Communication Network Transmission Research Articles

An optimized cooperative data transmission scheme in relay‐enabled cellular communication networks

SummaryCooperative transmission is of great significance in data transmission and resource schedule in mobile cellular communication networks. To attain the desired network transmission performance objectives over the whole cellular network system, we propose an appropriate cooperative data transmission scheme to optimize the data delivery efficiency in terms of the transmission time consumption for each and every transmission group. The proposed transmission optimization scheme includes the tasks of determining the transmission group, allocating the channel rate resource, specifying the cooperative transmission mechanism, and performing resource allocation and schedule as well. Firstly, we propose a utility function based rate allocation scheme to optimize the channel rate resource utilization for all those transmission groups over the cellular communication network. Based on it, we further present a cooperative data transmission scheme to deal with the data delivery and reception for all those subgroups with high efficiency over the whole network system. Particularly, we propose a resource efficiency function‐based coordination scheduling (EFCS) scheme to conduct the cooperative data transmission and resource schedule as well for each transmission group within the network. The EFCS scheme facilitates to determine the subgroups for schedule over each scheduling cycle, which can produce the best data transmission efficiency across both the direct and cooperative transmission hop. Both the theoretical analysis and the simulation evaluation results verify the superior performance of our proposed cooperative data transmission scheme.

Channel prediction method based on the data-driving for distribution automation main station

A data-driven channel prediction method for distribution automation master is proposed to address the poor quality of communication network and communication system transmission problems in distribution network communication. In this paper, an adaptive broad learning network (ABLN) consisting of a standard broad learning network and a hybrid learning network is introduced to predict the channel state information of the communication system. Among them, the hybrid learning network is used to solve the ill-conditioned solution problem when estimating the output weight matrix of the standard broad learning network. Therefore, the ABLN produces sparse output weight matrices and provides excellent prediction performance. In the simulation analysis, the outdoor and indoor scenes are considered based on OFDM system. The prediction performance of ABLN is subsequently evaluated in one step prediction and multistep prediction. The results show that for the prediction performance is concerned, the maximum improvement of ABLN is about 96.49% as compared to other evaluation models, indicating that the CSI is effectively predicted by the ABLN to support the adaptive transmission of the main station of the distribution automation and to satisfy the quality of the communication network of the distribution network.

Asymptotical tracking control for the complex network based on the dynamic topology

A tracking control scheme is proposed for complex dynamic network (CDN), where the CDN is regarded wholly as a dynamic composite system which consists of two mutually coupled subsystems. One subsystem consists of all nodes and the other consists of all links, and consider the weights of the links to be state variables in the latter subsystem. There are two parts in the structure of the proposed tracking control scheme: the designed controller of nodes and the synthesis of the coupling term in links. These two parts can guarantee two subsystems to asymptotically track the given reference targets, respectively. This approach originates from the communication transmission network (CTN). In CTN, for the network optimization management, the reference network topology (NT), such as the star topology, is required as a target for tracking in communication transmission (links) when each node in network needs to track its own target. The control scheme provided of this paper coincides with above requirement. And finally, a comparative simulation example is given for illustrating the effectiveness of the provided control scheme.

Linear Anti-interference Algorithm for Digital Signal Transmission in Fiber Optic Communication Networks based on Link Analysis

In order to achieve accurate transmission of protection signals in fiber optic communication networks, it is necessary to perform channel balancing configuration of fiber optic communication networks and adaptive forwarding control processing of relay protection signals, the author proposes an accurate transmission method for relay protection signals in fiber optic communication networks based on time-varying multipath fading suppression and adaptive beamforming. The system analyzes the sources of wireless long-distance pain signal interference signals, introduces anti-interference technologies such as two-dimensional joint processing (STAP), provides anti-interference algorithms and related gain analysis, and conducts signal processing gain simulation using MATLAB. Based on the analysis of comprehensive simulation results, at a given symbol length, the signal bandwidth increases, and the processing gain infinitely approaches the given theoretical limit value, rather than increasing nonlinearly. The reason is that the channel is affected by noise, and the channel estimation value and signal conjugate multiplication produce a noise quadratic term. At this point, the estimated value of the coherent region channel is reduced by the influence of noise, and the signal-to-noise ratio loss caused by the noise quadratic term is reduced, so the processing gain increases. During the process of infinite increase in signal bandwidth, the input signal-to-noise power ratio of the receiver tends to decrease towards an infinite value, limited by the size of the coherent region. The channel estimation value increases under the influence of noise, and the noise quadratic term is the main factor affecting the output noise power. When the symbol length is greater than the coherent time, the smaller the maximum Doppler frequency shift and the larger the coherent detection area, the greater the processing gain.

RIS-Assisted Device Activity Detection With Statistical Channel State Information

This paper studies reconfigurable intelligent surface (RIS)-assisted device activity detection for grant-free (GF) uplink transmission in wireless communication networks. In particular, we consider mobile devices located in an area where the direct link to an access point (AP) is blocked. Thus, the devices try to connect to the AP via a reflected link provided by an RIS. Therefore, for the RIS, a phase-shift design is desired that covers the entire blocked area with a wide reflection beam because the exact locations and times of activity of the devices are unknown in GF transmission. In order to study the impact of the phase-shift design on the device activity detection at the AP, we derive a generalized likelihood ratio test (GLRT) based detector and present an analytical expression for the probability of detection, which is a function of the channel statistics and the phase-shift design. Assuming knowledge of statistical channel state information (CSI), we formulate an optimization problem for the phase-shift design for maximization of the guaranteed probability of detection for all locations within a given coverage area. To tackle the non-convexity of the problem, we propose two different approximations of the objective function and an algorithm based on the majorization-minimization (MM) principle. The first approximation leads to a design that aims to reduce the variations of the end-to-end channel while taking system parameters such as transmit power, noise power, and probability of false alarm into account. The second approximation can be adopted for versatile RIS deployments because it only depends on the line-of-sight (LoS) component of the end-to-end channel and is not affected by system parameters. For comparison, we also consider a phase-shift design maximizing the average channel gain and a baseline analytical phase-shift design for large blocked areas. Our performance evaluation shows that the proposed approximations result in phase-shift designs that guarantee a high probability of detection across the coverage area and outperform the baseline designs.

RESEARCH OF AUDIO AND VIDEO TRAFFIC THE CHARACTERISTICS IN LOW-BANDWIDTH RADIO COMMUNICATION NETWORKS

The construction of mass service systems, namely automated control systems, requires preliminary analysis and modeling of traffic in their communication networks. Mathematical models of various types of traffic have been developed for public networks, which allows to estimate the necessary functional characteristics of equipment for building a communication network, depending on the number of users. Low-bandwidth communication networks, which are built on the basis of ultra high frequency and very high frequency (UHF/VHF) radio stations, are distinguished by low speed, high delay and jitter of data transmission. To work in such communication networks, special data transmission protocols are adapted and developed. In this paper, a study of the characteristics of audio and video traffic in low-bandwidth communication networks is carried out, which are built on the basis of UHF/VHF radio stations, which will allow creating a software implementation of simulated traffic modeling for the further determination of the services availability at the stage of planning and designing the communication system. Two personal computers and two modern RF‑7850M-HH UHF/VHF radio stations were used to study the characteristics of audio traffic. The radio stations worked in three operating modes: narrowband mode with a fixed carrier frequency FF, narrowband mode with pseudo-random adjustment of the operating frequency QL1A, and wideband mode ANW2C. The voice was transmitted in digital mode using the built-in MELP 2400 codec, and the "iperf-v2.0.5" software was used to determine the characteristics of the audio traffic on personal computers connected to these radio stations. Two personal computers, two modern RF‑7850M‑HH UHF/VHF radio stations, a video encoder and a video camera were used to study video traffic characteristics. The radio stations operated in ANW2C broadband mode. To evaluate the characteristics of the video traffic, the Wireshark software was used on a personal computer, with the help of which the video broadcast from the video encoder was presented. It was found that voice transmission in low-speed communication networks based on UHF/VHF radio stations occupies a bandwidth of 2 Kbit/s - 2.5 Kbit/s, and when voice and data are simultaneously transmitted in radio stations, data buffering and jitter increase. The resolution, bitrate, FPS, and necessary bandwidth of video traffic that can be transmitted via UHF/VHF radio communication channels are determined. Based on the conducted research, recommendations are provided for the transmission of video traffic through low-bandwidth communication channels.

A new scheme of 2:1 photonic multiplexer and multiplexer-based NOT, OR, AND logic gates in electro-optic Mach–Zehnder interferometer

This paper introduces the development of NOT, OR, and AND logic gates utilizing a 2:1 Multiplexer (MUX) based on a titanium-diffused lithium niobate electro-optic Mach–Zehnder interferometer. The shift towards large-scale optical integrated circuits as an alternative to traditional CMOS technology has gained traction, driven by the growing demand for high-speed computation and data transfer rates, reaching up to the terahertz scale, along with the need for energy-efficient interconnects. To optimize the design and reduce the number of photonic MUX, we leverage Shannon decomposition and Reduced Binary Decision Diagram mapping in the creation of MUX-based combinational and logic circuits. The entire design undergoes comprehensive simulation and verification using OPTIBPM with a beam propagation method (BPM). The wafer dimensions for the 2:1 electro-optic MZI-MUX and MUX-based NOT, AND, OR gates are 33 mm × 100 μm, classifying them as integrated optics. The proposed photonic MUX-based combinational circuits exhibit rapid response times, making them particularly advantageous for communication systems, transmission networks, and various industrial applications. Key device parameters, including insertion loss (0.0012 dB), extinction ratio (ER) (28.97 dB), and contrast ratio (29.5 dB), fall within acceptable limits. The BPM simulated results align well with the mathematical computations based on PYTHON simulations.

Application of quantum key distribution in intelligent security operation and maintenance of power communication networks

With the continuous development of power communication network and the improvement of intelligent degree, network security and operation and maintenance become more and more important. Therefore, this paper proposes a solution for intelligent security operation and maintenance of power communication network based on Quantum key distribution (QKD). QKD is an encryption technology based on the principle of quantum mechanics, which can realize secure Key exchange and resist attacks of traditional encryption algorithms. We use QKD technology to generate and distribute security keys for protecting communication and data transmission in power communication networks. The results show that the efficiency and accuracy of communication data acquisition, transmission, analysis and processing of the Artificial Intelligence for IT Operations system of the power communication network using the power Internet of Things technology are far higher than that of the traditional operation and maintenance technology, which improves the operation and maintenance accuracy of the power communication network by about 25%. The intelligent operation and maintenance system of the power communication network designed by the author, it effectively improves the communication data processing capability and the reliability of operation and maintenance results, and can meet the current practical engineering application requirements. This study provides an innovative solution for the secure operation and maintenance of power communication networks, which is of great significance for protecting the security and stable operation of power communication networks.

Semantic-Driven Efficient Service Network Towards Smart Healthcare System in Intelligent Fabric

The advantages of intelligent fabrics enable health service systems more efficient and safe to perceive and transmit, where massive sensitive data related to health and behavior are collected through the multi-source flexible sensor network. However, due to its complex network structure, health service systems face the challenge of low-power data transmission and processing in intelligent fabric space. Recently, Deep learning-powered semantic communication (Deep-SC) has emerged as a promising communication paradigm. To tackle the above problem, we introduce the concept of semantic cognition into the cyber-physical system of health service and present the Deep-SC based network service framework for the healthcare system, where physical layer blocks are merged into the traditional communication system to jointly optimize the transceiver in communication. Since semantic encoding and decoding require additional knowledge, consider the introduction of the semantic knowledge base in the system to formulate the joint optimization problem of service offloading and bandwidth allocation in the proposed network service framework, with the goals of reliable semantic communication and efficient network transmission. Furthermore, an online algorithm that optimally adapts service offloading and subcarrier allocation decisions to the time-varying channel conditions is required. Finally, we use a reinforcement learning-based decision algorithm to solve combinatorial optimization problems, which further reduces the computing complexity. Experimental results show that the proposed framework achieves significant performance improvements in system energy consumption and reliable transmission, compared with traditional communication strategies.

A Comparative Study of Plastic and Glass Optical Fibers for Reliable Home Networking

Home networking using fiber optics is essential for uninterrupted data transmission in modern communication networks. In this study, we evaluated and compared the reliability of plastic optical fibers (POFs) and glass optical fibers (GOFs) for home networking applications. Furthermore, assess the advantages and disadvantages of POF and GOF over short distances and find that POF is more suitable for home network applications due to its higher reliability. In addition, it has the advantage of being cost-effective and flexible for short-distance applications. The results show that POF indicates higher reliability and better performance at 8.25517 × 101of the Q factors, 2.21355 × 10−3 of the eye height, and 2.8307 × 10−3 of the threshold values at 30 meters, while GOF shows 6.30 × 101 of the Q factor, 3.78087 × 10−3 of the eye heights and 4.34736 × 10−3 of the threshold values. Moreover, this research highlights the importance of reliability in designing and applying optical fiber networks and can help network designers and engineers make informed decisions when selecting the appropriate type of optical fiber for specific applications.

Event-triggered near-optimal tracking control based on adaptive dynamic programming for discrete-time systems

Frequent state monitoring and controller updates can enhance the precision of tracking control, while simultaneously overburdening the communication network transmission. In this paper, For the purpose of saving communication costs, we propose event-triggered control algorithms for the optimal tracking control problem. First, we reconstruct the discrete-time nonlinear system into a converted system. Then, the adaptive dynamic programming algorithm is employed to find the optimal controller off-line, and the event-triggered scheme is used to reduce the communication costs online. Novel triggering conditions with fewer assumptions are designed to implement the event-triggered scheme. Different from existing works, the event-triggered scheme can be introduced not only into the converted system but also into the actual system, which is more practical because the actual controller is what one can only access in practice. In addition, with the developed algorithms, the tracking error can be proved to be stable at the origin, in other words, the actual system can be guaranteed to track the desired trajectory. Algorithms developed in this paper are implemented by three neural networks, the model network, the action network and the critic network. Finally, examples are presented to verify the effectiveness and rationality of the algorithms.

Fuzzy Harmony Search Technique for Cyber Risks in Industry 4.0 Wireless Communication Networks

Industry 4.0 houses diverse technologies including wireless communication and shared networks for internal and external operations. Due to the wireless nature and remote operability, the exposure to security threats is high. Cyber risk detection and mitigation are prominent for secure industrial operations and planned outcomes. In addition, the system faces the threat of intelligence attacks, security standards issues, privacy concerns and scalability problems. The cyber risk related research problems influence overall data transmission in industry wireless communication networks. For augmenting communication security through cyber risk detection, this article introduces an Explicit Risk Detection and Assessment Technique (ERDAT) for cyber threat mitigation in the industrial process. A fuzzy harmony search algorithm powers this technique for identifying the risk and preventing its impact. The harmony search algorithm mimics the adversary impact using production factors such as process interruption or halting and production outcome. The search performs a mimicking operation for a high objective function based on production output for the admitted plan. The fuzzy operation admits the above factors for identifying the cyber impacting risk, either for its impacts or profitable outcome. In this process, the fuzzy optimization identifies the maximum or minimum objective output targeted for either outcome or risk interrupts, respectively. The fuzzy threshold is identified using a mediated acceptable range, computed as the ratio between minimum and maximum, mimicking occurrences between the risk and scheduled production outcomes. Therefore, the mimicking crossing or falling behind the threshold for the interruption/halting or production, respectively, are identified as risks and their source is detected. The detection communication source is disconnected from the industrial process for preventing further adversary impacts. The introduced system achieves 8.52% high-risk detection, 12.5% fewer outcome interrupts, 8.3% fewer halted schedules, 8.08% less interrupt span, and 7.94% less detection time compared to traditional methods.

The strategic analysis and operation of the multiservice model used for synchronous transmission in communication networks

The core idea of asynchronous transfer mode (ATM) technology was revealed a long time ago. The main technology under development at the time was time-division multiplexing (TDM) technology, which consisted of synchronous switching based on the sequence number of bytes in the integrated frame. The main disadvantage of TDM technology, also known as synchronous transport module (STM) synchronous transmission technology, is the inability to reallocate the bandwidth of the integrated channel between subchannels. During those periods when no user data is sent on the subchannel, the aggregated channel still sends the bytes of this subchannel filled with zeros. Efforts to load sub channels’ idle periods necessitate the introduction of a header for each subchannel’s data. In intermediate statistical time-division multiplexing (STDM) technology, which allows idle periods to be filled by transmitting bursts of traffic from other sub channels, headers that actually have a subchannel number are introduced. In this paper, the strategic analysis and operation of technologies used in multiservice networks were discussed. Simultaneously, the structure of data sets is drawn into sets resembling computer networks. The fact that each packet has an address allows it to be transmitted asynchronously since its location relative to data on other subchannels is not its address. Asynchronous packets from one subchannel are inserted into the free time slots of another subchannel, but they are not mixed with the data of this subchannel because they have their own address.

Space optical communication system with a sub-second acquisition time.

Acquisition is the key technology in space laser communication and the nodus in communication-link establishment. Traditional laser communication demands too long an acquisition time to meet the requirements of a space optical communication network and real-time transmission of big data. One novel laser communication system which fuses a laser communication function with a star-sensitive function to achieve precise autonomous calibration of the open-loop pointing direction of line of sight (LOS) is proposed and developed. Theoretical analysis and field experiments proved that the novel, to the best of our knowledge, laser-communication system can achieve sub-second-level scanless acquisition.

Improved Rate of Intelligent Surfaces for Vehicular Networks

An intelligent reflecting surface (IRS) is an array that consists of a large number of passive reflecting elements. Such a device possesses the potential to extend the coverage of transmission in future communication networks by overcoming the effects of non line-of-sight propagation. Accordingly, to present the case for utilizing IRS panels in future wireless networks, in this paper, we analyze a multi-user downlink network aided by IRS. In particular, by using a realistic 5G channel model, we compare the performance of the IRS-aided network with a decode and forward (DF) relay-aided scenario and a network without IRS or relay. Our analysis revealed the following: (i) At best, communication aided by a DF relay with perfect channel state information (CSI) could match the performance of the IRS-aided network with imperfect CSI when the channel estimation error was high and the number of users was large. (ii) IRS-aided communication outright outperformed the DF relay case when the transmit power was high or the number of users in the network was low. (iii) Increasing the number of elements in an IRS translated to greater quality of service for the users. (iv) IRS-aided communication showed better energy efficiency compared with the other two scenarios for higher quality of service requirements.

PAPR Analysis of OFDM using Partial Transmit Sequence Method

Orthogonal Frequency Division Multiplexing (OFDM) is one of the most widely used multicarrier transmission and effective technologies in today's communication networks. OFDM has many benefits and drawbacks. High Peak to Average Power Ratio (PAPR) is one of its main drawbacks. The spectral efficiency of the high-power amplifiers decreases with increasing PAPR. Therefore, maintaining a wireless system's efficiency is required to lower the PAPR. A possible method for lowering the high PAPR in OFDM systems is Partial Transmit Sequence (PTS). PTS generates a number of candidate signals, and the best signal with the lowest PAPR is chosen for transmission. The results shows that the PTS technique achieves greater PAPR minimization with less complexity. MATLAB simulation has been used to examine the OFDM system's PSD, spectral efficiency, BER performance, and PAPR analysis.

Analysis of the Construction Requirements and Technical Scheme of 5G Communication Transmission Network

Analysis of the Construction Requirements and Technical Scheme of 5G Communication Transmission Network

Research on Children’s Education App Network Transmission Based on 5G Mobile Computing Technology

With the continuous improvement of China’s scientific and technological level, the popularity of mobile network technology is becoming more and more widespread. Many big data technologies and wireless sensor technologies have brought new changes to people’s lives. At present, the functions of communication technology and network transmission have moved from perfection to new innovation and development. 5G mobile network technology has played an important role in various fields. When China’s economy and science and technology develop better and better, people pay more and more attention to children’s education. The research on children’s education has become a hot topic. From the above background, this paper studies the network transmission function and network transmission path of children’s education app in 5G era mobile computing technology. First, starting from the development trend and main functions of 5G, this paper briefly describes the functional requirements of children’s education app. The efficient data transmission in the 5G mobile wireless sensor network is applied to children’s education app. Starting from the distance of network transmission nodes, the data transmission optimization algorithm is adopted, and the network transmission module is composed of the best transmission path of nodes. Combined with the energy-saving effect of mobile computing technology, the problem of excessive consumption of network transmission resources is optimized. Finally, the data transmission path is studied in the 5G mobile network. The results show that 5G mobile computing technology can optimize the network transmission performance, improve the operation efficiency of the server, and has a good effect in solving the problems of delay and low coverage. In the process of children’s education app network transmission under 5G mobile computing technology, it can ensure the user’s personal information and improve the security of system feedback.

Research on Digital Twin Modeling and Simulation Technology for Distributed Resource Aggregation Regulation

Virtual power plants need to build awareness, transmission and application of information flow model, require multiple levels between virtual power plant, the virtual power plant each participation main body, regulation and control of virtual power plant and quantification of communication information transmission between the main constraints, this paper studies the distributed resources polymerization technology, the modeling and simulation of mechanical and electrical characteristics of virtual power plant communication network transmission characteristics of digital simulation technology, This paper proposes a simulation method of diversified resource aggregation regulation based on virtual group structure. By collecting the electrical characteristic change curve of each distributed unit, and stacking the transmission characteristics of communication network, digital simulation aggregation is carried out to obtain the digital model of cooperative operation and control characteristics of virtual power plant "information flow + energy flow". Through this model will be connected to Matlab/Simulink power system simulation environment for power regulation and operation simulation verification.

Survey on encode biometric data for transmission in wireless communication networks

The aim of this research survey is to review an enhanced model supported by artificial intelligence to encode biometric data for transmission in wireless communication networks can be tricky as performance decreases with increasing size due to interference, especially if channels and network topology are not selected carefully beforehand. Additionally, network dissociations may occur easily if crucial links fail as redundancy is neglected for signal transmission. Therefore, we present several algorithms and its implementation which addresses this problem by finding a network topology and channel assignment that minimizes interference and thus allows a deployment to increase its throughput performance by utilizing more bandwidth in the local spectrum by reducing coverage as well as connectivity issues in multiple AI-based techniques. Our evaluation survey shows an increase in throughput performance of up to multiple times or more compared to a baseline scenario where an optimization has not taken place and only one channel for the whole network is used with AI-based techniques. Furthermore, our solution also provides a robust signal transmission which tackles the issue of network partition for coverage and for single link failures by using airborne wireless network. The highest end-to-end connectivity stands at 10 Mbps data rate with a maximum propagation distance of several kilometers. The transmission in wireless network coverage depicted with several signal transmission data rate with 10 Mbps as it has lowest coverage issue with moderate range of propagation distance using enhanced model to encode biometric data for transmission in wireless communication.