Transmission Power Levels Research Articles

Blockchain-enabled cooperative spectrum sensing in 5G and B5G cognitive radio via massive multiple-input multiple-output nonorthogonal multiple access

One of the greatest ways to guarantee that networks designed for fifth generation (5G) and beyond reach the required levels of spectrum efficiency (SE) is through nonorthogonal multiple access (NOMA). This work presents two new blockchain-based techniques that take advantage of massive multiple input multiple output in a single-cell network to improve performance. NOMA power domain is used in the 5G cooperative cognitive radio network (CCRN) to improve the SE of the downlink. This study investigates a novel cooperative NOMA-based CCRN for underlay spectrum sharing. A cooperative NOMA technique is proposed by considering the access modes of relays and secondary users (SUs) on the secondary network. The proposed system's performance is assessed with respect to random channel characteristics, frequency-selective Rayleigh fading and perfect successive interference cancellation (SIC). The first signal decoded by SU identifies the relay states with the best channel quality between users and the destination users to offset the bit error rate. The throughput dropped during the period because of the perfect SIC. The precise closed-form expressions for the system throughput of the secondary network are derived under the interference constraint of the primary network to evaluate the efficacy of the suggested cooperative strategy. The suggested approaches are assessed under various conditions using the MATLAB application by considering varying transmit power levels, power location coefficients and lengths. In every case, four users are assumed to be using a 90 MHz bandwidth and M-ary Quadrature Amplitude Modulation technology.

Distributed clustering model for energy efficiency based topology control using game theory in wireless sensor networks

In this study, we use a topology control technique to tackle the issue of energy balance and consumption minimization in wireless sensor networks. By maintaining network connection while sensibly adjusting the transmission power level, such an algorithm may reduce and balance energy usage. This study provides an energy welfare topological control using a game-theoretic approach by calculating energy welfare as usefulness metric for energy populations using the welfare function from the social sciences. Energy balance occurs when every node works to improve its local society's energy situation to the best of its ability. We demonstrate that the consequence ant game is an intriguing game with a single Nash equilibrium that is Pareto optimum. According to economic theory, Pareto optimality is a situation in which improving one person's circumstances would always make another person's worse off. We demonstrate our suggested methodology's superiority in establishing energy balance and efficiency in wireless sensor networks by contrasting the simulation results of our algorithm with those of other approaches. Our approach surpasses existing methods by a wide margin. For reliable and long-lasting wireless sensor applications, this study offers insightful information about how to maximize network performance while preserving energy resources.

Разработка ВТСП кабельных линий для систем вывода мощности от источников генерации и протяженных линий передачи энергии

The article discusses general approaches to the development of HTS cable lines for long energy transmission lines and power output systems from generation sources, as part of a new technological structure of the energy industry. The use of the superconductivity effect makes it possible to achieve power transmission levels of 0.5-2.0 GVA or more without significantly increasing weight and size characteristics while simultaneously reducing energy losses. The results of theoretical estimates are presented, showing the possibility of reducing energy losses to a level of no more than 3% of the transmitted power and creating HTS power transmission lines up to 100 km long. It is shown that the accumulated experience makes it possible to start implementing pilot projects using superconducting cable lines, however, such developments will require taking into account many factors, including infrastructural technical and economic aspects.

Optimal Decoding Order and Power Allocation for Sum Throughput Maximization in Downlink NOMA Systems.

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) system over Nakagami-m channels. The single-antenna base station serves two single-antenna NOMA users based on statistical channel state information (CSI). We derive the closed-form expression of the exact outage probability under a given decoding order, and we also deduce the asymptotic outage probability and diversity order in a high-SNR regime. Then, we analyze all the possible power allocation ranges and theoretically prove the optimal power allocation range under the corresponding decoding order. The demarcation points of the optimal power allocation ranges are affected by target data rates and total power, without an effect from the CSI. In particular, the values of the demarcation points are proportional to the total power. Furthermore, we formulate a joint decoding order and power allocation optimization problem to maximize the sum throughput, which is solved by efficiently searching in our obtained optimal power allocation ranges. Finally, Monte Carlo simulations are conducted to confirm the accuracy of our derived exact outage probability. Numerical results show the accuracy of our deduced demarcation points of the optimal power allocation ranges. And the optimal decoding order is not constant at different total transmit power levels.

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Efficient Connectivity in Smart Homes: Enhancing Living Comfort through IoT Infrastructure.

Modern homes are experiencing unprecedented levels of convenience because of the proliferation of smart devices. In order to improve communication between smart home devices, this paper presents a novel approach that particularly addresses interference caused by different transmission systems. The core of the suggested framework is an intelligent Internet of Things (IoT) system designed to reduce interference. By using adaptive communication protocols and sophisticated interference management algorithms, the framework minimizes interference caused by overlapping transmissions and guarantees effective data sharing. This can be accomplished by creating an optimization model that takes into account the dynamic nature of the smart home environment and intelligently allocates resources. By maximizing the signal quality at the destination and optimizing the distribution of frequency channels and transmission power levels, the model seeks to minimize interference. A deep learning technique is used to augment the optimization model by adaptively learning and predicting interference patterns from real-time observations and historical data. The experimental results show how effective the suggested hybrid strategy is. While the deep learning model adjusts to shifting interference dynamics, the optimization model efficiently controls resource allocation, leading to better data reception performance at the destination. The system's robustness is assessed in various kinds of situations to demonstrate its flexibility in responding to changing smart home settings. This work not only offers a thorough framework for interference reduction but also clarifies how deep learning and mathematical optimization can work together to improve the dependability of data reception in smart homes.

ACTOR: Adaptive Control of Transmission Power in RPL.

RPL-Routing Protocol for Low-Power and Lossy Networks (usually pronounced "ripple")-is the de facto standard for IoT networks. However, it neglects to exploit IoT devices' full capacity to optimize their transmission power, mainly because it is quite challenging to do so in parallel with the routing strategy, given the dynamic nature of wireless links and the typically constrained resources of IoT devices. Adapting the transmission power requires dynamically assessing many parameters, such as the probability of packet collisions, energy consumption, the number of hops, and interference. This paper introduces Adaptive Control of Transmission Power for RPL (ACTOR) for the dynamic optimization of transmission power. ACTOR aims to improve throughput in dense networks by passively exploring different transmission power levels. The classic solutions of bandit theory, including the Upper Confidence Bound (UCB) and Discounted UCB, accelerate the convergence of the exploration and guarantee its optimality. ACTOR is also enhanced via mechanisms to blacklist undesirable transmission power levels and stabilize the topology of parent-child negotiations. The results of the experiments conducted on our 40-node, 12-node testbed demonstrate that ACTOR achieves a higher packet delivery ratio by almost 20%, reduces the transmission power of nodes by up to 10 dBm, and maintains a stable topology with significantly fewer parent switches compared to the standard RPL and the selected benchmarks. These findings are consistent with simulations conducted across 7 different scenarios, where improvements in end-to-end delay, packet delivery, and energy consumption were observed by up to 50%.

Cooperative Study for Power Spectral Towards Different Sizes Taper Optical Microfiber for Sensing Purpose

Optical fibre, also referred to as fibre optics, is a method and medium of transmitting data using bursts of light through strands of glass or plastic. When light signals travel through fibre optic cables, they bounce off the core and cladding in a series of zigzag bounces, which is a phenomenon known as total internal reflection. Microfiber optic sensors have recently gained considerable attention due to their high sensitivity, quick detection, and adaptability to harsh environments. To produce microfibers in various diameters, a tapering technique is used. However, the sensor's performance may vary depending on the transmitted power levels produced by the different taper microfiber sizes. Several diameters of taper microfiber will be used as sensors to determine the sensing performance. The results indicate that the best performing sensors are those with smallest diameters.

RANCANG BANGUN PURWARUPA SISTEM KOMUNIKASI ANTAR KENDARAAN MENGGUNAKAN NRF24L01 MODE SIMPLEX

This research aims to design and develop a prototype vehicle-to-vehicle (V2V) communication system utilizing the NRF24L01 module, ESP32 microcontroller, and OLED display in simplex mode. The system enables effective and instant communication between vehicles in the Vehicle Ad-Hoc Networks (VANETs) environment. In the implementation, we optimized the power transmission level and data rate to ensure fast and responsive data transmission. We integrated key components, such as the ESP32, NRF24L01, and OLED display, into the hardware design to establish a reliable and seamlessly integrated system. We also designed the prototype to minimize costs. The prototype demonstrates an effective and cost-efficient technical solution for vehicle communication, making it suitable for research and development projects requiring wireless communication in real-world vehicle scenarios. This research aims to positively contribute to advancing technology to support connectivity and safety in future vehicle mobility. The findings of this research can be beneficial for researchers, engineers, and policymakers interested in improving vehicular communication and mobility.

Optimizing High Data Rate Up to 2.5 Tbps Transmission using 64-Channel DWDM System with DCF and NRZ Modulation

Objectives: This study aims to enhance and optimize a modern communication system for high data rate transmission using Dense Wavelength Division Multiplexing (DWDM). The objectives include employing a 64-channel DWDM system, implementing different data speeds, and utilizing a dispersion compensation method. Methods: To achieve the objectives, we simulate and analyze the effects of Dispersion Compensation Fiber (DCF) in a DWDM system with 64 channels. The system employs Non-Return-to-Zero (NRZ) modulation format at varied bit rates and multiple energy levels. We propose a method for achieving data rates of 10 to 40 Gbps using NRZ modulation and Erbium-Doped Fiber Amplifier (EDFA) over a single-mode fiber transmission distance of 40 to 160 km, along with a dispersion compensation fiber of 8 to 32 km (DCF). The performance of the developed model is evaluated based on Quality Factor, Bit Error Rate (BER), Eye Height, and Threshold. These metrics are measured at two input energy levels from an optical power source, covering a communication capacity ranging from 0.625 Tbps to 2.5 Tbps. Findings: Through the simulations and analyses, we uncover the impact of dispersion and demonstrate the effectiveness of the proposed method in compensating for dispersion effects. Performance analysis of two different input transmitter power levels, -10 dBm is more efficient compared to 0 dBm input transmitter power in terms of bit error rate and quality factor. Novelty: This study presents a novel approach to improving modern communication systems by utilizing DWDM with a dispersion compensation method. The use of a 64-channel DWDM system, combined with the proposed NRZ modulation technique and dispersion compensation fiber, provides an efficient solution for achieving high data rates over long transmission distances while minimizing the effects of dispersion. The findings contribute to the advancement of communication systems for high data rate transmission. Keywords Dispersion effect, Bit Error Rate, Q-factor, Optisystem software, Erbium doped fiber amplifier

An Improved Interference Mitigation Scheme for Femtocell Networks

Femtocell networks have gained significant attention in recent years due to their ability to improve indoor wireless coverage and capacity. However, they are susceptible to interference from neighboring cells, which significantly degrade their performance and quality of service to the end-user. The study introduced an adaptive power control technique that causes the power level of the femtocell base station to adjust dynamically to reduce the interference caused by adjacent femtocell networks, thereby adjusting the system bandwidth, carrier frequency, path loss and femtocell Base Station (BS) transmission power based on the request made by the users. The interference mitigation scheme was optimized by tuning the parameters of the power control algorithm, such as the transmit power levels and the interference thresholds. The algorithm was simulated with MATLAB simulation tools. Throughput, Signal to Interference Noise Ratio (SINR), coverage enhancement and user satisfaction were used as measurement metrics for the model using descriptive statistics. The results showed that the average performance obtained for the throughput increased by 25.88% from 3.40 X 1010 (bps) to 4.28 X 1010 (bps), and the SINR increased by 35.29% from 1.70 X 109 dB to 2.30 X109 dB for the benchmarked power control and improved power control techniques respectively. Coverage enhancement and user satisfaction were nearly 0, which indicates that the technique was of average performance. This study concluded that the new scheme enhances wider coverage to reach more users and mitigate interference while maintaining a higher level of femtocell user satisfaction.

Displacement Estimation via 3D-Printed RFID Sensors for Structural Health Monitoring: Leveraging Machine Learning and Photoluminescence to Overcome Data Gaps.

Monitoring object displacement is critical for structural health monitoring (SHM). Radio frequency identification (RFID) sensors can be used for this purpose. Using more sensors enhances displacement estimation accuracy, especially when it is realized through the use of machine learning (ML) algorithms for predicting the direction of arrival of the associated signals. Our research shows that ML algorithms, in conjunction with adequate RFID passive sensor data, can precisely evaluate azimuth angles. However, increasing the number of sensors can lead to gaps in the data, which typical numerical methods such as interpolation and imputation may not fully resolve. To overcome this challenge, we propose enhancing the sensitivity of 3D-printed passive RFID sensor arrays using a novel photoluminescence-based RF signal enhancement technique. This can boost received RF signal levels by 2 dB to 8 dB, depending on the propagation mode (near-field or far-field). Hence, it effectively mitigates the issue of missing data without necessitating changes in transmit power levels or the number of sensors. This approach, which enables remote shaping of radiation patterns via light, can herald new prospects in the development of smart antennas for various applications apart from SHM, such as biomedicine and aerospace.

Optimal D2D power for secure D2D communication with random eavesdropper in 5G‐IoT networks

SummaryIn the rapidly evolving landscape of fifth generation Internet of Things (5G‐IoT) networks, Device‐to‐Device (D2D) communication has emerged as a promising paradigm to enhance secrecy transmission rate (STR) and connectivity. However, the security of D2D communications in the presence of eavesdroppers remains a critical challenge. This article investigates the problem of optimizing D2D transmit power to achieve secure D2D communication while considering the presence of random eavesdroppers in 5G‐IoT networks. We propose a novel secrecy‐based power control approach (SRMWPCA) approach to model the random distribution of eavesdroppers in the network, taking into account their varying distances from D2D pairs and deliberately increasing interference at the eavesdropper's link. By leveraging tools from stochastic geometry, we derive an analytical expression for the secrecy transmission probability (STP), which quantifies the probability of eavesdroppers successfully decoding the D2D transmission. In this analysis, we have incorporated practical considerations such as channel fading, path loss, and interference from other devices. To enhance the security of D2D communication, we formulate an optimization problem to determine the optimal transmit power levels for D2D pairs, subject to constraints on the secrecy transmission probability and interference to the cellular network. We propose an efficient algorithm to find the power allocation that maximizes the secrecy outage performance while meeting these constraints. Simulation results demonstrate the effectiveness of the proposed approach in achieving secure D2D communication in 5G‐IoT networks with random eavesdroppers. The performance of the proposed SRMWPCA approach improved by 23.25% and 20.9% compared with standard approaches in terms of the secrecy rate and throughput of the users from malicious attacks.

Evaluation of energy consumption of LPWAN technologies

The majority of IoT implementations demand sensor nodes to run reliably for an extended time. Furthermore, the radio settings can endure a high data rate transmission while optimizing the energy-efficiency. The LoRa/LoRaWAN is one of the primary low-power wide area network (LPWAN) technologies that has highly enticed much concentration. The energy limits is a significant issue in wireless sensor networks since battery lifetime that supplies sensor nodes have a restricted amount of energy and neither expendable nor rechargeable in most cases. A common hypothesis is that the energy consumed by sensors in sleep mode is negligible. With this hypothesis, the usual approach is to consider subsets of nodes that reach all the iterative targets. These subsets also called coverage sets, are then put in the active mode, considering the others are in the low-power or sleep mode. In this paper, we address this question by proposing an energy consumption model based on LoRa and LoRaWAN, which optimizes the energy consumption of the sensor node for different tasks for a period of time. Our energy consumption model assumes the following, the processing unit is in on-state along the working sequence which enhances the MCU unit by constructing it in low-power modes through most of the activity cycle, a constant time duration, and the radio module sends a packet of data at a specified transmission power level. The proposed analytical approach permits considering the consumed power of every sensor node element where the numerical results show that the scenario in which the sensor node transfers data to the gateway then receives an acknowledgment RX2 without receiving RX1 consumes the most energy; furthermore, it can be used to analyze different LoRaWAN modes to determine the most desirable sensor node design to reach its energy autonomy where the numerical results detail the impact of scenario, spreading factor, and bandwidth on power consumption.

An analysis of wireless signal propagation in collapsed mine scenarios

The missing miner problem arises when a miner working in an underground mine gets trapped after a mine collapse. The ability to precisely locate a missing miner is directly linked with the availability of a communication infrastructure which can allow communication with the trapped miner. Conventional communication systems commonly used in the mines are generally unable to communicate with the miners after mine collapse due to either their limitations or damage because of the collapse. A better understanding of the wireless signal propagation in collapsed mine scenarios can help in the design of robust systems which can provide connectivity even after a mine collapse. This paper analyzes wireless channel in different collapsed mine scenarios using both simulations and real experiments in a mock mine. No such study exists to the best knowledge of the authors. Finally, suitable transmit power levels that can be used in such scenarios are also determined.

Impact Assessment of Elevation Angles on Signal Propagation at VHF and UHF Frequencies for Improved Rural Telephony

Rural telephony is challenging in the remote part of Nigeria due to inadequate telecommunication infrastructure, exorbitant cost of communication systems and poor road network for extension of fiber network. These factors constitute poor or no cellular network services in many villages. Alternatively, using Television White Space (TVWS) technology to facilitate telephony services in the rural areas through Ultra High Frequency (UHF) and Very High Frequency (VHF) spectrum is cost effective. Thus, this research investigates impact of elevation angle on signal propagation at UHF/VHF frequencies. The experimental test scenarios took measurements of received signal quality performance at different elevation angles and transmit power levels to obtain more stable results for substantive inference. The experimental test scenario considered a communication link, operating at UHF frequency of 436 MHz. During the experiment, azimuth and propagation loss for the communication link were kept constant while the receiving antenna elevation angles were varied to assess the impact of elevation angles. The assessment examined results obtained during the experiment. Comparing the received signal quality performance at zero (00) elevation angle, it has been observed that the received signal quality improves when the transmit power allocation increases. Results further show that for a given transmit power level of 34dBm, at zero (00) elevation angle test configuration, received signal quality performance of 1.80 dB, 6.90 dB at 300 elevation angle and 10.9 dB at 600 elevation angle were obtained, compared to improved quality performance of 11.8 dB at 00 elevation angle, 19.90 dB at 300 elevation angle and 24.92 dB at 600 elevation angle when the transmit power level was increased to 46.98 dBm. It is deduced from the experimental results that elevation angle of receiving antenna has significant influence on the received signal quality performance. This insight is very useful in the design and network planning of rural telecommunication services using TVWS frequencies for improved rural broadband penetration.

Energy-efficient underwater acoustic communication based on Dyna-Q with an adaptive action space

The underwater acoustic (UWA) channel exhibits large spatial–temporal dynamics. This work focuses on adapting the transmission power to the channel condition to achieve energy efficiency in UWA communications. To tackle the unknown channel variation, a reinforcement learning (RL) algorithm called Dyna-Q is introduced. Consider the continuous variation of UWA channels. Instead of using a fixed action space in the Dyna-Q, an adaptive action space with an updated Q-value iteration is proposed in this work. The switching of the transmission power level occurs on a block-by-block basis during transmission, aiming to maximize the system’s long-term energy efficiency performance. Using the widely-used communication technique, Orthogonal Frequency-Division Multiplexing (OFDM), as an example, both simulations and experimental data processing results demonstrate that the proposed method outperforms two comparative methods, including the original Dyna-Q with fixed action spaces.

Using Randomization in Self-organized Synchronization for Wireless Networks

The concept of pulse-coupled oscillators for self-organized synchronization has been applied to wireless systems. Putting theory into practice, however, faces certain obstacles, particularly in radio technologies that cannot implement pulses but use common messages for interactions between nodes. This raises the question of how to deal with interference between messages. We show that interference can disturb the synchronization process and propose low-complex, randomization-based techniques to address this issue. First, we demonstrate that randomly switching between two transmit power levels (without increasing the average power) can expedite synchronization. The high-power transmissions temporarily boost network connectivity with negligible impact on the average interference. Second, we reduce interference by blindly distributing the messages over the entire oscillator cycle. Instead of using a fixed oscillator phase at which the pulses are sent, each node chooses its own, randomly selected phase to send a synchronization message. This node-specific “fire phase” is contained in the message to permit others to compute the timing. Third, we suggest that such interference management can also be beneficial for other synchronization techniques and validate this claim using Glossy as an example. Our insights may contribute to feasible solutions for self-organized wireless synchronization. Further work is needed to gain a comprehensive understanding of the effects of randomization and to develop algorithms for the adaptability of local parameters.

Energy efficiency maximization for UAV-enabled amplify-and-forward relaying via joint power and trajectory optimization

This paper investigates an optimization problem corresponding to energy efficiency maximization of an unmanned aerial vehicle (UAV)-enabled relaying system, where a fixed-wing UAV acts as an amplify-and-forward mobile relay to assist data transmission between a source node and a destination node. On the premise of satisfying the speed and acceleration constraints of the UAV, the energy efficiency (EE) of the relaying system is maximized by jointly optimizing the UAV’s trajectory and the individual transmit power levels of the source and the UAV relay. The initial joint optimization problem is non-convex and cannot be solved directly. Therefore, the joint optimization problem is decomposed into two sub-problems which are solved by applying the successive convex approximation technique and the Dinkelbach’s algorithm. On this basis, an efficient iterative algorithm is proposed to tackle the joint optimization problem through the block coordinate descent technique. Simulation results demonstrated that by conducting the proposed algorithm, the flight trajectory of the UAV and the individual transmit power levels of the nodes can be flexibly adjusted according to the system conditions, and the proposed algorithm contributes to the higher EE compared with the benchmark schemes.

Energy‐efficient power control and altitude planning for UAV‐based vehicular communications in 5G NR‐V2X networks

AbstractUnmanned aerial vehicles (UAVs) are becoming increasingly popular in various industries, including telecommunications. In the realm of 5G new radio vehicle‐to‐everything (NR‐V2X) networks, UAVs can be used as mobile base stations (UAV‐BS) to provide vehicular communications. However, effective power control and altitude planning algorithms are required to maximize the energy efficiency (EE) of these UAV‐BS systems. In this article, we propose an energy‐efficient power control and altitude planning algorithm for UAV‐BS in NR‐V2X networks. We formulate the optimization problem of maximizing the system's EE while considering the reliability requirements of vehicular users, the limitations of UAV‐BS hovering altitude, and the feasibility of transmission power levels. The problem is nonconvex, and we address this by reformulating it into a convex problem using the Dinkelbach and alternating optimization methods. The simulation results demonstrate that the proposed algorithm closely achieves the performance of exhaustive search while it is more computationally efficient. Moreover, our algorithm by jointly optimizing transmission power and hovering altitude performs better than other schemes proposed in the literature, as shown through our simulation results.