. By offloading more tasks to edge servers, both the energy efficiency of mobile devices and the responsiveness of computation-intensive applications can be improved simultaneously.

Distributed filtering algorithm based on local outlier factor under data integrity attacks

Network security is becoming a prominent issue for the development of information technology, and intelligent network attacks pose great challenges to system security due to its strong concealment. The existence of these attacks threatens the operation process of the complicated control system. Motivated by such a security problem, we study the secure distributed filtering algorithm under a kind of complex data integrity attack which can attack in two forms. We design a detection mechanism based on local outlier factor to distinguish the rightness of exchanged data, which determines whether to fuse the estimates by comparing the local density (LD) of the estimation of each sensor. Such a detection mechanism does not need the sensor to transmit redundant data information, thus greatly saving calculation cost and improving transmission efficiency. Meanwhile, we optimize the distributed filtering algorithm and obtain a suboptimal estimation gain. Finally, we demonstrate a numerical example to verify the availability of the filtering algorithm, and explore the influence of detector parameters on the performance of the estimation system.

Intelligent Random Access for Massive-Machine Type Communications in Sliced Mobile Networks

With the emerging Internet of Things paradigm, massive Machine-Type Communication (mMTC) has been identified as one of the prominent services that enables a broad range of applications with various Quality of Service (QoS) requirements for 5G-and-beyond networks. However, it is very difficult to employ a monolithic physical network to support various mMTC applications with differentiated QoS requirements. Moreover, in ultra-dense mobile networks, the scarcity of the preamble and Physical Downlink Control CHannel (PDCCH) resources may easily lead to resource collisions when a large number of devices access the network simultaneously. To tackle these issues, in this paper, we propose a network slicing-enabled intelligent random access framework for mMTC. First, by tailoring a gigantic physical network into multiple lightweight network slices, fine-grained QoS provisioning can be accomplished, and the collision domain of Random Access (RA) can be effectively reduced. In addition, we propose a novel concept of sliced preambles (sPreambles), based on which the transitional RA procedure is optimized, and the issue of preamble shortage is effectively relieved. Furthermore, with the aim of alleviating PDCCH resource shortage and improving transmission efficiency, we propose a learning-based resource-sharing scheme that can intelligently multiplex the PDCCH resources in the naturally dynamic environment. Simulation results show that the proposed framework can efficiently allocate resources to individual mMTC devices while guaranteeing their QoS requirements in random access processes.

Experimental Research on the Surface Quality of Milling Contour Bevel Gears

Contour bevel gears have the advantages of high coincidence, low noise and large bearing capacity, which are widely used in automobile manufacturing, shipbuilding and construction machinery. However, when the surface quality is poor, the effective contact area between the gear mating surfaces decreases, affecting the stability of the fit and thus the transmission accuracy, so it is of great significance to optimize the surface quality of the contour bevel gear. This paper firstly analyzes the formation process of machined surface roughness of contour bevel gears on the basis of generating machining method, and dry milling experiments of contour bevel gears are conducted to analyze the effects of cutting speed and feed rate on the machined surface roughness and surface topography of the workpiece. Then, the surface defects on the machined surface of the workpiece are studied by SEM, and the causes of the surface defects are analyzed by EDS. After that, XRD is used to compare the microscopic grains of the machined surface and the substrate material for diffraction peak analysis, and the effect of cutting parameters on the microhardness of the workpiece machined surface is investigated by work hardening experiment. The research results are of great significance for improving the machining accuracy of contour bevel gears, reducing friction losses and improving transmission efficiency.

Fundamental Study on Improvement of Transmission Efficiency by Applying α-Coil to Transcutaneous Energy Transmission System

Fundamental Study on Improvement of Transmission Efficiency by Applying α-Coil to Transcutaneous Energy Transmission System

Domain Knowledge Driven Semantic Communication for Image Transmission Over Wireless Channels

Recent progress in semantic communication has shown potential in improving transmission efficiency by the removal of signal-level redundancies. However, existing semantic communication systems fail to consider the high-level conceptual semantics embedded in the source, which is critical for human perception especially in certain domains. This letter proposes a novel domain knowledge driven semantic communication (DKSC) system, which is a dual-path framework with semantic extraction and reconstruction at both information and concept levels. Specifically, the dual-path semantic encoder and decoder are jointly designed and optimized in the end-to-end wireless communication system based on deep neural networks. To illustrate the performance of DKSC system, we execute image transmission task over wireless channels in medical domain as an example, and the impacts of various channel models and compression ratios are investigated. Experimental results demonstrate that with the integration of domain knowledge semantics, the proposed DKSC system outperforms other baseline schemes in terms of image restoration metrics with robustness against channel variations.

An novel optimal design method for segmented modification of cycloid gear based on improved transmission efficiency

An novel optimal design method for segmented modification of cycloid gear based on improved transmission efficiency

Design of a combined horizontal and U slot patch antenna with reduced cross-polarization and increased sustainability

This paper presents a rectangular microstrip patch antenna designed to operate at a frequency of 2.6348 GHz. The antenna is equipped with a U-slot and horizontal slot to mitigate cross-polarization effectively. By strategically placing the U-slot on the radiating patch and incorporating a horizontal slot on the patch, the antenna achieves enhanced radiation characteristics. It demonstrates excellent impedance matching with a VSWR of 1.02, indicating minimal signal reflection (S11 of -27.47dB) and improved transmission efficiency with a gain of 7.11dBi. The proposed design offers reduced cross-polarization characteristics and increased sustainability with compact size, making it suitable for WLAN applications prioritizing reliable and efficient communication.

Trajectory planning method with grinding compensation strategy for robotic propeller blade sharpening application

A propeller is the main part of a water-borne carrier's drive system. Geometrical shape accuracy and sharpness on the cutting side of the propeller's blade play vital roles to minimize fluid resistance and improve transmission efficiency. For Jet Ski and small boats, the significant thickness variation along the blade edge is embedded in the lost-wax casting process. The automatic trajectory planning for the robotic propeller blade's sharpening operation is challenging due to its complicated curved shape and the tiny gaps between two connected blades. The trajectory planning for robotic grinding based on the edge thickness distribution of the standard model may result in over- or under-cutting due to the highly inconsistent shape deformation caused by the casting process. To address the aforementioned challenges, this study proposes a fully automated robot grinding system. The proposed method combines a novel trajectory planning approach based on a parametric and point cloud model with a 3D scanning on edge-based trajectory adjustment approach. Moreover, to improve the grinding accuracy, a laser-vision sensor-based detection algorithm is also developed for grinding compensation to counteract the geometrical variation caused by the casting process. The effectiveness of the proposed system is validated through numerous experimental trials using a 6-DOF industrial robot. The research findings showcase that the proposed technique is feasible, stable, and effective for robotic propeller blade edge sharpening operations.

LoRa Backscatter Network Efficient Data Transmission Using RF Source Range Control

Networks based on backscatter communication provide wireless data transmission in the absence of a power source. A backscatter device receives a radio frequency (RF) source and creates a backscattered signal that delivers data; this enables new services in battery-less domains with massive Internet-of-Things (IoT) devices. Connectivity is highly energy-efficient in the context of massive IoT applications. Outdoors, long-range (LoRa) backscattering facilitates large IoT services. A backscatter network guarantees timeslot-and contention-based transmission. Timeslot-based transmission ensures data transmission, but is not scalable to different numbers of transmission devices. If contention-based transmission is used, collisions are unavoidable. To reduce collisions and increase transmission efficiency, the number of devices transmitting data must be controlled. To control device activation, the RF source range can be modulated by adjusting the RF source power during LoRa backscatter. This reduces the number of transmitting devices, and thus collisions and retransmission, thereby improving transmission efficiency. We performed extensive simulations to evaluate the performance of our method.

Performance Analysis of Reconfigurable Intelligent Surface-Assisted Wireless Communication Systems Under Co-Channel Interference

Reconfigurable Intelligent Surface (RIS) can intelligently control the wireless propagation environment by adjusting the signal phase and amplitude in real time, which is considered as one of the key technologies of 6G. Although RIS-assisted wireless communication systems greatly improve transmission efficiency under ideal conditions, there are various uncertainties in actual communication systems. In this paper, RIS-assisted communication system is investigated where the RIS cannot completely eliminate the phase error and the user location is randomly distributed with uncertainty. In addition, there are some interference sources around the user, which are simplified as co-channel interference (CCI). Then we study the performance of RIS-assisted communication system, and derive the closed-form expressions for the outage probability (OP) and channel capacity of the system. Furthermore, we analyze the effects of various parameters on the OP and channel capacity. Finally Monte Carlo simulation is carried out which verify the accuracy of the derivation.