Transmission Power Levels Research Articles

Auto-induced uplink 4G and 5G RF-EMF exposure assessment using a network monitoring application in different microenvironments across seven European countries.

The auto-induced uplink (a-UL) radio-frequency electromagnetic field (RF-EMF), often the dominant part of the total RF-EMF exposure, has not been included in previous microenvironmental studies. As 5G exposure depends more on mobile phone usage, monitoring typical transmit power levels is crucial towards more accurate personal exposure assessment. This study describes spatial differences in average mobile phone transmit power and investigates the influence of uplink duty cycles and frequency band usage. A novel methodology using the network monitoring application QualiPoc in fourth-generation (4G) and non-standalone fifth-generation (5G) networks was presented. For the first time, the assessment of 4G and 5G a-UL RF-EMF exposure was conducted simultaneously in a large-scale microenvironmental study in Europe. Measurements were performed along predefined routes in 282 different microenvironments (e.g., parks, residential areas) across seven European countries, during a maximum uplink usage scenario. The Netherlands had the highest average transmit powers per microenvironment (median 20.6 dBm). Transmit powers in villages were 0.6 to 2.1 dB higher than in big cities. The study suggested that base station density is a key predictor of a-UL exposure. Comparing technologies and frequency bands, average transmit powers for 5G were about 3.3 dB lower than for 4G and lowest for frequency bands with a time division duplexing (TDD) scheme due to the low uplink duty cycle (below 20%). This study provides crucial measurement data for epidemiologists and governments to enhance the understanding of the a-UL component of personal RF-EMF exposure.

Enhancing monitoring systems with interference-handling radio frequency direction finding: BMKG C-Band weather radar in West Kalimantan Indonesia case study

This study investigates the effectiveness of the interference-handling radio frequency direction finding (RFDF) monitoring system in detecting and localizing interference sources near the BMKG C-Band weather radar in West Kalimantan, Indonesia. We conducted field tests varying interference transmitter power levels (0-30 dBm) and distances (100, 500, and 1,000 m) from the radar. Results indicate the RFDF system's robust performance, consistently detecting interference within 5-20 minutes and accurately localizing sources with minimal deviation from actual positions. The findings confirm the system's superiority over traditional manual methods, offering a reliable solution for interference management in weather radar operations. However, limitations include controlled test conditions and a need for further exploration of the system's efficacy in diverse environmental settings. This research contributes to improving radar reliability and lays the groundwork for future studies to refine RFDF technology for broader meteorological applications.

Water Quality Monitoring and Assessment System Along Tigris River in Mosul City

This paper aims to address the issue of water pollution in the Tigris River in Mosul city through continuous water quality monitoring. The proposed solution involves the use of LoRa-WAN wireless technology. Wireless sensor nodes would be placed at various stations along the river in Mosul, transmitting data to a LoRa gateway at the Nineveh Water Directorate. This gateway would then communicate with a server via a Cloud platform on the internet. The study utilized the OMNET++ program to simulate data transfer from sensor nodes to the LoRa gateway. Two main contributions are highlighted: an environmental contribution in providing data on water pollution levels and a technological contribution in utilizing the LoRa network for water quality monitoring. Thirteen parameters were measured at nine river stations. The sensor nodes will send notifications to the LoRa-WAN network if any parameter exceeds a predetermined value. The simulations analyzed the received signal strength indicator and packet delivery ratio with 117 sensor nodes managed by one LoRa gateway, covering a 20km area. The LoRa-WAN technology demonstrated satisfactory results in the simulated scenarios, improving network performance by studying the impact of increasing distance between sensor nodes and the gateway on RSSI values for different transmitting power levels (2-14 dBm).

Unmanned-Aerial-Vehicle-Assisted Secure Free Space Optical Transmission in Internet of Things: Intelligent Strategy for Optimal Fairness.

In this article, we consider an UAV (unmanned aerial vehicle)-assisted free space optical (FSO) secure communication network. Since FSO signal is impossible to detect by eavesdroppers without proper beam alignment and security authentication, a BS employs FSO technique to transfer information to multiple authenticated sensors, to improve the transmission security and reliability with the help of an UAV relay with decode and forward (DF) mode. All the sensors need to first send information to the UAV to obtain security authentication, and then the UAV forwards corresponding information to them. Successive interference cancellation (SIC) is used to decode the information received at the UAV and all authenticated sensors. With consideration of fairness, we introduce a statistical metric for evaluating the network performance, i.e., the maximum decoding outage probability for all authenticated sensors. In particular, applying an intelligent approach, we obtain a near-optimal scheme for secure transmit power allocation. With a well-trained allocation scheme, approximate closed-form expressions for optimal transmit power levels can be obtained. Through some numerical examples, we illustrate the various design trade-offs for such a system. Additionally, the validity of our approach was verified by comparing with the result from exhaustive search. In particular, the result with DRL was only 0.3% higher than that with exhaustive search. These results can provide some important guidelines for the fairness-aware design of UAV-assisted secure FSO communication networks.

Detection of Modulated Wave Transmission Failure in Aviation Communication Using IoT-Based RTL-SDR

Communication is a crucial component in aviation telecommunications services, where failures can lead to fatal incidents that may result in loss of life. According to Regulation No. 48 of 2017, aviation telecommunication service providers must be able to provide VHF A/G services with an availability value of 0.99999 and detect failures within two seconds. At Perum LPPNPI Yogyakarta, the VHF A/G equipment is located in a transmitter building 760 meters away from the Technician Standby Building. This distance makes it difficult for technicians to directly monitor the equipment's condition, leading to failures being identified based on reports from air traffic controllers. Therefore, the author designed an IoT-based RTL-SDR system to directly monitor equipment conditions based on the modulated waves transmitted. This design employs the ADDIE method in its development. The system operates by measuring the transmission power and audio level of the modulated waves. Based on research conducted at frequencies 120.2 MHz, 125 MHz, 126.7 MHz, 127 MHz, 129.5 MHz, 130 MHz, 132.5 MHz, 133.2 MHz, 134 MHz, and 135 MHz, this design can detect equipment failures based on the received modulated waves with highest and lowest deviation while measuring transmission power are 2.24 dB and 0.4 dB.

A switched full duplex MIMO architecture with digital linear and nonlinear cancellation

Enabling full duplex (FD) in MIMO systems is challenging due to increased hardware complexity and increased training overhead required for canceling not only self-interference (SI) but also cross-link-interference (CLI) signals, considering both linear and nonlinear effects on each stream. In this paper, we propose switched FD MIMO (FD-SW-MIMO) architecture as a low-complexity, low-overhead solution, which enables stream-based nonlinear estimation to be performed independently from channel estimation, so that those nonlinear reference signals are fed to linear SI and CLI cancellation stages. For improved performance at high transmit power levels, the Random Fourier Features - Least Mean Squares (RFF-LMS) algorithm is employed on the residual SI and CLI signals per stream. Our experiments conducted on a software-defined radio based 2x2 FD MIMO test setup reveal that the proposed FD-SW-MIMO architecture can provide up to 12 dB enhancement over linear only digital cancellation. The proposed architecture requires only minor hardware modification(s), avoiding active analog cancellation circuitry and extra Tx/Rx chains. Requiring the same training overhead as linear only cancellation, FD-SW-MIMO architecture can quadruple the rate of HD SISO for low to moderate transmit power levels, and for high transmit power levels, the HD SISO rate is tripled due to slightly increased overhead.

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.