Path Loss Model Research Articles

RSSI Fingerprint Height Based Empirical Model Prediction for Smart Indoor Localization.

Smart indoor living advances in the recent decade, such as home indoor localization and positioning, has seen a significant need for low-cost localization systems based on freely available resources such as Received Signal Strength Indicator by the dense deployment of Wireless Local Area Networks (WLAN). The off-the-shelf user equipment (UE's) available at an affordable price across the globe are well equipped with the functionality to scan the radio access network for hearable single strength; in complex indoor environments, multiple signals can be received at a particular reference point with no consideration of the height of the transmitter and possible broadcasting coverage. Most effective fingerprinting algorithm solutions require specialized labor, are time-consuming to carry out site surveys, training of the data, big data analysis, and in most cases, additional hardware requirements relatively increase energy consumption and cost, not forgetting that in case of changes in the indoor environment will highly affect the fingerprint due to interferences. This paper experimentally evaluates and proposes a novel technique for Received Signal Indicator (RSSI) distance prediction, leveraging transceiver height, and Fresnel ranging in a complex indoor environment to better suit the path loss of RSSI at a particular Reference Point (RP) and time, which further contributes greatly to indoor localization. The experimentation in different complex indoor environments of the corridor and office lab during work hours to ascertain real-life and time feasibility shows that the technique's accuracy is greatly improved in the office room and the corridor, achieving lower average prediction errors at low-cost than the comparison prediction algorithms. Compared with the conventional prediction techniques, for example, with Access Point 1 (AP1), the proposed Height Dependence Path-Loss (HEM) model at 0 dBm error attains a confidence probability of 10.98%, higher than the 2.65% for the distance dependence of Path-Loss New Empirical Model (NEM), 4.2% for the Multi-Wall dependence on Path-Loss (MWM) model, and 0% for the Conventional one-slope Path-Loss (OSM) model, respectively. Online localization, amongst the hearable APs, it is seen the proposed HEM fingerprint localization based on the proposed HEM prediction model attains a confidence probability of 31% at 3 m, 55% at 6 m, 78% at 9 m, outperforming the NEM with 26%, 43%, 62%, 62%, the MWM with 23%, 43%, 66%, respectively. The robustness of the HEM fingerprint using diverse predicted test samples by the NEM and MWM models indicates better localization of 13% than comparison fingerprints.

Comparative Analysis of Mobile Signal Propagation Path Loss in Lagos, Nigeria

This research involves comparative analysis of mobile radio transmission path loss models in Lagos state. Lagos, coastal region within an altitude of 38m, and geographical coordinates (63.60N, 3.280E), in the rainforest area of south-western, Nigeria. The measured active base stations propagation measured parameters (for selected areas; Agbowa, Ibeju Imota, Ilupeju, and Surulere in Lagos between 2019 and 2020 from MTN-NG Microsites) recorded between frequency range of 1500- 2500MHz band with a visible line of sight (LOS) in three areas within the state. Stanford University Interim, ECC-33 and COST 231 models were adopted and optimized models were developed and their empirical outcomes revealed standard deviations (SDs) of 1.87, 1.11, and 31.78 respectively at 500m distance from the microsite of average rural areas. For the sub-urban areas, RMSEs (root mean square errors) observed were 39.11, 0.04, and 1.98 and with SD being 33.52, 0.03, and 1.69. More so, for an urban area, it was discovered that the RMSEs obtained for these three models were 34.84, 1.98 and 0.55 with SD of 29.86, 10.27 and 0.47 at same distance of 500m. The implication is that probability of an improved performance is high when optimized models is adopted compared with what is in existence.

Singular Value Decomposition and Quasi-Moment-Method as pathloss model calibration alternatives

Using indoor-to-outdoor pathloss measurements for a femtocell network, this paper presents a comparative evaluation of the performances of Singular Value Decomposition (SVD) and Quasi-Moment-Method (QMM) as pathloss model calibration tools. First, the performances of two published SVD models are compared with those of corresponding QMM models, developed through the calibration of basic ECC33 and WINNER II models. Then, and after noting that the ‘base models’ from which the poorer performing, published SVD calibrations reportedly derive, are either incompletely described or characterized by misprints, alternative ‘base models’ are prescribed by this paper. It is then shown through analysis that QMM and SVD represent alternative implementations of the same basic model calibration algorithm. Computational results due to the alternative models suggest that better performance metrics (Mean Prediction Error (MPE) and Root Mean Square Prediction Error (RMSPE)) are recorded, when existing basic models are modified to mimic the SVD ‘base model’, prior to SVD/QMM calibration. Indeed, because the MPE due to the calibration of the alternative models are all close to zero (actually equal to zero in a few cases), the associated residual profiles closely follow the Gaussian distribution typically assumed in the literature, for shadow fading modelling.

Channel Measurements and Modeling for Low Terahertz Communications in an Aircraft Cabin

The low terahertz band (0.1–1 THz) offers very high data rates for novel mobile applications and constitutes a promising candidate to meet the requirements in aviation, enabling future wireless in-flight entertainment (IFE) systems. An extensive knowledge of the propagation effects in the radio channel in complex scenarios is a prerequisite to successfully design a communication system. This article presents a measurement campaign in a real aircraft investigating the radio channel at 300 GHz for different deployments of a wireless IFE system. The propagation effects as well as temporal and spatial channel characteristics are analyzed for likely communication links between an access point and a user equipment (UE). In the same way, interference links between two UEs are studied, reporting transmission and reflection losses for various components of the aircraft. A deterministic and geometry-based channel model is derived and extended to cover the effect of human blockage that suggests an integration of the access point into the passenger service unit. The measurement and realistic path loss models can be used in further link and system level simulations and contribute to the design of future IFE systems.

Outdoor Channel Modeling at D-Band Frequencies for Future Fixed Wireless Access Applications

Fixed wireless access networks at millimeter wave frequencies enable an alternative to fiber-optic installations for providing high-throughput Internet connectivity. In this letter, we present outdoor channel measurements at D-band frequencies ranging from 120 GHz to 165 GHz, contributing to the design of future fixed wireless access networks. We measure angular path loss (PL) for both Line-of-Sight (LOS) and non-Line-of-Sight (NLOS) scenarios and calculate angular spread. We also measure building reflection loss for different angles and building facades. Directional LOS PL equals free-space PL, whereas omnidirectional PL is slightly lower. The angular spread of the LOS measurements is 19.7°. The omnidirectional NLOS PL model has a higher PL and the angular spread increases to 54.4°. Losses up to 11 dB should be taken into account for reflection on a fiber cement or building brick facade. and up to 15.6 dB and 18.5 dB for roughcast and stone bricks. Even though wireless communication via the direct path is preferred, reflected paths can enable high-throughput wireless communication if the direct path is obstructed.

Accurate Empirical Path Loss Models with Route Classification for mmWave Communications

This paper presents accurate empirical path loss models with route classification for the high band frequency of 5 G wireless. Propagation path routes are mainly classified into line of sight (LOS) and non-line-of-sight (NLOS). The NLOS routes are classified into 2 separate routes, namely, Hard_NLOS and Soft_NLOS. Their path loss models include free-space loss (Lfs) and multiscreen diffraction loss (Lmsd) together with the reflection from the building blocks. However, these NLOS routes can be combined into a single formula. The path loss models were fitted with measured path loss data at frequencies of 28 GHz and 73 GHz. These models are compared with four 5G empirical models, namely 5GCM, 3GPP, METIS, and mmMAGIC. The results show that the separated route models provide good agreement, especially for the hard routes compared with those models and provide the minimum MAE of 4.45 dB, 4.34 dB, and 6.72 dB for the hard route, soft route, and an all-NLOS route, respectively, for the dual-band frequency.

Intelligent network planning tool for location optimization of unmanned aerial vehicle base stations using geographical images

Nowadays, automated and intelligent solutions are required by different services and applications to satisfy current industrial necessities. Internet of things/robotic devices have been found useful in the collection and processing of data for pattern recognition, analyzing and anticipating incident information, optimization, and provision of better and timely decision-making to enable network providers to measure the quality of services, thereby ensuring efficiency. Telecommunication systems need reliable and fast internet networks for connected devices and other business activities; thus, technologies are being explored to determine efficient ways of planning and installing base stations. Recently, possibilities of deploying unmanned aerial vehicles (UAVs) as base stations had been investigated. Although successes have been recorded, not much work has been done on network planning tools for location optimization of UAV base stations (UAV-BS) in 5G and beyond networks to the best of our knowledge. In this paper, an intelligent network planning tool (iNPT) for location optimization of UAV-BS has been developed with different channel models and network planning parameters. The developed tool has resources to suggest a better positioning of the UAV-BS using the simulated annealing meta-heuristic to optimize their locations. The tool also includes a battery management interface that can calculate the battery dissipation with reference to the received and transmitted power of the UAV-BS and display the estimated time of flight for the UAV-BS. Geographical information, such as the height of a specific region, obtained from a map is considered in the simulations. The results obtained using the COST231-Hata, Hata path loss, log distance, and two-ray ground reflection models have been presented in this paper. Based on the experimental results, the developed simulator can be useful in network planning tasks to improve coverage areas using UAV-BSs. In addition, the proposed tool has a friendly interface that provides geographical images, and the BSs and UAVs optimized locations.

In-Body to On-Body Channel Characterization and Modeling Based on Heterogeneous Human Models at HBC-UWB Band

In this work, the in-body to on-body (IB2OB) channel characteristics of the ultrawideband (UWB) link from 10 to 50 MHz at the human body communication (HBC) band are studied for developing high-speed and large-capacity intrabody wireless communication systems. Incorporating the time-domain finite integration technique (FIT) with three types of anatomical human models (adult male, adult female, and teenager) and a simple geometric human model with homogeneous or multilayer biological tissues, the 10–50-MHz signal propagation characteristics are investigated, and a comprehensive path loss model is proposed based on typical in-body links of the heart, brain, and intestine to the on-body sensor nodes. The statistical results show that a linear regulation term related to the surface wave propagation should be added to construct a more accurate logarithmic-distance path loss model in the sense of least-mean-square error (LMSE), indicating that the surface wave propagation mechanism can describe the 10–50-MHz signal propagation more accurately. The shadow fading in decibel is normally distributed around the mean path loss with a standard deviation in the range of 7–9 dB. And the average group delay of the IB2OB channel fluctuates around 0–7 ns, illustrating that the channel can be approximated as a linear phase response. Moreover, the experimental verification is conducted with a tissue-equivalent liquid phantom and an adult man, demonstrating the validity of our proposed statistical path loss model. The key parameters for channel characterization in simulations and measurements are summarized to provide useful insights for HBC-UWB communication system design and performance analysis.

Low-Altitude-Platform-Based Airborne IoT Network (LAP-AIN) for Water Quality Monitoring in Harsh Tropical Environment

This article proposes a novel Airborne Internet of Things Network (AIN) system architecture for monitoring water quality, combining existing wireless technologies with the aid of a low altitude platform (LAP) to relay data over long distances in hilly terrain. The proposed system consists of water quality sensors, smart utility network (SUN) devices, long range (LoRa) wireless devices, an LAP air balloon, and Wi-Fi devices. A measurement campaign was conducted to assess the proposed system, focusing on the communication link reliability and the LAP stability and robustness. Several constraints, such as payload limit and safe weather conditions, were also highlighted for operating the LAP with extensive and reliable coverage. On the other hand, characterizing the wireless channel has become a crucial parameter for planning and deploying Internet of Things (IoT) applications. Accordingly, this work proposes a novel hybrid machine learning (ML)-based semi-empirical path loss (PL) model for LoRa wireless communication. The results validated the proposed system’s effectiveness, unique characteristics, and capability to monitor water quality in a harsh environment. Results also revealed a significant difference in packet delivery rate (PDR) for different gateway height and spreading factor (SF) configurations. For instance, switching SF7 to SF12 increased PDR by 28.7%. Meanwhile, increasing gateway height increased PDR by 29.2% for similar SF configurations. The evaluation also revealed that none of the established PL models are suitable to represent harsh tropical environments. Finally, the proposed model achieved nearly 90% prediction accuracy for testing samples and 95% accuracy for training and overall measurement samples, vastly outperforming conventional models.

Field trial measurement and channel modeling for reconfigurable intelligent surface

With the advantage of programmable electromagnetic properties, Reconfigurable Intelligent Surfaces (RISs) have drawn wide attention from both industry and academia. RIS-assisted communication systems can promote huge wireless channel quality improvement and remarkable coverage enhancement. This paper proposes general pathloss model, radiation pattern and mirror beam effect of 1-bit RIS at sub-6 GHz band. Field trails have been carried out in outdoor and indoor deployment scenarios. The proposed model is validated through extensive simulations and field-trial measurements. In addition, an optimized RIS phase-shit design process for the mirror beam elimination is proposed and validated with simulations. The proposed theoretical model and measurement results can promote future research and application in RIS-assisted communications.

Path Loss Measurements and Model Analysis in an Indoor Corridor Environment at 28 GHz and 38 GHz.

This paper examines the large-scale path loss models for an indoor corridor environment at frequencies of 28 and 38 GHz. The measurement environment consists of an indoor corridor with both line-of-sight (LOS) and non-line of sight (NLOS) scenarios using vertical–vertical (V–V) and vertical–horizontal (V–H) antenna polarizations. The single-frequency close-in (CI), floating intercept (FI), free space large-scale path loss models and measured data from the measurement campaign were used to evaluate the performance analysis. The paper also focuses on various parameters, such as standard deviation, path loss exponent (PLE), accuracy, simplicity, and stability of the models. The analysis focuses on the peculiarity of the effect of the wall proximity on the path loss parameters as well as comparisons with the parameters in some of the reviewed literature studies. The FI and CI models produce comparable results for both antenna polarizations and clearly fit with the measured path loss. The PLE, with the highest value of 3.33 at 38 GHz (V–H), is much higher in the NLOS scenario with V–H polarization due to the signal degradation along the path from the transmitter (Tx) to the receiver (Rx). This is because there is no direct LOS between the Tx and Rx antennas. The Rx only relies on signal diffractions and reflections from obstacles as it transmits through the path from the Tx antenna. The path loss measurements and model analysis presented here are useful in designing 5G wireless communication systems for indoor environments, particularly for power budget calculations.

Underwater Wireless Sensor Network Performance Analysis Using Diverse Routing Protocols

The planet is the most water-rich place because the oceans cover more than 75% of its land area. Because of the unique activities that occur in the depths, we know very little about oceans. Underwater wireless sensors are tools that can continuously transmit data to one of the source sensors while monitoring and recording their surroundings’ physical and environmental parameters. An Underwater Wireless Sensor Network (UWSN) is the name given to the network created by collecting these underwater wireless sensors. This particular technology has a random path loss model due to the time-varying nature of channel parameters. Data transmission between underwater wireless sensor nodes requires a careful selection of routing protocols. By changing the number of nodes in the model and the maximum speed of each node, performance parameters, such as average transmission delay, average jitter, percentage of utilization, and power used in transmit and receive modes, are explored. This paper focuses on UWSN performance analysis, comparing various routing protocols. A network path using the source-tree adaptive routing-least overhead routing approach (STAR-LORA) Protocol exhibits 85.3% lower jitter than conventional routing protocols. Interestingly, the fisheye routing protocol achieves a 91.4% higher utilization percentage than its counterparts. The results obtained using the QualNet 7.1 simulator suggest the suitability of routing protocols in UWSN.

Path Loss Modelling for High Speed Rail in 5G Communication System

A new path loss model for high-speed rail (HSR) in the 5G communication system is constructed in this paper. The model is identified to obtain an accurate mathematical representation of path loss multipath propagation in line of sight of HSR scenarios. The grey box modelling utilization of Generalized Reduced Gradient (GRG) and Genetic algorithm (GA) is applied to find the unknown parameters of the constructed path loss model since some uncertainties in obtaining the corresponded parameters are unavoidable to be collected in the field. Both algorithms achieve excellent results in finding the unknown parameter values with RMSE and MAPE evaluation which are converging finally to 2.779 and 1.701 %. The visualization of fitting plots is also presented, and GA provides a better-adjusted agreement with the measurement dataset of HSR. Accordingly, the constructed path loss model is successfully validated since it is capable of following

Machine Learning Regression for RF Path Loss Estimation Over Grass Vegetation in IoWSN Monitoring Infrastructure

This proposal examines the effect of grass vegetation elevation and density on path loss between sensors deployed in an IoT-enabled wireless sensor network (IoWSN) crop monitoring infrastructures. Observations via real-time measurement campaigns at different node heights and vegetation depths revealed that the sensor deployment made using free-space or tree vegetation based path loss model (PLM) experiences network disconnectivity due to variations in vegetation density in a cropping cycle. An empirical PLM is formulated to identify signal strength at different development phases of paddy and sugarcane medium grass vegetation. For this, the 2.4 GHz RF path loss coefficient (PLC) is estimated using data collected through measurement campaign over combinations of sensor height and vegetation density. Further, the formulated PLC is used to train multiple regression model to develop a generic PLM for all medium grass vegetation. Improvements in coverage and connectivity have been validated through proof of concept.

Towards Practical Path Loss Predictions in Indoor Corridors Considering 5G mmWave Three-Dimensional Measurements

Theoretical and empirical foundations of how radio waves behave in practical wireless channels need to be fully revisited for millimeter-wave (mmWave) frequencies so that fifth-generation (5G) technologies may be successful. Kriging is an outstanding geostatistal interpolation technique that employs variography to understand the spatial variability of known samples at specific locations to predict unmeasured samples, based on the fact that there is an implied connection between the measured value and its location in space. The research we here report is aimed at validating the improvement in predictions when this tool is included for mmWave frequency path loss modeling in a long indoor corridor with break. In order to quantify the accuracy of the proposed methodology, it is compared with a well-established procedure described in the literature. Extensive path-loss measurements were collected through specialized narrowband sounders at 28 and 60 GHz. Spatially averaged power measurements using omnidirectional and directive antennas at different heights provided the empirical basis for the three-dimensional Kriging-aided model. It was found that this method significantly improves the accuracy as it considers all the singularities and site-associated features that are implicit in measured samples. This is important to obtain a reliable path loss model for planning and deployment of mmWave wireless communication systems in indoor scenarios.

Directional link attenuation in millimeter-wave range based on empirical model modification

The upcoming fifth and next generation mobile phone systems will use not only the frequencybands of sub-6 GHz but also the millimeter-wave and terahertz bands. From a practical viewpoint,this approach requires the use of directional antennas or beamforming systems. To ensure greaterenergy efficiency of the wireless link, the radio beams on the transmitting and receiving sides shouldbe aligned ones. Path loss models are commonly used for designing the radio communication systemsand networks. However, in the literature, there are no adequate methods of attenuation modellingavailable for the cases of misalignment of antenna beams. In this paper, a method of modifying the pathloss model, based on a multi-elliptical propagation model, is proposed. For this purpose, dedicatedsoftware was developed in the MATLAB environment, which was used to conduct simulation tests.In the remainder of the paper, exemplary results of the adaptation of empirical path loss models inthe range of millime-ter-waves are presented, which were obtained using the developed program.Keywords: wireless communication, radio wave propagation, path loss models, multi-ellipticalpropagation model, directional antennas, directional radio link, millimeter waves, 5G systems,simulation studies

A hybrid model of regional path loss of wireless signals through the wall

A hybrid model of regional path loss of wireless signals through the wall

Exploring cooperative NOMA assisted hybrid visible light and radio frequency for enhanced vehicular message dissemination at road intersections

Vehicle-to-everything (V2X) communication aims to achieve significantly improved safety and traffic efficiency, more particularly at road intersection where high percentage of accidents usually occur. The existing vehicular radio frequency (V-RF) based V2X utilizes relaying for improving safety message dissemination at road intersections. For a high traffic density scenario, the V-RF communication with relaying solution may suffer from large latency and low packet delivery rates due to channel congestion. In this paper, we explore cooperative non-orthogonal multiple access (NOMA) communication assisted hybrid vehicular visible light communication (V-VLC) and V-RF communication for improving safety message dissemination and enabling massive connectivity among vehicles for road intersection scenarios. We develop a stochastic geometry based analytical framework to model cooperative NOMA (C-NOMA) transmissions subject to interference imposed by other vehicles on roads. We also examine the impact of vehicles headlights radiation pattern viz. Lambertian and empirical path loss models on statistical characterization of the proposed C-NOMA supported hybrid solution. Our numerical findings reveal that C-NOMA assisted hybrid V-VLC/V-RF system leads to considerable improvement in outage performance and average achievable rate as compared to traditional V-RF solution with relaying. Interestingly, Lambertian model offers a lower outage and higher average achievable rate compared to the empirical model for the proposed hybrid solution. Further, we observe the performance improvement using maximal ratio combining (MRC) considering NOMA transmission for the proposed hybrid solution. The presented framework may serve as an alternative for cooperative intelligent transportation system (C-ITS) to meet diverse application needs for beyond 5G (B5G) V2X networks.

Propagation Measurements for IQRF Network in an Urban Environment.

Recently, IQRF has emerged as a promising technology for the Internet of Things (IoT), owing to its ability to support short- and medium-range low-power communications. However, real world deployment of IQRF-based wireless sensor networks (WSNs) requires accurate path loss modelling to estimate network coverage and other performances. In the existing literature, extensive research on propagation modelling for IQRF network deployment in urban environments has not been provided yet. Therefore, this study proposes an empirical path loss model for the deployment of IQRF networks in a peer-to-peer configured system where the IQRF sensor nodes operate in the 868 MHz band. For this purpose, extensive measurement campaigns are conducted outdoor in an urban environment for Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) links. Furthermore, in order to evaluate the prediction accuracy of well-known empirical path loss models for urban environments, the measurements are compared with the predicted path loss values. The results show that the COST-231 Walfisch–Ikegami model has higher prediction accuracy and can be used for IQRF network planning in LoS links, while the COST-231 Hata model has better accuracy in NLoS links. On the other hand, the effects of antennas on the performance of IQRF transceivers (TRs) for LoS and NLoS links are also scrutinized. The use of IQRF TRs with a Straight-Line Dipole Antenna (SLDA) antenna is found to offer more stable results when compared to IQRF (TRs) with Meander Line Antenna (MLA) antenna. Therefore, it is believed that the findings presented in this article could offer useful insights for researchers interested in the development of IoT-based smart city applications.

Network deployment for Energy Efficiency using Single-Slope and Multiple-Slope Path Loss Models

Network deployment for Energy Efficiency using Single-Slope and Multiple-Slope Path Loss Models