Transmission Scheme Research Articles

An Enhanced Q-Learning MAC Protocol for Energy Efficiency and Convergence in Underwater Sensor Networks

Under-Water Sensor Networks (UWSNs) are important for applications like oceanographic data collection, environmental protection, monitoring, and disaster response. These UWSN networks face challenges in energy efficiency and protocol convergence because of dynamic underwater ecosystems limited in number and low channel capacity. This paper covers and finds real-world solutions for these challenges by proposing an adaptive Q-Learning Medium Access Control (MAC) protocol for UWSNs. The methodology used in this paper involves utilizing Q-Learning, a reinforcement learning technique, to make sensor nodes autonomously refine their transmission strategies in real-time, enhancing energy consumption and improving protocol convergence. The protocol was implemented using the NS 3 network simulator, which offers a detailed and real-world environment for analyzing the protocol’s performance. Extensive simulations were conducted, and experiments were used to analyze the performance of the proposed protocol. The results showcase significant improvements over other and traditional MAC protocols, with a 13% to 19% increase in energy efficiency and channel utilization enhancement in static and mobile network scenarios. The adaptive Q-Learning MAC protocol provides a robust solution for the challenges of UWSNs, offering energy efficiency and faster convergence times. This research significantly contributes to the advancement of efficient and adaptive underwater communication protocols, paving the way for future development in the field

Joint Noniterative Beamforming Schemes for BER Minimization in Next‐Generation Wireless Sensor Networks

This research paper proposes three joint transmit and receive (TX/RX) beamforming schemes for minimizing the bit error rates of next‐generation wireless sensor networks. Based on minimizing the optimization problem of the total mean squared error between the transmitted and received data symbols, the first beamforming scheme is proposed. The second beamforming scheme is based on the projection of the effective channel on the space spanned by the channel matrix. A third practical beamforming scheme based on the strongest eigenvalues of the channel matrix is introduced. This beamforming scheme proves its optimality in its operation under the condition that the number of TX antennas is equal to or larger than the total number of RX antennas. The proposed joint TX/RX beamforming schemes are formulated in closed form. Numerous numerical results are provided using the MATLAB platform. The proposed beamforming schemes are compared with the widely adopted block diagonalization transmission scheme and linear block diagonalization. Moreover, the proposed systems are compared with state‐of‐the‐art beamforming techniques such as Tomlinson–Harashima precoding‐based MMSE. The simulation results demonstrated that the proposed beamforming schemes achieved better bit error rate performance than the block diagonalization and linear block diagonalization transmission schemes. Furthermore, the third beamforming scheme provides a gain of about 4dB compared to the cutting‐edge technology of beamforming Tomlinson–Harashima precoding‐based MMSE. Accordingly, more robust communications can be achieved for next‐generation wireless sensor networks. This research paper provides an efficient manner to meet the demanded reliability of next‐generation wireless sensor networks, which is a bit error rate of 10−9.

Transmission Scheme for Massive MIMO Systems Using Nulling‐Based Approach

Transmission Scheme for Massive MIMO Systems Using Nulling‐Based Approach

Temporal changes in Plasmodium falciparum genetic diversity and multiplicity of infection across three areas of varying malaria transmission intensities in Uganda

BackgroundMalaria is a significant public health challenge in Uganda, with Plasmodium falciparum (P. falciparum) responsible for most of malaria infections. The high genetic diversity and multiplicity of infection (MOI) associated with P. falciparum complicate treatment and prevention efforts. This study investigated temporal changes in P. falciparum genetic diversity and MOI across three sites with varying malaria transmission intensities. Understanding these changes is essential for informing effective malaria control strategies for the different malaria transmission settings.MethodsA total of 220 P. falciparum-positive dried blood spot (DBS) filter paper samples from participants in a study conducted during 2011–2012 and 2015–2016 were analyzed. Genotyping utilized seven polymorphic markers: Poly-α, TA1, TA109, PfPK2, 2490, C2M34–313, and C3M69–383. Genetic diversity metrics, including the number of alleles and expected heterozygosity, were calculated using GENALEX and ARLEQUIN software. MOI was assessed by counting distinct genotypes. Multi-locus linkage disequilibrium (LD) and genetic differentiation were evaluated using the standardized index of association (IAS) and Wright's fixation index (FST), respectively. Statistical comparisons were made using the Kruskal–Wallis test, and temporal trends were analyzed using the Jonckheere–Terpstra test, with statistical significance set at p < 0.05.ResultsOf the 220 samples, 180 were successfully amplified. The majority of participants were males (50.6%) and children aged 5–11 years (46.7%). Genetic diversity remained high, with mean expected heterozygosity (He) showing a slight decrease over time (range: 0.73–0.82). Polyclonal infections exceeded 50% at all sites, and mean MOI ranged from 1.7 to 2.2, with a significant reduction in Tororo (from 2.2 to 2.0, p = 0.03). Linkage disequilibrium showed a slight increase, with Kanungu exhibiting the lowest IAS in 2011–2012 (0.0085) and Jinja the highest (0.0239) in 2015–2016. Overall genetic differentiation remained low, with slight increases in pairwise FST values over time, notably between Jinja and Tororo (from 0.0145 to 0.0353).ConclusionsThis study highlights the genetic diversity and MOI of P. falciparum in Uganda's malaria transmission settings, noting a slight decrease in both genetic diversity and MOI overtime. Continued surveillance and targeted control strategies are essential for monitoring the impact of malaria control efforts in Uganda.

IMPROVING THE TECHNOLOGY OF MANUFACTURING CRANKSHAFTS BY FORGING

The article discusses the methods of manufacturing crankshafts by various methods and focuses on the forging method. Different approaches to producing crankshafts are considered, taking into account the requirements for the final product. A study of the crankshaft forging process was carried out by modelling forging schemes using the technological tool vestiges. This made it possible to visualise various aspects of the technological process and find out which methods and transmission schemes are the most rational for producing a crankshaft by forging. Based on the data obtained, conclusions were drawn that indicate which approaches and methods of crankshaft production are rational while reducing the number of technological transitions. The results of the study can be useful for industries engaged in crankshaft forging, helping them to choose the most rational methods and schemes of metal transfer during crankshaft forging to improve the production process and reduce costs.

Improving Transmission in Integrated Unmanned Aerial Vehicle–Intelligent Connected Vehicle Networks with Selfish Nodes Using Opportunistic Approaches

The integration of unmanned aerial vehicles (UAVs) into vehicular networks offers numerous advantages in enhancing communication and coverage performance. With the ability to move flexibly in three-dimensional space, UAVs can effectively bridge the communication gap between intelligent connected vehicles (ICVs) and infrastructure. However, the rapid movement of UAVs and ICVs poses significant challenges to the stability and reliability of communication links. Motivated by these challenges, integrated UAV–ICV networks can be viewed as vehicular delay-tolerant networks (VDTNs), where data delivery is accomplished through the “store-carry-forward” transmission mechanism. Since VDTNs exhibit social attributes, this paper first investigates the opportunistic transmission problem in the presence of selfish nodes. Then, by enabling node cooperation, this paper proposes an opportunistic transmission scheme for integrated UAV–ICV networks. To address the issue of node selfishness in practical scenarios, the proposed scheme classifies the degree of cooperation and analyzes the encounter probability between nodes. Based on this, information is initially flooded, and the UAV is selected for data distribution by jointly considering the node centrality, energy consumption, and cache size. Finally, simulation results demonstrate that the proposed scheme can effectively improve the delivery ratio and reduce the average delivery delay compared to state-of-the-art schemes.

A systematic review of age-structured malaria transmission models (2019–2024)

Malaria remains a serious and potentially fatal vector-borne disease, consistently ranking among the world’s deadliest infections. This study presents a systematic review of age-structured malaria transmission models. Articles were sourced from PubMed, Google Scholar, and the Research Gate Library, resulting in the identification and inclusion of eleven papers in the review. The findings highlight that children under the age of five are more susceptible to malaria than adults, due to their still-developing immune systems. The highest rates of morbidity and mortality are seen in youngsters, pregnant women, and people with impaired immune systems, making age structure a critical factor in the spread of malaria within populations. Personal protection and vector control are key strategies in reducing the transmission of malaria in communities. The study also suggests that the use of fractional operators in modeling could offer new insights into the dynamics of malaria transmission and potential control strategies.

Energy-efficient and secure routing strategy for opportunistic data transmission in WSNs

ABSTRACT Driven by the critical importance of routing in Wireless Sensor Networks (WSNs) and the security vulnerabilities present in existing protocols, this research aims to address the key challenges in securing WSNs. Many current routing protocols focus on computational efficiency but fall short of providing strong security measures, leaving them vulnerable to malicious attacks. Reactive protocols, often preferred for their reduced bandwidth usage, heighten security concerns due to their limited resources for maintaining network routes, while proactive alternatives require more resources. Additionally, the ad hoc nature and energy limitations of WSNs make traditional security models, designed for wired and wireless networks, impractical. To overcome these limitations, this paper introduces the Secured Energy-Efficient Opportunistic Routing Scheme for sustainable WSNs. The proposed protocol is designed to enhance security by continuously updating neighbor information and verifying the validity of routing parameters, while also being power-aware, a critical factor given the energy constraints of WSNs. The protocol has been evaluated through simulation experiments, measuring key performance indicators such as throughput, average end-to-end delay (E2 delay), energy consumption, and network lifetime. The results demonstrate that the proposed protocol effectively strengthens WSN security while addressing the unique operational constraints of these networks.

Quantum PSO-Based Optimization of Secured IRS-Assisted Wireless-Powered IoT Networks

In this paper, we explore intelligent reflecting surface (IRS)-assisted physical layer security (PLS) in a wireless-powered Internet of Things (IoT) network (WPIN) by combining an IRS, a friendly jammer, and energy harvesting (EH) to maximize sum secrecy throughput in the WPIN. Specifically, we propose a non-line-of-sight system where a hybrid access point (H-AP) has no direct link with the users, and a secure uplink transmission scheme utilizes the jammer to combat malicious eavesdroppers. The proposed scheme consists of two stages: wireless energy transfer (WET) on the downlink (DL) and wireless information transmission (WIT) on the uplink (UL). In the first phase, the H-AP sends energy to users and the jammer, and they then harvest energy with the help of the IRS. Consequently, during WIT, the user transmits information to the H-AP while the jammer emits signals to confuse the eavesdropper without interfering with the legitimate transmission. The phase-shift matrix of the IRS and the time allocation for DL and UL are jointly optimized to maximize the sum secrecy throughput of the network. To tackle the non-convex problem, an alternating optimization method is employed, and the problem is reformulated into two sub-problems. First, the IRS phase shift is solved using quantum particle swarm optimization (QPSO). Then, the time allocation for DL and UL are optimized using the bisection method. Simulation results demonstrate that the proposed method achieves significant performance improvements as compared to other baseline schemes. Specifically, for IRS elements N = 35, the proposed scheme achieves a throughput of 19.4 bps/Hz, which is 85% higher than the standard PSO approach and 143% higher than the fixed time, random phase (8 bps/Hz) approach. These results validate the proposed approach’s effectiveness in improving network security and overall performance.

Exploring the Relationship Between Translators’ Styles and Translation Competence: A Case Study of English Translations of The True Story of Ah Q

This study investigates the relationship between Translators&amp;rsquo; Styles and Translation Competence (TC) by examining five English translations of The True Story of Ah Q. The five translators are George Kin Leung, Chi-Chen Wang, Yang Xianyi &amp;amp; Gladys_Yang, William Lyell, and Julia Lovell. Employing a mixed-method approach, the research utilises the Multidimensional Analysis Tagger (MAT) for quantitative analysis and the PACTE model framework for qualitative analysis. The key competencies of TC&amp;mdash;bilingual, extralinguistic, strategic sub-competence, and knowledge about translation&amp;mdash;are evaluated to understand their impact on stylistic choices in the translations. MAT&amp;rsquo;s quantitative analysis provides insights into the lexical density, syntactic complexity, and narrative techniques, while the qualitative analysis explores cultural transmission and rhetorical strategies used by the translators. The findings reveal significant variations in translator style, influenced by their competencies. Translators with higher bilingual and knowledge about translation demonstrate greater linguistic flexibility and accuracy, whereas strategic and extralinguistic sub-competence impact cultural adaptations and rhetorical fidelity. This research contributes to expanding the PACTE model&amp;rsquo;s application to literary translation, offering empirical support for how TC manifests in stylistic choices. The study highlights the value of combining quantitative and qualitative approaches to advance the understanding of translator style and competence in translation studies.

Energy-Efficient Cooperative Transmission in Ultra-Dense Millimeter-Wave Network: Multi-Agent Q-Learning Approach.

In beyond fifth-generation networks, millimeter wave (mmWave) is considered a promising technology that can offer high data rates. However, due to inter-cell interference at cell boundaries, it is difficult to achieve a high signal-to-interference-plus-noise ratio (SINR) among users in an ultra-dense mmWave network environment (UDmN). In this paper, we solve this problem with the cooperative transmission technique to provide high SINR to users. Using coordinated multi-point transmission (CoMP) with the joint transmission (JT) strategy as a cooperation diversity technique can provide users with higher data rates through multiple desired signals. Nonetheless, cooperative transmissions between multiple base stations (BSs) lead to increased energy consumption. Therefore, we propose a multi-agent Q-learning-based power control scheme in UDmN. To satisfy the quality of service (QoS) requirements of users and decrease the energy consumption of networks, we define a reward function while considering the outage and energy efficiency of each BS. The results show that our scheme can achieve optimal transmission power and significantly improved network energy efficiency compared with conventional algorithms such as no transmit power control and random control. Additionally, we validate that leveraging channel state information to determine the participation of each BS in power control contributes to enhanced overall performance.

Highly secure OFDM scheme based on multi-level masking and performance-enhanced key accompanying transmission.

In this Letter, we propose a highly secure OFDM scheme based on multi-level masking and performance-enhanced key-accompanying transmission. Our scheme exploits a four-dimensional hyperchaotic model and uses subcarriers and symbols to scramble the signal, thereby achieving chaotic encryption and enhancing system security. The dual-mode index technique is employed to conceal the key within the encrypted signal, enabling cooperative transmission of both the key and the signal. We conducted experiments that successfully transmitted a 28 Gb/s dual-mode QPSK (DM-QPSK) signal and a 42 Gb/s dual-mode 8QAM (DM-8QAM) signal over a 2-km stretch of 7-core fiber. The results demonstrated that our proposed key-accompanying transmission scheme did not compromise the system's transmission performance. Moreover, the key space of this scheme is as large as 10135, effectively ensuring system security. Under the received optical power corresponding to the bit error rate of 3.8 × 10-3, the minimum number of key repetitions in DM-8QAM that makes the key bit error rate zero is less than 9 times. This demonstrates that our proposed scheme effectively enhances the transmission performance of the key, achieving high-quality joint transmission of both the key and the signal.

A low-cost system for continuous dynamic monitoring and autonomous data analysis using the Internet of Things and Machine Learning

Structural health monitoring using the Internet of Things (IoT) is the latest tech-nique employed in the field of structural damage detection. Although conventional systems based on commercial sensors, such as piezoelectric accelerometers, pro-vide high accuracy, their high cost often limits their application. To address this is-sue, one possibility has been the development of strategies using low-cost sen-sors. However, there are several challenges to be addressed, such as the optimiza-tion of the low-cost devices to increase their reliability in reading and processing data, and the development of data storage and data transmission strategies, mainly for dynamic monitoring applications, which requires working with large amounts of data. In this regard, this paper presents the development of a low-cost SHM so-lution, which is able to collect, store, process and transmit vibration data to the cloud from an instrumented aluminum beam. For this purpose, a prototype is de-veloped using an ESP32 board, an MPU6050 triaxial accelerometer and a mi-croSD card. A completely low-cost system is adopted, where the data processing and availability of results to the final user is performed in the free version of ThingSpeak IoT platform from MathWorks. As a result, a fully automatic dynam-ic monitoring strategy able to collect, store and transmit raw vibration data to the cloud is developed. Then, the raw acceleration data is processed and analyzed in the cloud, where the Fast Fourier Transforms (FFT) are computed and visualized in quasi-real time.

A Secure Transmission Scheme With Efficient and Lightweight Group Key Generation for Underwater Acoustic Sensor Networks

A Secure Transmission Scheme With Efficient and Lightweight Group Key Generation for Underwater Acoustic Sensor Networks

Phase demodulation method for stable long-haul frequency transmission based on the Michelson interferometer.

In this Letter, we present a fiber-optic radio frequency (RF) transmission scheme based on phase modulation with an interferometric detection structure. A self-developed Michelson interferometer (MI) is used to demodulate the frequency signal via an electrically controlled optical shifter. The two complementary outputs from the interferometer are detected using a balanced detector, which suppresses the common-mode noise of the fiber link. The structure is tested in the laboratory using a frequency transfer system over a 560 km fiber link. Experimental results show that a stable 2.4 GHz frequency transmission with a fractional frequency instability of 3.9 × 10-14 at 1 s and 6.2 × 10-17 at 10,000 s is achieved. Compared with the frequency transmission system based on intensity modulation and direct detection, the frequency instability is improved from 7.3 × 10-14 to 3.9 × 10-14 at 1 s. We believe that the proposed method will be useful for the construction of time-frequency synchronous fiber networks.

Sub-1 GHz RF-based Energy-efficient Sensor Node for Secure Communication in Low-power IoT and Embedded Applications

Background: The Internet of Things (IoT) devices consist of a microcontroller unit for data processing, a low-power wireless radio module for data transmission, and various sensors for data collection. The sensor nodes and processing devices used in the Internet of Things are resource-constrained, with power consumption and security being the two most critical parameters. Objective: This paper addresses the challenges of power consumption and security in IoT scenarios. It presents a low-power and secure heterogeneous multicore sensing architecture designed for low-power IoT and wireless sensor networks. The architecture comprises a sensing and control subsystem, an information processing unit, and a wireless communication module. Methods: The architecture uses a microcontroller unit based on ARM Cortex M4, a low-power sub-1 GHz RF-compliant communication radio, and a few sensors. The proposed architecture has been implemented and tested using the Contiki Operating System. Results: The implemented sensor node architecture demonstrated performance efficiency, lower energy consumption, and higher security. Conclusion: By leveraging efficient power management, data transmission strategies, and cryptographic security, the architecture contributes to developing energy-efficient and secure IoT devices.

An efficient data transmission scheme for WSNs assisted by multiple UAVs

An efficient data transmission scheme for WSNs assisted by multiple UAVs

Ultrathin, Lightweight Materials Enabled Wireless Data and Power Transmission in Chip-Less Flexible Electronics.

The surge of flexible, biointegrated electronics has inspired continued research efforts in designing and developing chip-less and wireless devices as soft and mechanically compliant interfaces to the living systems. In recent years, innovations in materials, devices, and systems have been reported to address challenges surrounding this topic to empower their reliable operation for monitoring physiological signals. This perspective provides a brief overview of recent works reporting various chip-less electronics for sensing and actuation in diverse application scenarios. We summarize wireless signal/data/power transmission strategies, key considerations in materials design and selection, as well as successful demonstrations of sensors and actuators in wearable and implantable forms. The final section provides an outlook to the future direction down the road for performance improvement and optimization. These versatile, inexpensive, and low-power device concepts can serve as alternative strategies to existing digital wireless electronics, which will find broad applications as bidirectional biointerfaces in basic biomedical research and clinical practices.

Wheat streak mosaic virus: transmission, its impact, and crop protection strategies—a systematic review

Wheat streak mosaic virus: transmission, its impact, and crop protection strategies—a systematic review

Multi-Intelligent Reflecting Surfaces and Artificial Noise-Assisted Cell-Free Massive MIMO Against Simultaneous Jamming and Eavesdropping.

In a cell-free massive multiple-input multiple-output (MIMO) system without cells, it is assumed that there are smart jammers and disrupters (SJDs) that attempt to interfere with and eavesdrop on the downlink communications of legitimate users. A secure transmission scheme based on multiple intelligent reflecting surfaces (IRSs) and artificial noise (AN) is proposed. First, an access point (AP) selection strategy based on user location information is designed, which aims to determine the set of APs serving users. Then, a joint optimization framework based on the block coordinate descent (BCD) algorithm is constructed, and a non-convex optimization solution based on the univariate function optimization and semi-definite relaxation (SDR) is proposed with the aim of maximising the minimum achievable secrecy rate for users. By solving the univariate function maximisation problem, the multi-variable coupled non-convex problem is transformed into a solvable convex problem, obtaining the optimal AP beamforming, AN matrix and IRS phase shift matrix. Specifically, in a single-user scenario, the scheme of multiple intelligent reflecting surfaces combined with artificial noise can improve the user's achievable secrecy rate by about 11% compared to the existing method (single intelligent reflective surface combined with artificial noise) and about 2% compared to the scheme assisted by multiple intelligent reflecting surfaces without artificial noise assistance.