Path Loss Model Research Articles

Machine-Learning-Based Combined Path Loss and Shadowing Model in LoRaWAN for Energy Efficiency Enhancement

Many practical Internet of Things (IoT) applications require deploying End Nodes (ENs) in hard-to-access places where replacing batteries is difficult or impossible. As a result, the ENs demand high energy efficiency. Long Range Wide Area Network (LoRaWAN) is an IoT protocol that aims to achieve low energy consumption. However, the energy consumption in LoRaWAN is related to transmission power, which can be set mainly based on path loss and shadow fading modeling and link budget analysis. Hence, appropriately setting this transmission power parameter saves energy and guarantees reliable communication links. Traditional path loss and shadow fading modeling and transmission power setting do not consider the variations caused by different environmental effects. In this work, we show via real-life data analysis that path loss and shadow fading depend on environmental variables. We propose Machine Learning models to calculate the empirical path loss and shadow fading, which is used to set the transmission power to save ENs’ energy. Our models include the effects of distance, frequency, temperature, relative humidity, barometric pressure, particulate matter, and Signal to Noise Ratio. Specifically, the models are based on Multiple Linear Regression, Support Vector Regression, Random Forests, and Artificial Neural Networks, exhibiting a Root Mean Square Error (RMSE) up to 1.566 dB and R up to 0.94. For energy saving, the developed models serve to set the transmission power and Spreading Factor based on the Adaptative Data Rate (ADR) algorithm principles, which reduces the link margin saving energy up to 43% compared with the traditional ADR protocol.

Path Loss and Auxiliary Communication Analysis of VANET in Tunnel Environments

Vehicular ad hoc network (VANET) communications face severe fading problems due to the signal reflections and diffractions within tunnels. Unlike the open road, the space of a tunnel is very limited, so VANET communication performance in a tunnel is seriously affected. In the process of signal transmission, the reflected signal is symmetrical with the incident signal after it is reflected by the road and the wall. In this paper, we establish a mathematical model of path loss for V2V (Vehicle-to-Vehicle) communication based on the principle of signal reflection symmetry in tunnels and considering several factors, such as the tunnel surface and the color of the tunnel wall. In addition, we use cooperative communication to form a virtual multiple-input multiple-output (V-MIMO) system, to improve the communication quality in tunnels. In the proposed system, the OBU (On-Board-unit) and RSU (Road-Side-Unit) share each other’s antennas, so that wireless cooperative communication can be employed, without increasing the number of antennas in a one-way tunnel. Therefore, this multipath fading internal electromagnetic wave propagation model can be used to improve performance. A deep reinforcement learning algorithm was used to solve the pairing problem to obtain a more accurate OBU and RSU pair, to form a V-MIMO system. Here, the RSU is regarded as an agent and interacts with the OBU in the tunnel. The optimal strategy was learned in a real-time changing simulation environment, and the experiment verified the convergence of the algorithm. The simulation results showed that, compared with the Q-learning based scheme, the optimal matching algorithm based on V-MIMO and a DQN (Deep Q-network) could effectively reduce the probability of transmission outages and improve the communication efficiency in tunnels.

Performance analysis of mmWave radio propagations in an indoor environment for 5G networks

Existing wireless communications in the sub-6 GHz bands are facing challenges from the growing demand for higher data rates and better quality of services. To satisfy these demands, the fifth generation (5G) mobile network would consider unused spectrum in the millimeter wave (mmWave) spectrum (30–300 GHz). The shortage of bandwidth in the sub-6 GHz band is solved using mmWave technology. Furthermore, mmWave provides significantly higher throughput, data rate, and capacity. Despite the fact that a huge bandwidth is employed, mmWave technology suffers from diffuse scattering from rough materials, path loss, reflection loss, atmospheric attenuation, building penetration loss, and shadowing which leads to a decrease in the transmitted signal power. Therefore, a reliable and accurate channel model is important in the mmWave bands, particularly for the indoor environment. Moreover, by using technologies like beam-forming and others coupled with mmWave, the listed impairments are minimized. In this work, we analyze the performance of different path loss models (CI, free space, and two rays) at 38, 60, and 73 GHz carrier frequencies in terms of path loss in terms of separation distance between transmitter and receiver. Additionally, we have evaluated the performance of the path loss with respect to the break point distance to enhance the received signal power and throughput. We have also done analysis of the directional power delay profile with received signal power, path loss and path loss exponent (PLE) at 38 GHz and 73 GHz mmWave bands for both LOS and NLOS by using uniform linear array (ULA) 2 × 2 and 64 × 16 antenna configurations using the channel model simulator (NYUSIM). The simulation results show the performance of different path loss models in the mmWave and sub 6 GHz bands. Path loss in the close-in (CI) model at mmWave bands is larger than that of free space and two ray path loss models, because it considers all shadowing and reflection effects between transmitter and receiver.

NSGA-III Based Heterogeneous Transmission Range Selection for Node Deployment in IEEE 802.15.4 Infrastructure for Sugarcane and Rice Crop Monitoring in a Humid Sub-Tropical Region

In this proposal, the impact of dynamic farm environment due to varying vegetation density on the Received Signal Strength (RSS), coverage and energy consumption of an IoT assisted Wireless Sensor Network (IoWSN) is analyzed through measurement campaign. Experimental observations on free-space and tree Path Loss Model (PLM) based sensor node deployment strategies in a cropping period have shown network disconnectivity due to incorrect assessment of excess attenuation caused by dynamically varying vegetation height and density during the monitoring period. To address the challenge, an empirically formulated PLM is proposed to estimate the excess attenuation at different crop development stages of medium grass vegetation. Further, using the formulated PLM, a Non-dominated Sorting Genetic Algorithm (NSGA-III) multi-objective optimization is performed to generate initial node deployment with a heterogeneous transmission range. To address the issue of over-coverage, transmitter output power scheduling is performed with predefined upper limit derived from the NSGA-III optimization. The output power is dynamically scheduled during the monitoring period based on changes in the captured RSS to minimize over-coverage. Improvements in coverage, connectivity, and energy efficiency compared to existing approaches are validated through Proof of Concept.

Pathloss and Airframe Shadowing Loss of Air-to-Ground UAV Channel in the Airport Area at UHF- and L-Band

In air-to-ground unmanned aerial vehicle (UAV) communications, an accurate channel propagation model is very important for the evaluation and design of communication systems. For this purpose, we have conducted several channel measurement campaigns in the airport area at UHF- and L-band (around 433 MHz and 1.518 GHz). In the line-of-sight (LoS) case, we give the distance-dependent pathloss models for both frequenciy bands. Meanwhile, it is found that the measured pathloss in the LoS scenario has a good agreement with the two-ray propagation model at short link distances. This is because of the strong ground reflection path. In the non-LoS (NLoS) case, we propose the elevation-dependent pathloss model at UHF-band based on the field measurement results. On the other hand, considering that the airframe of the UAV can block the wave propagation during the 3-D rotation in the air and the taking off and landing procedures, we specifically analyze the statistical characteristics of the airframe shadowing loss for the two cases and provide the loss distribution models for the fixed-wing, small-sized UAVs made of wood structure and carbon fiber skins.

Correction to “A Simple Analytical Model for THz Band Path Loss”

In the above article <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , an analytical model for THz band transmittance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\tau $ </tex-math></inline-formula> ) is devised as the joint function of distance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> ), altitude ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$h$ </tex-math></inline-formula> ), and frequency ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$f$ </tex-math></inline-formula> ). In <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , the last paragraph of Section II should be corrected as follows, also replacing <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1, eq. (6)]</xref> with <xref ref-type="disp-formula" rid="deqn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(1)</xref> .

Analytical Comparison of Path Loss Models for Radio Wave Propagation over Yenagoa–Southern Nigeria

Using propagation models helps with communication system planning and maximizes the use of the radio spectrum, a limited natural resource. Here is a comparative analysis between some propagation models and actual measurements from Yenagoa, Southern Nigeria. Electric field strength measurements made during drive tests for two television transmitters operating at 210.25 MHz and 577.10 MHz make up the experimental data. Analytical comparisons were made between verified predictions for the free space, Okumura, and Hata models and measured data. The results demonstrate that these empirical models fail to take into account Yenagoa's actual terrain profile for television broadcast. The Okumura model is the best fit, with ideal values for root mean square error (RMSE) of 34.9136 and 33.2841 and average relative error of 0.13212 and 0.4327 for 210.25 MHz and 577.10 MHz, respectively. However, if the Okumura model is tailored for Yenagoa to improve electric field strength prediction and coverage estimation, better results can be attained.

Path loss modeling and performance evaluation of double IRSs-aided wireless communication systems based on spatial scattering channel model

Intelligent reflecting surface (IRS) is a key enabling technology to reshape the electromagnetic propagation environment and enhance the communication performance. Current single IRS-aided or multiple distributed IRSs-aided wireless communication systems leave inter-IRSs collaboration out of consideration, and as a result, the system performance may be severely restricted. For cooperative double IRSs-aided wireless communication systems, dyadic backscatter channel model is widely used in the performance analysis and optimization. However, the impact of factors such as the size and gain of IRS elements is omitted. As a result, the performance quantification and evaluation are inaccurate. In order to avoid the above limitations, spatial scattering channel model is leveraged to quantify the path loss of the double reflection link in typical application scenarios of double IRSs-aided wireless communication systems. When the near-field condition is satisfied, the electromagnetic wave signal transmitted between IRSs is a spherical wave, which leads to high-rank channel and a lower signal to noise ratio. This paper considers the rank-1 inter-IRSs equivalent channel and derives the closed-form received signal power which reveals its relationship with the deployment of IRSs and the physical and electromagnetic properties of IRSs. Taking the impact of near/far-field effects of IRS on signal propagation further into consideration, the network configurations under which double cooperative IRSs can enhance the system performance are recognized. Simulation results show that whether double IRSs should be selected to assist in the communication between the transmitter and the receiver depends on practical network configurations, and the same number of elements should be assigned to the two IRSs to maximize the system performance if they are adopted.

A Proposed V2V Path Loss Model: Log-Ray

A Proposed V2V Path Loss Model: Log-Ray

Dynamic V2V Channel Measurement and Modeling at Street Intersection Scenarios

Vehicular communication has been widely concerned by academia and industry. Wireless channel characterization and modeling are the foundation of communication systems. Compared with typical road scenarios such as urban and suburban areas, wireless channel characterization in intersections is a challenging task. In this paper, channel measurements at 5.9 GHz in street intersection scenarios are carried out and provide data for the characterization and modeling of time-varying vehicular channels. This paper proposes a double-slope path loss model, which can accurately reflect the signal propagation loss at intersections. Further, the time-varying spatial characteristics of multipath are extracted and analyzed, and the azimuth and elevation spread of arrival are statistically characterized. The influence of obstacles on multipath spatial characteristics in intersection scenarios is investigated. Then we investigate the spatial stationarity of channels and analyze the possible reasons for the differences in spatial stationarity of different scenarios. In addition, based on multipath extraction, we quantitatively analyze the energy of dense multipath components in different propagation scenarios. The research in this paper can enrich the investigation of vehicular channels and enable the analysis and design of vehicular communication systems.

Signal Loss Detection and Correction for Improved Distance Estimation in Indoor Environments Using Path Loss Models

Signal Loss Detection and Correction for Improved Distance Estimation in Indoor Environments Using Path Loss Models

Specific Attenuation Estimation in Perturbed Radio Wave Propagation Using Artificial Neural Networks

Path loss modeling is a crucial consideration in radio engineering for wireless networks. Over the years, diverse techniques have been implemented in attempts to accurately predict path loss across a given terrain. In this study, path loss predictors created on the bases of artificial neural networks (ANN) were used to estimate path loss across a rural section of the Nigerian middle-belt grassland. The ANN structures considered were the Generalized Regression Neural network (GRNN) and the Radial Basis Function Neural Network (RBFNN), which exhibit a few differences and similarities. These ANN based predictors were trained, validated and tested for path loss prediction using path loss values computed from received power measured at 900MHz from six Base Transceiver Stations (BTSs) situated along the rural terrain. Findings show that the RBFNN predictor with a Root Mean Squared Error (RMSE) of 5.17dB and the GRNN with 4.9dB are slightly more accurate than the COST 231 Hata model with 6.64dB, while the Hata-Okumura with 25.78dB is simply not suitable for the terrain under investigation. Overall, the GRNN, which proffers a 26.21% improvement over the COST 231 Hata is recommended for the terrain in question.

Effective path-loss compensation model based on multipath exploitation for through-the-wall radar imaging

Through-the-wall radar imaging (TWRI) has attracted a great deal of attention in several sensitive applications, including rescue missions and military operations. Notwithstanding its broad range of applications, TWRI suffers from path-loss because distant targets experience more attenuation of signal power than those closer to the transceiver. This challenge may lead to missed targets with important information necessary for analysis and informed decision making. Responding to the challenge, we have developed a signal model with an effective path-loss compensator incorporating a free space exponent. Furthermore, multipath exploitation and compressive sensing techniques were employed to develop an effective algorithm for isolating residual clutter that may corrupt real targets. The proposed signal model integrates contributions from the front wall, multipath returns, and path-loss. Compared with the state-of-the-art model under the same experimental conditions, simulation results show that the proposed model achieves improved signal-to-clutter ratio, relative clutter peak, and probability of detection by 13.1%, 17.4% and 33.6%, respectively, suggesting that our model can represent the scene more accurately.

A RSS-based path loss model approaches multi-dimensional scaling to localize 2D sensor nodes in WSN

A RSS-based path loss model approaches multi-dimensional scaling to localize 2D sensor nodes in WSN

AJ-Olu-1: An Innovative Path Loss Model for Typical Nigerian Urban Environments

The modeling of outdoor path loss propagation is critical in the planning and construction of the Global System for Mobile Communication (GSM) coverage area. For GSM signal prediction at any location inside its service region, a precise forecast based on critical characteristics and a mathematical model is required. Numerous research findings on path loss propagation model forecast for GSM mobile networks conducted in various cities in Nigeria revealed that the COST231-Hata model gives closer prediction to most of the practical measure path loss values. Based on the existing COST-23-Hata path loss model and outdoor measurements at 1800 MHz frequency range within Ilorin metropolis, this paper proposed a suitable path loss model. The developed model was used and validated in various locations throughout Ilorin city with the measured and COST-231 Hata models. The analysis of the results revealed that the developed model performed satisfactorily in terms of the closest path loss prediction to the practical measure path loss values at all study locations. It also has the lowest Square Root Means Error and Standard Deviation (SD) of any Base Station (BTS) tested in Ilorin, Nigeria. As a result, it is concluded that the newly developed AJ-Olu-1 model is more suitable for GSM 1800 network design and installation in Ilorin City, Nigeria, as well as other cities in Nigeria and other cities outside Nigeria with similar environments.

Path Loss Modeling in Urban Water–Land Environments at 28 GHz: Considering Water Surface Reflection and Building Diffraction

This letter proposes a path loss model in urban water–land environments for line-of-sight (LOS) and non-LOS (NLOS) propagation at millimeter-wave (mm-wave) band, in which water surface reflection and building diffraction are considered simultaneously. An extensive measurement campaign in a campus pond environment at 28 GHz is conducted. Other channel characteristics, such as power delay profile and root-mean-square delay spread are also analyzed. Results indicate that the proposed model can predict the path loss in urban water–land environments accurately. This work can be applied to the deployment of wireless networks in urban water–land environments.

Massive MIMO and Secrecy Guard Zone Based Improving Physical Layer Security in UAV-Enabled uRLLC Networks

Ultra reliable low latency communications (uRLLC) is a new service category for sixth-generation (6G) wireless networks. The security and confidentiality of information transmission faces more challenges in the context of uRLLC because of the openness nature of wireless medium. By using the inherent characteristics of wireless medium, physical layer security (PLS) can be used as a promising solution to ensure the security of wireless communications. Unmanned aerial vehicle (UAV) communications is frequently characterized by line-of-sight (LoS) and dynamic propagation conditions. Since UAV can provide a strong line-of-sight link with strong reliability and speed, it is widely used in various wireless communication scenarios. Much previous work ignored the role of UAVs in PLS research in uRLLC. In this paper, we consider the line-of-sight/non-line-of-sight (NLoS) path-loss model for UAV-aided air-to-ground (A2G) wireless channel. Furthermore, massive MIMO technology is adopted in the deployment of transmitter-receiver pairs. In terms of performance measurement, we introduce the network insurance framework for network users. Under this framework, this paper deduces the closed expressions of connection outage probability (COP) and secrecy outage probability (SOP) for the above UAV-enabled network scenarios. Finally, the secrecy guard zone is proposed to further protect the confidentiality. Simulations validate our derived theoretical results, and indicate that communication security increases with the radius of the guard zone, while eavesdropper density has a detrimental effect.

Vehicle-to-vehicle communication channel measurements on a vertical curve road

Vehicle-to-Vehicle (V2V) communication channel measurements were carried out in different environments such as urban, suburban, rural, highway, tunnel, and overpass. The roads in these environments have generally flat terrain. However, there are horizontal or vertical curve roads that have been little focused in the literature. In this study, we performed two V2V measurements on a vertical-curve road in a rural environment to show how received signal strength changes with the distance between the transmitter and the receiver. The path loss exponent of log-distance path loss model was calculated by using the least-square method. According to the results, the path loss exponents were estimated as 7.53 and 7.61 with 78% and 83% fitting performances for two measurements. In literature, however, the path loss exponent for different propagation environments was obtained up to 6.13, especially in the straight road. Thus, our findings show that the vertical curve roads cause 15-20 dB more attenuation in the received signal strength than the straight roads. As a result, the vertical curve roads should be investigated and included in existing wireless communication simulators to better model real measurements. The authors contend that this study will aid in improving the channel modeling of V2V communication.

Multi-Boundary Empirical Path Loss Model for 433 MHz WSN in Agriculture Areas Using Fuzzy Linear Regression.

Path loss models are essential tools for estimating expected large-scale signal fading in a specific propagation environment during wireless sensor network (WSN) design and optimization. However, variations in the environment may result in prediction errors due to uncertainty caused by vegetation growth, random obstruction or climate change. This study explores the capability of multi-boundary fuzzy linear regression (MBFLR) to establish uncertainty relationships between related variables for path loss predictions of WSN in agricultural farming. Measurement campaigns along various routes in an agricultural area are conducted to obtain terrain profile data and path losses of radio signals transmitted at 433 MHz. Proposed models are fitted using measured data with "initial membership level" (μAI). The boundaries are extended to cover the uncertainty of the received signal strength indicator (RSSI) and distance relationship. The uncertainty not captured in normal measurement datasets between transmitter and receiving nodes (e.g., tall grass, weed, and moving humans and/or animals) may cause low-quality signal or disconnectivity. The results show the possibility of RSSI data in MBFLR supported at an μAI of 0.4 with root mean square error (RMSE) of 0.8, 1.2, and 2.6 for short grass, tall grass, and people motion, respectively. Breakpoint optimization helps provide prediction accuracy when uncertainty occurs. The proposed model determines the suitable coverage for acceptable signal quality in all environmental situations.

Path loss measurement and modeling of 5G network in emergency indoor stairwell at 3.7 and 28 GHz.

Research on path loss in indoor stairwells for 5G networks is currently insufficient. However, the study of path loss in indoor staircases is essential for managing network traffic quality under typical and emergency conditions and for localization purpose. This study investigated radio propagation on a staircase where a wall separated the stairs from free space. A horn and an omnidirectional antenna were used to determine path loss. The measured path loss evaluated the close-in-free-space reference distance, alpha-beta model, close-in-free-space reference distance with frequency weighting, and alpha-beta-gamma model. These four models exhibited good compatibility with the measured average path loss. However, comparing the path loss distributions of the projected models revealed that the alpha-beta model exhibited 1.29 dB and 6.48 dB for respectively, at 3.7 GHz and 28 GHz bands. Furthermore, the path loss standard deviations obtained in this study were smaller than those reported in previous studies.