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The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions. [ABSTRACT FROM AUTHOR]

The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions.

The usage scenarios defined in the ITU-M2150-1 recommendation for IMT-2020 systems, including enhanced Mobile Broadband (eMBB), Ultra-reliable Low-latency Communication (URLLC), and massive Machine Type Communication (mMTC), allow the possibility of accessing different services through the set of Radio Interface Technologies (RITs), Long-term Evolution (LTE), and New Radio (NR), which are components of RIT. The potential of the low and medium frequency bands allocated by the Federal Communications Commission (FCC) for the fifth generation of mobile communications (5G) is described. In addition, in the Internet of Things (IoT) applications that will be covered by the case of use of the mMTC are framed. In this sense, a propagation channel measurement campaign was carried out at 850 MHz and 5.9 GHz in a covered corridor environment, located in an open space within the facilities of the Pedagogical and Technological University of Colombia campus. The measurements were carried out in the time domain using a channel sounder based on a Universal Software Radio Peripheral (USRP) to obtain the received signal power levels over a range of separation distances between the transmitter and receiver from 2.00 m to 67.5 m. Then, a link budget was proposed to describe the path loss behavior as a function of these distances to obtain the parameters for the close-in free space reference distance (CI) and the floating intercept (FI) path loss prediction models. These parameters were estimated from the measurements made using the Minimum Mean Square Error (MMSE) approach. The estimated path loss exponent (PLE) values for both the CI and FI path loss models at 850 MHz and 3.5 GHz are in the range of 2.21 to 2.41, respectively. This shows that the multipath effect causes a lack of constructive interference to the received power signal for this type of outdoor corridor scenario. These results can be used in simulation tools to evaluate the path loss behavior and optimize the deployment of device and sensor network infrastructure to enable 5G-IoT connectivity in smart university campus scenarios. [ABSTRACT FROM AUTHOR]

In this letter, the extensive measurements and simulations are conducted at 28 GHz in the large waiting hall environments. The rotated linear array‐based method of measurement is proposed. The rotated linear array‐based method of measurement and the uniform virtual array‐based method of measurement are performed and compared. The space‐alternating generalized expectation‐maximization algorithm is exploited to extract the propagation parameters of multipath components (MPCs). Path loss models are illustrated based on self‐developed ray tracing simulator. A good agreement is achieved between the simulated results and the measured results, so the correctness of improved ray tracing method is verified. The results show that the measured results of the rotated linear array‐based method and the uniform virtual array‐based method are consistent. But the rotated linear array‐based method is simpler and less time‐consuming. A universal path loss model is proposed in the large waiting hall scenarios at 28 GHz. Moreover, clustering of MPCs is investigated by the K‐power‐mean algorithm. The number of clusters are calculated and analyzed. [ABSTRACT FROM AUTHOR]

In the realm of radio frequency identification (RFID) technology, the integration of reconfigurable intelligent surfaces (RISs) has opened up new possibilities for real-time remote data capturing and seamless connectivity. By manipulating the electromagnetic properties of the environment, RIS enables the control of electromagnetic wave propagation and allows for virtual line-of-sight (LOS) in cases where physical LOS is blocked. This has tremendous implications for the future of RFID applications, particularly with the emergence of chipless RFID technology. In this regard, this paper develops free-space path loss models for RIS-assisted RFID wireless communications. The proposed models in this study have taken into account several crucial physical factors, including tag radar cross-section (RCS), the physical properties of the RIS, and the radiative near-field/far-field effects of the RIS. To further validate the theoretical findings, we have conducted experimental measurements using a fabricated RIS. Numerical simulations were also utilized to validate the models and verify our findings. The channel measurements have demonstrated good agreement with the proposed path loss models, further bolstering the potential of RIS-assisted RFID wireless communications.

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

Effective communication in underwater environments is essential for numerous applications, including marine research, oil and gas exploration, and underwater surveillance. However, signal loss during propagation is a significant challenge for underwater communication systems. Accurate mathematical models are necessary to develop and optimize communication systems for underwater environments. This research proposes a mathematical model, SWARA, that incorporates crucial parameters such as transmitter and receiver responses, channel conditions, node placements, and signal frequency to accurately model short-range losses in underwater medium. We conducted tank trials at the UWAA Lab, CARE, IIT Delhi to validate our simulation results, using a chirp signal with a frequency ranging from 25–35 kHz. Our simulation results show that the SWARA model effectively predicts short-range propagation losses in underwater media. Compared to experimental losses, the maximum and minimum simulated losses deviated by only − 0.18–0.10 W/Hz and − 0.36–0.19 W/Hz, respectively, indicating the accuracy of the model. Our tank trials further revealed the significant impact of projector and hydrophone placements on incurred losses, highlighting the importance of careful placement in the design of underwater communication systems. In conclusion, this research proposes the SWARA model for studying short-range losses in underwater tank, which effectively incorporates crucial parameters for accurate modeling. The model has practical applications in the design and optimization of underwater communication systems for short-range applications. This research provides important insights for the development of effective underwater communication systems. [ABSTRACT FROM AUTHOR]

In this paper, a path loss characterization at millimeter-wave (mmWave) frequencies is performed in a typical indoor office environment. Path loss results were derived from propagation channel measurements collected in the 25–40 GHz frequency band, in both line-of-sight (LOS) and obstructed-LOS (OLOS) propagation conditions. The channel measurements were performed using a frequency-domain channel sounder, which integrates an amplified radio over fiber (RoF) link to avoid the high losses at mmWave. The path loss was analyzed in the 26 GHz, 28 GHz, 33 GHz and 38 GHz frequency bands through the close-in free space reference distance (CI) and the floating-intercept (FI) models. These models take into account the distance dependence of the path loss for a single frequency. Nevertheless, to jointly study the distance and frequency dependence of the path loss, multi-frequency models were considered. The parameters of the ABG (A-alpha, B-beta and G-gamma) and the close-in free space reference distance with frequency path loss exponent (CIF) models were derived from the channel measurements in the whole 25–40 GHz band under the minimum mean square error (MMSE) approach. The results show that, in general, there is some relationship between the model parameters and the frequency. Path loss exponent (PLE) values smaller than the theoretical free space propagation were obtained, showing that there are a waveguide effect and a constructive interference of multipath components (MPCs). Since the measurements were obtained in the same environment and with the same configuration and measurement setup, it is possible to establish realistic comparisons between the model parameters and the propagation behavior at the different frequencies considered. The results provided here allow us to have a better knowledge of the propagation at mmWave frequencies and may be of interest to other researchers in the simulation and performance evaluation of future wireless communication systems in indoor hotspot environments. [ABSTRACT FROM AUTHOR]

The performance of any Mobile Wireless Network (MWN) is dependent on the appropriate level of radio coverage, with Path Loss (PL) models being a valuable resource for its evaluation. Recently, advancements in Machine Learning (ML) and Deep Neural Networks (DNNs) have been applied to radio propagation to produce new data-driven PL models. Notoriously, these advancements have also allowed the inclusion of non-classical inputs, such as satellite images. However, data-driven PL models are often developed under the assumption that training and test data distributions are similar, which is a weak assumption in real-world scenarios. Thus, generalization (i.e., the model’s ability to perform on different data distributions) is a crucial aspect of data-driven PL models in the context of Mobile Network Operators (MNOs). This paper proposes a new data-driven PL model, the Ubiquitous Satellite Aided Radio Propagation (USARP) model, developed to enhance the geographical generalization capabilities of empirical PL models, by using satellite images. The USARP model considers self-supervised learning to extract general data representations of the radio environment from satellite images, improving the PL prediction Root Mean Square Error (RMSE) of the $3^{rd}$ Generation Partnership Project (3GPP) PL model in the order of 9 dB, and for a data distribution distinct from the training data. Moreover, it was demonstrated the potential of the USARP model in terms of geographical and radio environment generalization. Although the generalization capabilities of ML regression algorithms are limited, the chosen USARP architecture and the use of regularization techniques had a positive impact on its geographical generalization performance.

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. [ABSTRACT FROM AUTHOR]

Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, the radio signal attenuation loss between the path lengths of a base transmitter and the mobile station receiver must be appropriately estimated. Although many log-distance-based linear models for path loss prediction in wireless cellular networks exist, radio frequency planning requires advanced non-linear models for more accurate predictive path loss estimation, particularly for complex microcellular environments. The precision of the conventional models on path loss prediction has been reported in several works, generally ranging from 8–12 dB in terms of Root Mean Square Error (RMSE), which is too high compared to the acceptable error limit between 0 and 6 dB. Toward this end, the need for near-precise machine learning-based path loss prediction models becomes imperative. This work develops a distinctive multi-layer perception (MLP) neural network-based path loss model with well-structured implementation network architecture, empowered with the grid search-based hyperparameter tuning method. The proposed model is designed for optimal path loss approximation between mobile station and base station. The hyperparameters examined include the neuron number, learning rate and hidden layers number. In detail, the developed MLP model prediction accuracy level using different learning and training algorithms with the tuned best values of the hyperparameters have been applied for extensive path loss experimental datasets. The experimental path loss data is acquired via a field drive test conducted over an operational 4G LTE network in an urban microcellular environment. The results were assessed using several first-order statistical performance indicators. The results show that prediction errors of the proposed MLP model compared favourably with measured data and were better than those obtained using conventional log-distance-based path loss models. [ABSTRACT FROM AUTHOR]

The ability to estimate radio coverage accurately is fundamental for planning and optimizing any wireless network, notably when a new generation, as the 5th Generation (5G), is in an early deployment phase. The knowledge acquired from radio planning of previous generations must be revisited, particularly the used path loss and antennas models, as the 5G propagation is intrinsically distinct. This paper analyses a new beamforming antenna model and distinct path loss models - 3rd Generation Partnership Project (3GPP) and Millimetre-Wave Based Mobile Radio Access Network for Fifth Generation Integrated Communications (mmMAGIC) - applying them to evaluate 5G coverage in 3-Dimensional (3D) synthetic and real scenarios, for outdoor and indoor environments. Further, real 5G Drive Tests (DTs) were used to evaluate the 3GPP path loss model accuracy in Urban Macro (UMa) scenarios. For the new antenna model, it is shown that the use of beamforming with multiple vertical beams is advantageous when the Base Station (BS) is placed below the surrounding buildings; in regular UMa surroundings, one vertical beam provides adequate indoor coverage and a maximized outdoor coverage after antenna tilt optimization. The 3GPP path loss model exhibited a Mean Absolute Error (MAE) of 21.05 dB for Line-of-Sight (LoS) and 14.48 dB for Non-Line-of-Sight (NLoS), compared with real measurements. After calibration, the MAE for LoS and NLoS decreased to 5.45 dB and 7.51 dB, respectively. Moreover, the non-calibrated 3GPP path loss model led to overestimations of the 5G coverage and user throughput up to 25% and 163%, respectively, when compared to the calibrated model predictions. The use of Machine Learning (ML) algorithms resulted in path loss MAEs within the range of 4.58 dB to 5.38 dB, for LoS, and within the range of 3.70 dB to 5.96 dB, for NLoS, with the Random Forest (RF) algorithm attaining the lowest error.

The millimeter-wave (mm-wave) frequency band is projected to play a critical role in next-generation wireless networks owing to its large available bandwidth. Despite the theoretical potential for high data throughput, the mm-wave frequency faces numerous challenges—including severe path loss and high penetration loss. Therefore, a reliable understanding of channel propagation characteristics is required for the development of accurate and simple indoor communication systems. In this study, we conducted measurement campaigns with unique transmitter- receiver combinations using horn and tracking antennas, at 3.7 and 28 GHz in an indoor corridor environment on the $10^{th}$ floor of an IT building and the $3^{rd}$ floor of the main building of Chosun University, Gwangju, South Korea, and the details are presented herein. In both line-of-sight and non-line-of-sight scenarios, the large-scale path losses, and small-scale channel statistics, such as root mean square delay spread, and number of clusters, were obtained using the measurement results in a waveguide structure indoor corridor environment. We have proposed alternate methodologies beyond classical channel modeling to improve path loss models using artificial neural network (ANN) techniques—to alleviate channel complexity and avoid the time-consuming measurement process. The presented regression successfully assists the prediction of the path loss model in a new operating environment using measurement data from a specific scenario. The validated results suggest that the ANN large-scale path loss model used in this study outperforms the close-in reference distance and floating-intercept (alpha-beta) models. Additionally, our result shows that the number of time clusters follows an Erlang distribution.

Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, the radio signal attenuation loss between the path lengths of a base transmitter and the mobile station receiver must be appropriately estimated. Although many log-distance-based linear models for path loss prediction in wireless cellular networks exist, radio frequency planning requires advanced non-linear models for more accurate predictive path loss estimation, particularly for complex microcellular environments. The precision of the conventional models on path loss prediction has been reported in several works, generally ranging from 8–12 dB in terms of Root Mean Square Error (RMSE), which is too high compared to the acceptable error limit between 0 and 6 dB. Toward this end, the need for near-precise machine learning-based path loss prediction models becomes imperative. This work develops a distinctive multi-layer perception (MLP) neural network-based path loss model with well-structured implementation network architecture, empowered with the grid search-based hyperparameter tuning method. The proposed model is designed for optimal path loss approximation between mobile station and base station. The hyperparameters examined include the neuron number, learning rate and hidden layers number. In detail, the developed MLP model prediction accuracy level using different learning and training algorithms with the tuned best values of the hyperparameters have been applied for extensive path loss experimental datasets. The experimental path loss data is acquired via a field drive test conducted over an operational 4G LTE network in an urban microcellular environment. The results were assessed using several first-order statistical performance indicators. The results show that prediction errors of the proposed MLP model compared favourably with measured data and were better than those obtained using conventional log-distance-based path loss models.

This paper presents an extensive path loss measurement campaign carried out in rural areas at 3.7 GHz, including line-of-sight (LOS) and non-LOS conditions. For this purpose, a commercially established fixed wireless access (FWA) network is exploited, operating with time-division long term evolution configuration. Furthermore, various models are examined and validated regarding their ability to predict accurately the path loss. The results reveal that the standard propagation model (SPM) achieves the best performance, thus being an attractive option for planning rural FWA links. The WINNER II and 3GPP/ITU-R models exhibit very good performance, as well. From the statistical assessment, the shadow fading follows the Lognormal distribution with a standard between 4.6 and 5.4 dB. An almost excellent fit is obtained regardless of the diverse propagation conditions in the specific area. Finally, from the model evaluation was concluded that SPM is highly recommended as the best option for a precise network dimensioning and planning. [ABSTRACT FROM AUTHOR]

The performance of most empirical models varies from place to place. The suitable models for a particular location with correct predicted signal path loss needed to be determined for proper communication budget planning. This paper examined the signal path loss of a UHF television station using different empirical path loss models. Okumura model, SUI MODEL for type A, Wilfisch-Ikegami model for urban, Hata model for urban, Hata- Okumira model for urban, Cost 231 Hata model for urban, Egli's model and free space model were used to analysed the signal path loss characteristics of NTA Osogbo, Ile Ife, Osun state network Centre in different routes within Ile-ife metropolis. The propagation measurements of signal strength and path loss were conducted in Ilorin using Agilent N9342C 100Hz-7GHz spectrum analyser. From the data collected, the signal powers received at each of the locations were estimated. The measured UHF signal strength and path loss of Agilent Spectrum Analyser was compared with the predicted signal path loss from eight different models and the models with best performance was determined by estimating errors between measured and predicted values of each models. The results showed that the path loss increased with the distance from the transmitter while the received power signal decreases with the ditsnace from transmitter antenna. Wilfisch-Ikeami model and Hata model are best suitable for the path loss prediction although Hata model has better performance with least mean error and standard error of precision. Using Hata model to predict the signal path loss, the maximum mean error is less than -10dB while Wilfisch-Ikegami model is -13dB slightly greater than the measured values. [ABSTRACT FROM AUTHOR]

Abstract: A modified indoor path loss prediction model is presented, namely, effective wall loss model. The modified model is compared to other indoor path loss prediction models using simulation data and real‐time measurements. Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, effective wall loss model shows the best performance among other models as it outperforms 2 times the dual‐slope model, which is the second best performance. Similar observations were recorded from the experimental results. Linear attenuation and one‐slope models have similar behavior, the two models parameters show dependency on operating frequency and antenna polarization. [ABSTRACT FROM AUTHOR]

For Wi-Fi positioning usually location fingerprinting or (tri)lateration are employed whereby the received signal strengths (RSSs) of the surrounding Wi-Fi Access Points (APs) are scanned on the mobile devices and used to perform localization. Within the scope of this study, the position of a mobile user is determined on the basis of lateration. Two new differential approaches are developed and compared to two common models, i.e., the one-slope and multi-wall model, for the conversion of the measured RSS of the Wi-Fi signals into ranges. The two novel methods are termed DWi-Fi as they are derived either from the well-known DGPS or VLBI positioning principles. They make use of a network of reference stations deployed in the area of interest. From continuous RSS observations on these reference stations correction parameters are derived and applied by the user in real-time. This approach leads to a reduced influence of temporal and spatial variations and various propagation effects on the positioning result. In practical use cases conducted in a multistorey office building with three different smartphones, it is proven that the two DWi-Fi approaches outperform the common models as static positioning yielded to position errors of about 5 m in average under good spatial conditions. [ABSTRACT FROM AUTHOR]

In this work Hata, Lee, Walfisch-Ikegami and Free Space Loss models have been compared with practical path loss based on series of measurements in Karada district in Baghdad for GSM900 downlink band. Hata model showed the closest path loss predictions with mean square error = 10.8 dB, but these results are far from good prediction results and need enhancement. Hata model was optimized using Least Squares method based on measured received signal power. The optimized Hata model showed much better results from the original Hata with mean square error = 6.96 dB. The simulation and calculations were implemented using MATLAB R2009b. The measurements were done using Field Test Display (FTD) with a compatible hand phone to measure signal strength. A Ground Positioning System (GPS) was used to measure the distance from transmitter.

This article describes the indoor IRLA (Intelligent Ray Launching Algorithm), which originates from an efficient outdoor propagation prediction model. Implementation and validation are given in detail. An indoor office scenario is selected and simulations via the IRLA model and two other reference models have been performed. Predictions are analysed and recommendations are given. Results show that the indoor IRLA model is suitable for indoor wireless network planning and optimisation process.

This paper compares three candidate large-scale propagation path loss models for use over the entire microwave and millimeter-wave (mmWave) radio spectrum: the alpha–beta–gamma (ABG) model, the close-in (CI) free-space reference distance model, and the CI model with a frequency-weighted path loss exponent (CIF). Each of these models has been recently studied for use in standards bodies such as 3rd Generation Partnership Project (3GPP) and for use in the design of fifth-generation wireless systems in urban macrocell, urban microcell, and indoor office and shopping mall scenarios. Here, we compare the accuracy and sensitivity of these models using measured data from 30 propagation measurement data sets from 2 to 73 GHz over distances ranging from 4 to 1238 m. A series of sensitivity analyses of the three models shows that the four-parameter ABG model underpredicts path loss when relatively close to the transmitter, and overpredicts path loss far from the transmitter, and that the physically based two-parameter CI model and three-parameter CIF model offer computational simplicity, have very similar goodness of fit (i.e., the shadow fading standard deviation), exhibit more stable model parameter behavior across frequencies and distances, and yield smaller prediction error in sensitivity tests across distances and frequencies, when compared to the four-parameter ABG model. Results show the CI model with a 1-m reference distance is suitable for outdoor environments, while the CIF model is more appropriate for indoor modeling. The CI and CIF models are easily implemented in existing 3GPP models by making a very subtle modification—by replacing a floating non-physically based constant with a frequency-dependent constant that represents free-space path loss in the first meter of propagation. This paper shows this subtle change does not change the mathematical form of existing ITU/3GPP models and offers much easier analysis, intuitive appeal, better model parameter stability, and better accuracy in sensitivity tests over a vast range of microwave and mmWave frequencies, scenarios, and distances, while using a simpler model with fewer parameters. [ABSTRACT FROM AUTHOR]

This paper presents 28 GHz wideband propagation channel characteristics for millimeter wave (mmWave) urban cellular communication systems. The mmWave spectrum is considered as a key-enabling feature of 5G cellular communication systems to provide an enormous capacity increment; however, mmWave channel models are lacking today. The paper compares measurements conducted with a spherical scanning 28 GHz channel sounder system in the urban street-canyon environments of Daejeon, Korea and NYU campus, Manhattan, with ray-tracing simulations made for the same areas. Since such scanning measurements are very costly and time-intensive, only a relatively small number of channel samples can be obtained. The measurements are thus used to quantify the accuracy of a ray-tracer; the ray-tracer is subsequently used to obtain a large number of channel samples to fill gaps in the measurements. A set of mmWave radio propagation parameters is presented based on both the measurement results and ray-tracing, and the corresponding channel models following the 3GPP spatial channel model (SCM) methodology are also described. [ABSTRACT FROM PUBLISHER]

Received signal strength (RSS) measurements are important in indoor location solutions based on WiFi, cellular networks or Bluetooth. RSS-based positioning involves two phases, namely, learning and estimation. The database sizes required both for the learning and for the estimation phases grow rapidly as the network coverage areas and the number of access points number increase. Achieving large-scale/global localization solutions would be possible if the database size bottlenecks were solved. We present here an innovative approach based on spectral compression, which allows a tremendous reduction in the database sizes in both learning and estimation phases. We introduce the new concept of compressed RSS images. We show how, through an astute 2-D frequency analysis, only a fraction of the transform-domain components need to be stored and transferred to/from the mobiles. Our idea is validated with WiFi real-life measurements from five multistory buildings. We show that our method is able to provide comparable results with the traditional fingerprinting approach, but with up to 80% reduction in the database sizes. [ABSTRACT FROM PUBLISHER]

In this letter, we present a path loss characterization of the vehicular-to-vehicular (V2V) propagation channel. We have assumed a path loss model suitable for vehicular ad hoc networks (VANETs) simulators. We have investigated the value of the model parameters, categorizing in line-of-sight (LOS) and non-LOS (NLOS) paths. The model parameters have been derived from extensive narrowband channel measurements at 700 MHz and 5.9 GHz. The measurements have been collected in typical expected V2V communications scenarios, i.e., urban, suburban, rural, and highway, for different road traffic densities, speeds, and driven conditions. The results reported here can be used to simulate and design the future vehicular networks. [ABSTRACT FROM AUTHOR]

Current shipboard monitoring systems use extensive lengths of cables to connect sensors to control units. Replacing wired connections by wireless ones may be an efficient solution to reduce the ship weight and cost. Ships are characterized by a specific metallic environment which can severely decrease the efficiency of wireless networks due to signal attenuation and multipath effects. In this paper, we present a feasibility study of a Wireless Sensor Network (WSN) using ubiquitous technologies on board vessels. A measurement campaign has been conducted on board a ferry to investigate the radio propagation challenges of wireless communications in this particular environment. Path loss models have been obtained for typical shipboard environments. Engineering rules concerning the placement and the number of communication nodes needed to cover the decks and maintain the network connectivity have been determined. Based on these results, an IEEE 802.15.4 compliant WSN has been tested on board the same ferry. Sensor nodes have been placed on the four decks of the ferry and the base station has been placed in the control room located in the bottom deck. Results show an excellent performance with respect to transmission ratio of sensor nodes and a significant connectivity between nodes located in different compartments and decks separated by metallic watertight doors. [ABSTRACT FROM AUTHOR]

This article describes the indoor IRLA (Intelligent Ray Launching Algorithm), which originates from an efficient outdoor propagation prediction model. Implementation and validation are given in detail. An indoor office scenario is selected and simulations via the IRLA model and two other reference models have been performed. Predictions are analyzed and recommendations are given. Results show that the indoor IRLA model is suitable for indoor wireless network planning and optimization process. [ABSTRACT FROM AUTHOR]

A good understanding of signal wave attenuation along a stairwell is necessary for successful wireless network planning. In this study, the propagation characteristics in indoor multi-floor stairwell environments are examined under the millimeter frequency band. An extensive signal measurement is conducted in two stairwells. These measurements provide information important for ensuring consistent radio transmission of data in such environment, which then enables immediate response during emergency operations. In these measurements, directional horn antennas for co-polarization and cross-polarization in transmitters and receivers are used for different millimeter frequencies (26, 28, 32, and 38 GHz). The feasibility of using the millimeter wave, which is suitable for indoor 5G wireless networks, in two different indoor stairwell environments is investigated. Four different models are employed for path loss investigation. Under single frequencies, the close-in free-space reference distance and floating-intercept path loss models are adopted. For multiple frequencies, the close-in free space reference distance with frequency dependent path loss exponent and alpha-beta-gamma models are applied. The measurements provide data on the received power at multi-floor stairwells through the stair steps, which are useful for path loss study. Accordingly, the path loss exponent values, standard deviations, and other parameters are obtained. [ABSTRACT FROM AUTHOR]