Transmission In Wireless Networks Research Articles

Enhanced Performance Analysis of 120 Gbps Single‐Channel IQ Modulation Based PDM‐FSO Transmission System Using 64‐QAM Signals

ABSTRACTThe ever‐augmenting demand of data channel‐bandwidth by the end users has resulted in the exploration of new transmission techniques for wireless transmission networks. In this work, we have demonstrated the modeling of a single‐channel free space optics (FSO) transmission system by employing polarization‐division‐multiplexing (PDM) technique. Further, in‐phase‐quadrature modulation (IQM) has been used to increase the transmission efficiency of the system. To decrease the baud‐rate of the system, we have proposed the use of 64‐level quadrature amplitude modulation (QAM) signals. The net transmission rate of the system is 120 Gbps with a baud‐rate of 10 Gbps. Furthermore, the overcome the signal degradation of the 120 Gbps signal propagating through atmospheric channel, we have reported the use of advanced digital signal processing (DSP) algorithms. The system's performance is investigated for adverse external climate weather conditions and the results reported show reliable 120 Gbps data transmission along range between 870 m and 16.25 km with good performance of BER and EVM 7.5%.

Energy Efficient Approach with ANN based Intrusion Detection System for Securing Network and Route for Transmission in Wireless Sensor Network

The research focuses on hierarchical clustering-based intrusion detection using artificial neural networks (ANNs) for secure data transmission in wireless sensor networks (WSNs). WSNs consist of numerous tiny sensor nodes deployed to monitor environmental phenomena. These nodes face significant challenges, including restricted energy, memory space, communication range, and limited capacity for managing energy, storing, transmitting, and processing data. To address these limitations, a machine learning-based approach is proposed to detect intrusions and efficiently utilize energy by properly selecting cluster heads using a secure clustering protocol. The proposed method was implemented and tested using MATLAB software, employing the NSLKDD and UNSW-NB15 datasets for intrusion detection. The results demonstrated promising outcomes in detecting intruders and enhancing network efficiency, achieving a 92% packet delivery ratio (PDR) and 1.82 Mbps throughput. The study concludes that while WSNs are gaining popularity due to their simplicity, flexibility, and scalability, innovative solutions are necessary for efficient energy management and security. Future research should focus on advanced machine learning models, energy harvesting techniques, scalable protocols, real-time data processing, and integration with IoT platforms for broader applications and enhanced functionality.

Unveiling intrusions: explainable SVM approaches for addressing encrypted Wi-Fi traffic in UAV networks

AbstractUnmanned aerial vehicles (UAVs), also known as drones, have become instrumental in various domains, including agriculture, geographic information systems, media, logistics, security, and defense. These UAVs often rely on wireless communication networks for data transmission, making them vulnerable to cyberattacks. To address these challenges, it is necessary to detect potential threats by analyzing the encrypted Wi-Fi traffic data generated by UAVs. This study aimed to develop a linear SVM model that is enhanced with explainable artificial intelligence (XAI) techniques and fine-tuned using Bayesian optimization for intrusion detection systems (IDSs); the model is specifically designed to identify malware threats targeting UAVs. This research utilized encrypted Wi-Fi traffic data derived from three different UAV networks, namely, Parrot Bebop 1, DBPower UDI, and DJI Spark, while considering unidirectional and bidirectional communication flow modes. SVM-based intrusion detection models have been modeled on these datasets, identified their key features using the local interpretable model-agnostic explanations (LIME) technique, and conducted a cost analysis of the proposed modeling approach. The incorporation of the LIME method enabled to highlight the features that are highly indicative of cyberattacks and provided valuable insights into the importance of each feature in the context of intrusion detection. In conclusion, this interpretable IDS model, fine-tuned with Bayesian optimization, demonstrated its superiority over the state-of-the-art methods, proving its efficacy in detecting and mitigating threats to UAVs while offering a cost-effective solution.

DEVELOPMENT OF A HYBRID NETWORK CONGESTION MONITORING SYSTEM

Constantly growing requirements for the information systems service quality require monitoring of network congestion. The experimental results proved that when using hybrid networks, it is difficult to estimate the network load based on the average time of information delivery due to the presence of a significant scatter of time data. A mathematical model of information transmission in wireless computer networks in the form of a queuing system has been developed. The system identifies the main elements: a data transmission channel, a data frame and a device that transmits data. Analysis of transmission standards allows us to identify the following main transmission modes for modeling: one frame successful transmission; transmitting a frame with an error and repeating the transmission (possibly several times); frame transmission using performance-enhancing technology (Bursting technology is used as an example). Events associated with the transmission of information over the wireless network of one device are considered as monitoring system states under consideration. Packet exchange process was considered to be a homogeneous Markov process with discrete states, continuous time and constant intensities. A mathematical model has been developed based on the state graph of the device-frame-transmission channel system, which allows one to determine the timing characteristics for the previously identified modes. The methods for assessing network congestion based on statistical information during data transmission is proposed. Delivery times are broken down into ranges derived from the simulation. The proportion of packets whose delivery time lies within the selected test range is estimated. To evaluate the results, experimental studies were carried out on a fragment of the hybrid network. Delivery time results for each experiment were divided into four ranges: corresponding to accelerated delivery of fragments, successful delivery on the first, second and third attempts, respectively. Results analysis showed that it is preferable to use the fourth range to assess network congestion. Approximation reliability in this case is 0.85, the correlation coefficient is 0.92. The proposed methodology allows us to estimate network congestion based on testing data with a fairly high degree of reliability.

Enriched energy optimized LEACH protocol for efficient data transmission in wireless sensor network

Enriched energy optimized LEACH protocol for efficient data transmission in wireless sensor network

A State-Interactive MAC Layer TDMA Protocol Based on Smart Antennas

Mobile ad hoc networks are self-organizing networks that do not rely on fixed infrastructure. Smart antennas employ advanced beamforming technology, enabling ultra-long-range directional transmission in wireless networks, which leads to lower power consumption and better utilization of spatial resources. The media access control (MAC) protocol design using smart antennas can lead to efficient usage of channel resources. However, during ultra-long-distance transmissions, there may be significant transport delays. In addition, when using the time division multiple access (TDMA) schemes, it can be difficult to manage conflicts arising from adjacent time slot advancement caused by latency compensation in ultra-long-range propagation. Directional transmission and reception can also cause interference between links that reuse the same time slot. This paper proposes a new distributed dynamic TDMA protocol called State Interaction-based Slot Allocation Protocol (SISAP) to address these issues. This protocol is based on slot states and includes TDMA frame structure, slot allocation process, interference self-avoidance strategy, and slot allocation algorithms. According to the simulation results, the MAC layer design scheme suggested in this paper can achieve ultra-long-distance transmission without conflicts. Additionally, it can reduce the interference between links while space multiplexing. Furthermore, the system exhibits remarkable performance in various network aspects, such as throughput and link delay.

Case Study: Free Space Path Loss for Mobile Network and WLAN

Wireless communication systems transmit and receive information through free space. Thus, there are other factors to consider when designing a wireless communication system. One of those factors is Free space Path Loss (FPSL), which refers to the loss of signal strength in the propagation of the signal in free space. In this study, the effects of obstruction and distance on the FSPL of the transmission in mobile networks and Wireless Local Area Networks (WLAN) will be measured. The measured results show that the obstructions have a higher impact on the received signal compared to the distance. In the mobile network setting, the open area has an FPSL of 111 dB, whereas the obstructed office area has a significantly higher FSPL of 158 dB. Furthermore, in the WLAN setting, the FSPL of an obstructed area is 19 dB higher than the line-of-sight propagation. Thus, the layout of the area to implement a wireless communication system must be thoroughly analyzed for obstructions and distance to provide optimal wireless communication service to customers.

Research on Motion Capture System of Motor Skill Based on Computer Vision Technology

Compared with the existing motion capture system, the inertial conduction based motion capture method proposed in this project can effectively overcome the shortcomings of the current motion capture, such as limited communication distance, low accuracy of data acquisition, low visualization degree of model display software, narrow application range, etc., and improve the practical application value of the method. A method of motion capture and motion control based on wireless network is proposed. Since most of the skeleton of the human body is rigid, the complete expression of the human movement is realized through the study of 17 important joints, and all the movement information of the athlete can be obtained by placing sensors on the corresponding nodes. Through wireless network transmission technology, the player's action information is transmitted to the 3D modeling software to achieve real-time control of the action. When measuring each sensor, strapdown inertial navigation technology is used to improve the accuracy of acquisition. The 3D modeling software is based on a professional motion capture software, and through the forward and inverse kinematics of its motion, the 3D modeling is highly consistent with the wearable device.

Enhanced Secured and Real-Time Data Transmissions in Wireless Sensor Networks using SFRT Routing Protocol

Enhanced Secured and Real-Time Data Transmissions in Wireless Sensor Networks using SFRT Routing Protocol

Multi-UAV and IRS placement for secure data transmission in NOMA-enabled wireless networks

In this paper, we investigate multi-unmanned aerial vehicle (UAV)-enabled intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) downlink networks for secure data transmission in the presence of an intruder. Since Line of Sight (LoS) communication is obstructed, UAVs are utilized as aerial base stations to transmit confidential data to ground users with the assistance of IRS. The objective is to optimize the placement of UAVs and IRS, phase shift of the IRS, and transmit beamforming of the UAVs in order to maximize the network secrecy rate. The formulated optimization problem is non-convex in nature, posing a challenge in finding the optimal solution using conventional techniques. To tackle this problem, we propose a novel algorithm called balanced grey wolf optimizer and differential evolution (B-GWODE). This algorithm not only leverages the advantages of both the GWO and DE algorithms but also incorporates parameter modifications to mitigate the issue of premature convergence and to strike a suitable balance between exploration and exploitation. This hybrid approach efficiently search the solution space and obtain the optimal configuration that maximizes the network secrecy rate. Simulation results demonstrate the superiority of our proposed B-GWODE algorithm over the benchmark methods.

Multi-Flow Transmission in Wireless Interference Networks: A Convergent Graph Learning Approach

Multi-Flow Transmission in Wireless Interference Networks: A Convergent Graph Learning Approach

Spectrum sensing using deep learning for proficient data transmission in wireless sensor networks for wireless communication

Cognitive radio has been recommended for enhancing wireless spectrum usage, and an important part of cognitive radio is spectrum sensing. Conventional spectrum sensing techniques rely on energy detection and feature extraction from a received signal at a specific position. The advancement of artificial intelligence and deep learning has provided a chance to increase spectrum sensing efficiency. The proposed investigation presented a hybrid model comprising CNN, BILSTM, and Transformer Networks (TN) for spectrum sensing. With the aid of Transformer networks, the proposed model improves sensing accuracy even for lower SNR signals, particularly at −20 dB. The results of the proposed technique show that CNN-BILSTM-TN enhances spectrum sensing in comparison to earlier models studied in this domain. The proposed approach outperforms prior methods in terms of F1 Score and has an improved probability of detection at −20 dB and a lower likelihood of missed detection. Analysis of ten modulation techniques' performance criteria, such as the Jaccard index, Cohen Kappa coefficient, and Matthew's correlation coefficient, demonstrates that the suggested method's spectrum sensing is better even at lower SNRs.

DynAuthRoute: Dynamic Security for Wireless Sensor Networks

Objectives: The research aims to design an architecture for secure transmission of data in wireless sensor networks. Methods: The method involves three main pillars: authentication, data encryption, and dynamic routing. Extensive simulations have been conducted to evaluate the suggested method in terms of energy consumption, memory footprint, packet delivery ratio, end-to-end latency, execution time, encryption time, and decryption time. Findings: For authentication, a dynamic key is used to power an improved salt password hashing method. Data encryption is performed using format-preserving encryption (FPE) with the appended salt key. Dynamic routing is implemented using a cluster-based routing technique to enhance network efficiency in terms of power consumption and security. The execution time for MD5 ranges from 15 to 22 milliseconds, while for SHA-1 it ranges from 16 to 23 milliseconds and for the proposed salt key generation it is 1 to 5 milliseconds. Similarly, in terms of energy consumption, memory footprint, packet delivery ratio, end-to-end latency, execution time, encryption time, and decryption time the proposed method shows promising results in ensuring the integrity and security of transmitted encrypted data. Novelty: The presents a novel architecture with enhanced cluster head-based selection algorithm that combines dynamic key-based authentication and secure data routing to establish a safe environment for data transmission in wireless sensor networks. This research works offers a method for encrypting text with a dynamic salt key that is safe, energy-efficient, and lightweight. Keywords: Wireless Sensor Network, Dynamic Key, Authentication, Hash function, Salt algorithm, Dynamic routing, Node clustering, Format-preserving encryption

WiMAX Network Optimization Using Frame Period with Channel Allocation Techniques

Internet connectivity in WiMAX networks, along with various applications, is increasing rapidly, so the connectivity of internet and data transfer speed are always challenge for effective data transmission in wireless networks. Several factors affect the performance of networks. One important factor is to choose a suitable frame period for effective data transmissions. The performance of different frame period with round-robin and strict priority are evaluated in this work. A frame period in round robin performs better than a strict priority in terms of throughput, but a strict priority performs better in terms of drop rates is observed. This paper also demonstrates that an effective frame period, when combined with a proper bandwidth allocation algorithm, yields better results. This work gives the analysis that round robin performs 83.8847% better while strict priority performs 86.0020% better than the earliest deadline first algorithms for 10 subscriber stations in terms of throughput. This work is helpful to researchers and industrialists for actual implementations in WiMAX networks.

Overview of RIS-enabled secure transmission in 6G wireless networks

As the 6th-Generation (6G) wireless communication networks evolve, privacy concerns are expected due to the transmission of vast amounts of security-sensitive private information. In this context, a Reconfigurable Intelligent Surface (RIS) emerges as a promising technology capable of enhancing transmission efficiency and strengthening information security. This study demonstrates how RISs can play a crucial role in making 6G networks more secure against eavesdropping attacks. We discuss the fundamentals and standardization aspects of RISs, along with an in-depth analysis of Physical-Layer Security (PLS). Our discussion centers on PLS design using RIS, highlighting aspects including beamforming, resource allocation, artificial noise, and cooperative communications. We also identify the research issues, propose potential solutions, and explore future perspectives. Finally, numerical results are provided to support our discussions and demonstrate the enhanced security enabled by RIS.

Design of Photoelectric Positioning System and Realization of Its Positioning Mathematical Equation

The research of photoelectric positioning system based on wireless data transmission is a multidisciplinary research direction. In the design of photoelectric positioning system, the LED used for light sensing is selected as the light source, and the AC/DC isolated LED driving circuit based on AP3706 is designed. When designing photoelectric conversion circuit, considering the influence of noise interference on detection accuracy, a capacitor is added and connected in parallel with the feedback capacitor. In order to improve the detection accuracy, reduce the relative error of the four-channel signal processing process and maintain the consistency of the four channels, a noninverting amplifier circuit composed of four operational amplifiers LM324 amplifier chips is adopted in this study. NewMsg-RF2401 module is used for wireless data transmission. The system control module adopts ADμC841 single chip microcomputer as the control core. According to the characteristics of this single chip microcomputer, the corresponding ADC module input drive circuit and control-data transmission interface circuit are designed. While designing the hardware of the system, it is necessary to calculate the positioning position. In this study, a positioning mathematical equation is proposed, which can obtain the position of the moving target in the geographical area under the wireless transmission network. In the experiment, firstly, the implementation process of the positioning mathematical equation is described, and then the performance of the proposed positioning mathematical equation is compared with that of the random positioning equation and the binary positioning equation. The results show that more messages can be transmitted by using the positioning mathematical equation proposed in this study. Based on this, it is used in the positioning system designed in this study, which is unfolded under the condition of constant background light, adjusts the position of the movable light source and determines the position coordinates. According to the horizontal and vertical displacement of the light source detected by the system, the positioning error is less than 0.1%, which is in line with the design expectation.

High-capacity medical information hiding scheme with P-tensor product secret image sharing for wireless body area networks

Given the escalating demand for information transmission in the resource-restricted wireless body area networks (WBANs), securing medical data and minimizing energy consumption are paramount. We present an innovative information hiding scheme that employs P-tensor product secret image sharing (PTP-SIS) and multiple information-hiders for WBANs. Considering the remarkable compression performance demonstrated by compressed sensing (CS), as well as its link to Shamir's (k, n) secret sharing method, using CS rather than traditional secret sharing techniques for image processing purposes could potentially help alleviate transmission burden of sensor nodes. However, utilizing CS to process high-dimensional signals poses a significant challenge due to the large dimensionality of the measurement matrix. The P-tensor product (PTP) is a tool that offers outstanding universality and can overcome the dimension limitations of traditional matrix multiplication, it is applied in the secret sharing stage. Moreover, applying the ideas of secret sharing leads to less stress on an individual device as well as lower communication spending, and multiple hiders have the ability to independently embed additional secrets into shadow images for efficient information backup. Theoretical analysis and experiments validate that the proposed scheme ensures information security and transmission efficiency while achieving superior image recovery performance and higher information embedding rates compared to other approaches.

Throughput Maximization for Multipath Secure Transmission in Wireless Ad-Hoc Networks

Throughput Maximization for Multipath Secure Transmission in Wireless Ad-Hoc Networks

Self‐attention based generative adversarial network with Aquila optimization algorithm espoused energy aware cluster head selection in WSN

SummaryWSNs have a wide range of applications, and the effective Wireless Sensor Network (WSN) design includes the best energy optimization techniques. The nodes in wireless sensor networks run on batteries. The existing cluster head selection methods do not take into account the latency and rate of wireless network traffic when optimizing the node's energy constraints. To overcome these issues, a self‐attention based generative adversarial network (SabGAN) with Aquila Optimization Algorithm (AqOA) is proposed for Multi‐Objective Cluster Head Selection and Energy Aware Routing (SabGAN‐AqOA‐EgAwR‐WSN) for secured data transmission in wireless sensor network. The proposed method implements the routing process through cluster head. SabGAN classifiers are utilized to select the CH based on firm fitness functions, including delay, detachment, energy, cluster density, and traffic rate. After the selection of the cluster head, the malicious node gains access to the cluster. Therefore, the ideal path selection is carried out by three parameters: trust, connectivity, and degree of amenity. These three parameters are optimized under proposed AqOA. The data are transferred to the base station with the support of optimum trust path. The proposed SabGAN‐AqOA‐EgAwR‐WSN method is activated in NS2 simulator. Finally, the proposed SabGAN‐AqOA‐EgAwR‐WSN method attains 12.5%, 32.5%, 59.5%, and 32.65% higher alive nodes; 85.71%, 81.25%, 82.63%, and 71.96% lower delay; and 52.25%, 61.65%, 37.83%, and 20.63% higher normalized network energy compared with the existing methods.

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.