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Radio coverage in buildings
Abstract
For future personal communications services a very high standard of radio coverage within buildings will be essential. To achieve this standard requires good prediction models to make planning and installation of these systems as easy and cheap as possible. An appropriate model is evolved here for coverage at 864 MHz and 1728 MHz; these being the frequency bands of interest for these services. At each stage of the development of this model its prediction is compared with measured data in two contrasting types of building. The accuracy of the final model is shown to be high. Therefore it is concluded that good quality personal communications services are possible inside buildings.
... For this purpose, numerous power prediction algorithms have been proposed to help plan and evaluate RFID systems. These algorithms can be classified into full-wave simulation techniques [37][38][39], path-loss (PL) formulas [40][41][42][43] and ray-tracing models [44][45][46][47][48][49]. Among them, full-wave simulation techniques such as method of moments (MoM) and finite-difference time-domain (FDTD) method excel in their accuracy. ...
... For power-prediction algorithms, techniques based on path-loss formulas [40][41][42][43] lack spatial information and cannot predict the locations of signal peaks and nulls; Full-wave simulations [37][38][39] are of too high computational complexity and are impractical to be used in realistic scenarios; Current ray-tracing-based techniques in the literature [44][45][46][47][48] are not tailored for RFID applications. They do not consider some crucial factors in RFID, such as antennas' irregular radiation patterns, variable AR, random orientations and the system's Introduction uplink calculations. ...
... On the other hand, path-loss (PL) formulas are a group of empirical-statistical models in which only a few parameters are needed such as the distance from the transmitter to the receiver and attenuation factors of individual walls [40][41][42][43]. For instance, the PL model proposed in [43] is denoted as: ...
The low signal coverage problem has long been one of the most crucial problems in UHF RFID systems. In this thesis, the problem is tackled using a combination of antenna design, mathematical modelling and algorithm development. A novel UHF RFID reader antenna with 2D beam-scanning ability, a wide axial ratio (AR) beamwidth and tunable polarisation performance is designed, simulated, measured and tested in Chapter 3 of this thesis. It is experimentally verified that the antenna’s AR minima follow its gain maxima, generating an ultra-wide 3 dB AR beamwidth of 136°. It is demonstrated that the ratio of inventoried tags within 120 seconds increased from 65% with a static beam configuration to 96% with 1D beam-scanning and further to 100% with 2D beam-scanning. By manually degrading the proposed antenna’s AR to 4 dB without affecting other parameters, a maximum 18% degradation in the coverage ratio is observed, verifying the coverage contribution from the proposed antenna’s improved AR performance. To further improve the signal coverage of RFID systems, an optimised reader antenna deployment is necessary. A 3D ray-tracing model tailored for RFID applications is proposed, constructed and verified in Chapter 4 of this thesis. Compared with ray-tracing models in the literature, the proposed model considers practical antennas’ irregular beam patterns, polarisations, arbitrary orientations and variable AR. The proposed model is verified against commercial MoM simulation software and has shown comparable accuracy but orders of magnitude less time and memory consumption. It is also verified using experiments and shows a good match between the prediction and measurement. In the case study presented, the proposed model demonstrates the ability to consider practical antennas’ variable AR, predicting a 13% coverage difference between the AR-optimised antenna and its AR-degraded version, matching the measured value at 10%. Due to the higher power requirement of sensor tags over conventional passive tags, a fast and effective beam-forming algorithm is desirable. A scalable, computationally-light beam-forming algorithm for multi-antenna RFID systems is proposed and experimentally verified in Chapter 5. The proposed algorithm does not rely on iterative phase searching methods, avoiding slow convergence speed and can be implemented with low computational complexity. It is experimentally demonstrated that the proposed algorithm can achieve an RSSI improvement of up to 18 dB using three transmitting antennas. For the signal coverage problem in near-field RFID applications, a simple yet effective near-field antenna design is proposed and verified in Chapter 6 using full-wave simulations. The proposed antenna’s signal nulls can be dynamically moved using two sources with suitable phase differences. Moreover, an almost uniform field distribution along the strip-line can be achieved by setting the phase difference of two sources to be 90° or 270°. Furthermore, by adding a new track of strip-line and setting a proper phase difference, a side-power leakage suppression of up to 20 dB can be achieved with the vertical detection range extended from 43 cm to 65 cm at 30 dBm input power. This theory is further verified by changing the phase difference of S1 and S2 to π, in which the side-leakage gets greatly strengthened as predicted by theory.
... La distance de référence d 0 est choisie la plus proche de l'émetteur, mais suffisamment loin pour être en champ lointain, on prend généralement d 0 = 1m pour les fréquences d'intérêt de cette thèse. En outre, le modèle «Wall and Floor Factor» [15] décrit l'affaiblissement de propagation comme une somme de l'affaiblissement en espace libre et de pertes supplémentaires liées au nombre d'étages et de murs traversés lors de la propagation d'ondes électromagnétiques. Il est plus précis que le modèle à une pente, car il fournit plus de degrés de liberté. ...
... Il a été d'ailleurs normalisé dans les systèmes IEEE 802. 15.3a et IEEE 802. ...
... 15.3a et IEEE 802. 15.4a afin de modéliser les canaux des systèmes ultra-large bande (UWB). ...
Aujourd’hui, une quatrième révolution industrielle, appelée Industrie 4.0, est en marche afin d’assurer la numérisation et l’automatisation des systèmes de production dans un écosystème global respectueux des enjeux climatiques et économiques. Elle s’appuie sur le concept des Systèmes Cyber-Physiques (Cyber Physical Systems, CPS) pour créer des outils de production capables d’interagir avec leur environnement de manière continue via l’association d’éléments physiques, informatiques et de communication. Ces outils de production devront former un écosystème dans le but de coordonner leurs échanges. Dans ces conditions, il est indispensable de se doter d’un réseau industriel sans fil intelligent, capable d’envoyer la bonne information, au bon moment, à la bonne cible. La communication sans fil basée sur les ondes radioélectriques n’est pas nouvelle. Cependant, elle reste problématique dans des environnements industriels pour plusieurs raisons. En effet, de par la spécificité de l’environnement industriel et les contextes d’utilisation des technologies de production, la propagation des ondes électromagnétiques va introduire des phénomènes pouvant impacter la performance des technologies sans fil. Dans ces travaux de recherche, nous étudions l’impact du comportement des ondes électromagnétiques en environnement industriel aéronautique sur la performance des technologies sans fil. Ces études couvrent à la fois les aspects liés au canal de propagation, à la couche PHY et à la Qualité de Service (QoS). Nos travaux prennent en compte la spécificité de l’environnement industriel aéronautique (présence des structures d’avion : fuselage, caisson central, voilure, …) et des contraintes opérationnelles liées aux processus métier dans la définition des principales configurations de transmission à traiter. Ces dernières sont étudiées en s’appuyant conjointement sur des simulations et des expérimentations en situation réelle qui ne pouvaient donc pas être simplifiées. Cela engendre une complexité supplémentaire des expérimentations et de leur comparaison avec les simulations. Notre première contribution concerne la conception de modèles de canaux permettant de prédire l’affaiblissement de la puissance en fonction de la distance et le comportement moyen de la réponse impulsionnelle de chaque configuration de transmission. La deuxième contribution est l’exploitation de ces modèles dans la chaîne de simulation de la couche PHY des technologies 802.11g, 802.11n et 802.11ac afin d’analyser l’influence des canaux à travers le taux d’erreur paquet (PER). Pour aller au-delà de la simulation, nous avons réalisé le déploiement d’un réseau 802.11n afin d’évaluer cette fois-ci l’impact des canaux sur les métriques de QoS de la couche réseau à savoir le débit réel, la latence et le taux d’erreur paquet. Nos travaux se terminent par la proposition d’un système multi-bearers sous forme de perspective qui vise à améliorer la QoS en choisissant de manière intelligente la technologie la plus adaptée au contexte d’opération.
... Ces derniers sont utilisés pour estimer le niveau moyen du signal côté récepteur pour une distance de séparation donnée avec l'émetteur, comme illustré par la Figure 2. Parmi les modèles de path loss indoor existants, deux ont été choisis pour les travaux de cette thèse, principalement en raison de leur simplicité. Il s'agit du modèle log-distance qui représente le path loss comme étant une fonction linéaire croissante selon le logarithmique de la distance, et du modèle de Motley-Keenan [1] qui, en plus de la distance, tient compte du nombre de murs/étages traversés par le trajet direct reliant l'émetteur et le récepteur. Pour être utilisables, ces modèles ont besoin d'être calibrés par le biais de mesures du canal de propagation dans l'environnement considéré. ...
... The Motley-Keenan model [1] is similar to the LAM model [15] except that the exponentially-increasing loss factor is replaced by the attenuation induced by the number of walls and floors crossed by the direct path between the transmitter and the receiver. The path loss is given by: ...
... Based on the average path loss computed at different Rx locations and frequency subbands, three indoor path loss models have been established. The first one is a log-distance model and the other ones are based on the Motley-Keenan model [1]. These models did not remove the Tx and Rx antennas gain and are available for ℎ = 2.30 m. ...
The constant evolution of wireless technologies such as Wi-Fi, mobile networks standards or IoT, has given rise to new applications and usages. The possibilities offered by this multitude of alternatives are exploited by heterogeneous wireless networks which, by combining within a single network several technologies, provide the users with a seamless access to complementary services. However, to take full advantage of these benefits, there are several technical issues to address. One of them is related to the deployment of these multi-technology networks. In practice, this task relies, most of the time, on radio network design software to achieve optimal planning. In such context, the main objective of this thesis is to establish models which can be used by radio network planning tools in order to the deployment of multi-technology wireless local area networks. This task has involved calibrating propagation models for radio coverage estimation, in residential indoor environments from 800 MHz to 60 GHz; developing a throughput model for Wi-Fi capacity estimation based on uplink and downlink traffic; and establishing a multi- objective resolution model to optimize the positioning of access points operating at 5 and 60 GHz. Moreover, this thesis also proposes practical recommendations for a better positioning of access points during deployment phases. This task has been achieved through coverage sensitivity studies to various factors, such as the transmitter surroundings or the presence of obstructing people.
... • Other Propagation Models: Considering different aspects, researchers have proposed a variety of propaga-tion models. Including some famous models, such as Floor Attenuation Factor Path Loss Model [11], which considers the attenuation caused by different types of buildings and obstacles; Keenan-Motley model [12], which mainly considers the influence of reflection of signals on walls, floors, etc; Multi-wall model [13], which concentrates on the refraction of the wall surface corresponding to the influence of wireless signal propagation; Two-Ray model [14], which considers that all kinds of environment have one reflecting surface. All of these models can simulate the weakness of wireless signals in certain environments. ...
... In (15), RSSI (d) is the derivative of inverse function of the ranging function in (12). Therefore, ∆RSSI presumably less than 0.2db in practical. ...
... In order to determine the parameter of N shown in (12) and verify the performance of the proposed algorithm, the positioning experiment is designed. In this section, we will introduce our environment of experiment and show the result and performance of proposed positioning algorithm. ...
With the development of the mobile Internet, the demand for indoor location based services(ILBS) is increasing. Applications and devices in indoor environments can determine their position based on Received Signal Strength Indication(RSSI) of bluetooth Beacons. However, because of multipath effects, shadow fading and the blockage of obstacles, RSSI values are unstable for positioning. The propagation model are various in different environments, which have caused great difficulty in highprecision indoor positioning. In this paper, a novel positioning algorithm based on cellular network and bluetooth Beacon’s RSSI is proposed for ILBS. The whole algorithm is divided into two parts: Offline Preparation and Online Positioning. During Offline Preparation, Beacon node is cellular networked in regular quadrilateral; a universal ranging model is derived from traditional ranging model for high-precision positioning. During Online Positioning, missing RSSI values are replaced firstly; next, Outliers Removed Median-Kalman Filter is used to process RSSI, which makes the signal smoother to range; then, the cell in which the mobile terminal is located is determined according to the strongest four RSSI values; after that, using filtered RSSI, distances without height influence could be calculated; finally, Weighted Multi-Point Positioning Algorithm With Cellular Network Assistance is used to calculate the real-time location of the mobile terminal. Experiment results show that our algorithm achieves average accuracy in 0.3m..0.5m and limits the maximum error within 0.8 m.
... One such example is the DPM, where only the shortest (least attenuated) free space path is considered, which leads to the consideration of only diffractions and thus to the omission of reflections altogether, presumably reducing complexity without signifi-cantly compromising accuracy [47]. Among many, another notable example of semi-deterministic models is the widely used and improved Motley-Keenan multi-wall model [49], [50] specialized for indoor settings, which has been shown to provide relatively close pathloss prediction accuracy to more complex ray tracing methods. ...
... Remark 2. In DeepRay [68] and EM DeepRay [58], the Motley-Keenan multi-wall model [49], [50] was shown to yield not too inferior performance in comparison to uncalibrated ray tracing and the presented deep learning-based methods before calibration, while suffering from longer computation times than the deep learning-based method due to its usual non-parallelized implementation, i.e., pathloss for each pixel is computed serially, as we also observed in the implementation of a baseline tomography method in our RadioUNet paper [3]. We would like to point out that an efficiently parallelized GPU-enabled computation of such algorithms might be feasible, e.g. as was showcased by one of the challenge teams [84], [24] in calculating their fractional LOS maps using the CuPy library [85]. ...
Pathloss quantifies the reduction in power density of a signal radiated from a transmitter. The attenuation is due to large-scale effects such as free-space propagation loss and interactions (e.g., penetration, reflection, and diffraction) of the signal with objects such as buildings, vehicles, trees, and pedestrians in the propagation environment. Many current or planned wireless communications applications require the knowledge (or a reliable approximation) of the pathloss on a dense grid (radio map) of the environment of interest. Deterministic simulation methods such as ray tracing are known to provide very good estimates of pathloss values. However, their high computational complexity makes them unsuitable for most of the applications envisaged. To promote research and facilitate a fair comparison among the recently proposed fast and accurate deep learning-based pathloss radio map prediction methods, we have organized the ICASSP 2023 First Pathloss Radio Map Prediction Challenge. In this overview paper, we describe the pathloss radio map prediction problem, provide a literature survey of the current state of the art, describe the challenge datasets, the challenge task, and the challenge evaluation methodology. Finally, we provide a brief overview of the submitted methods and present the results of the challenge.
... Keenan and Motley [10] formulated a radio coverage predicted model based on a few building parameters. They specified the path loss in decibels as ...
... may be calculated for a known value of kL if a as a function of (') is known. To determine a + (') and a -('), we use a n N 10) in which N are the integers which most nearly satisfy the four equations (3.12) 46 N + and Nmay each have two separate values in a given problem and ...
With the imminent introduction of Personal Communication Services, indoor wireless systems will be used in a large variety of office, factory, residential and hospital environments. To ensure satisfactory performance of an indoor wireless communication system, it is important to characterise the indoor radio propagation channel. Site measurement can be costly; propagation models have been developed as a suitable low-cost alternative. Many models have been proposed but they are either relying on large volume of statistical data or depending of considerable computing power. Furthermore they do not account for dynamic effect of human movements within an indoor environment. However, the people movements have been found to cause significant fades in received signal. The thesis is aimed at development of a novel indoor propagation model for characterisation of indoor electromagnetic wave propagation. The model is targeted to run in a portable personal computer and will include the effect of human movements as well. Five research questions were then risen. They are : 1. “How to work out the electromagnetic propagation in an indoor environment ?”; 2. “How to capture the drawings of environments to be accessed by the model ?”; 3. “How do we model the dynamic effects of people activities in indoor environments ?”; 4. “How can we implement an efficient and accurate site-specific propagation model in a personal computer ?” and 5. “How much experimental verification is necessary for complete validation of model ?”.
In this thesis, a new ray tracing technique called “Geometrical-image ray tracing technique” is created. This technique uses the 3D geometry to derive general formulae for ray tracing of large number of multiple reflection between two parallel plane surfaces. An image method is employed for multiple reflection between non-parallel planes. The combination of 3D geometry and image method significantly simplifies the ray tracing algorithm. In order to broaden the model application range, the proposed model is supplemented with UTD so that diffraction in lower RF frequency can be taken into account to improve the model accuracy. These works give the answer to research question 1.
Dynamic effect of people activities in indoor radio signal propagation is simulated by movement of human model. Human body is modelled by four rectangular blocks and characterised by dielectric constant. This work answer research question 3.
The model has been developed in a Microsoft Windows application software package. This package provides an easy method to input the indoor environmental layout, parameters and locations of radio port. Research question 2 and 4 are then answered.
The performance of the propagation model in predicting signal distribution has been verified by three experiments performed in different typical indoor environments. The results showed that the propagation model can correctly predict the signal distribution trend. The accuracy of rms time delay calculation was tested by comparison with a measurement result. The difference of 9.7 ns between calculated and measured values is observed. The model can calculate rms time delay spread with reasonable accuracy provided that no significant objects are neglected in simulation. These works give answer to research question 5.
The model has been applied to study the propagation characteristics in typical environments. The results of study give useful guidelines for radio engineers in the design and installation of indoor radio systems.
The objectives of research program are achieved and the research questions have been answered. The indoor propagation model developed in this thesis is a practicable model for characterising electromagnetic propagation indoors. It has shown that it is an economical, efficient and reasonably accurate propagation model.
... The main target of this paper is to understand, the performance of some popular indoor path loss models at millimetre wave frequencies. Many indoor path loss models have been studied in literature, some models consider free-space loss along with losses due to walls and floors like Motley Keenan Model (MKM) [19], averaged wall loss model (AWM) [7], ITU-R P.1238 model [20], COST231 indoor model [21], and enhanced COST231 [22]. Another set of models use free space propagation model with different values for the path loss exponents (PLE) like single slope model (SSM) [23], two slope model (TSM) [24], and partitioned model (PM) [25]. ...
... In Motley-Keenan Model, losses are estimated by considering the free space propagation loss in addition to the effect of walls and floors [19], ...
In this paper, a comparative study between different indoor path loss prediction models is conducted. The investigated models include averaged wall loss model (AWM), single slope model (SSM), linear attenuation model (LM), two slope model (TSM), partitioned model (PM), and Motley-Keenan model (MKM). The models were tested in a simulated environment of the 3 rd floor of Chesham building, the University of Bradford, a different set of frequencies were used including 28 GHz, 60 GHz, and 73.5 GHz, TSM shows the best performance, both AWM and MKM tend to have a similar performance at millimetre-frequencies, both models' prediction for corridor and LOS regions are pessimistic while TSM, SSM, and LM have better estimations in these regions. Index Terms ─ Indoor path loss models, millimetre-wave frequencies, Motley Keenan model, ray tracing, received signal strength, single slope model, two slope model.
... That is, the sending power P TX of the sensor node is still greater than or equal to the receiving power P TSH of the sink node after passing through the energy PL of the part lost in the transmission process. We set sink j (0<j <= p) as a node in the set SINK, and use the multi-wall model (MWM) proposed by Keenan and Motley (1990) to obtain the path loss formula is: ...
At present, wireless sensor networks are developing rapidly, but they will also face many challenges. For example, in the deployment problem, many problems such as cost, coverage, connectivity, energy, network life cycle and so on need to be considered, while the traditional multi-objective algorithm does not perform well in dealing with many-objective problems. How to quickly find high-quality solutions is the focus of research today. This paper proposes a deployment method for wireless sensor networks based on MaOEA/P-GM algorithm. This method improves the mutation strategy of the algorithm according to the characteristics of wireless sensor network deployment based on the many-objective algorithm MaOEA/P. Experiments show that using this algorithm in a many-objective environment can quickly get a high-quality solution set with fewer nodes, high coverage, good connectivity, and balanced energy consumption.
... Most indoor models use a logarithmic decay of distance combined with losses induced by obstacles. The first method presented in Table 6 is the Motley-Keenan model [113], where is the number of floors in the propagation path, is the floor attenuation in dB, is the number of walls in the propagation path, and is the wall attenuation in dB. The attenuation with distance follows the free-space model, and the obstacles only affect the parameter. ...
LoRa systems are emerging as a promising technology for wireless sensor networks due to their exceptional range and low power consumption. The successful deployment of LoRa networks relies on accurate propagation models to facilitate effective network planning. Therefore, this review explores the landscape of propagation models supporting LoRa networks. Specifically, we examine empirical propagation models commonly employed in communication systems, assessing their applicability across various environments such as outdoor, indoor, and within vegetation. Our investigation underscores the prevalence of logarithmic decay in most empirical models. In addition, we survey the relationship between model parameters and environmental factors, clearing their nuanced interplay. Analyzing published measurement results, we extract the log-distance model parameters to decipher environmental influences comprehensively. Drawing insights from published measurement results for LoRa, we compare them with the model’s outcomes, highlighting successes and limitations. We additionally explore the application of multi-slope models to LoRa measurements to evaluate its effectiveness in enhancing the accuracy of path loss prediction. Finally, we propose new lines for future research in propagation modelling to improve empirical models.
... Cependant, ils ne sont pas très précis. Les modèles semi-déterministes [2][3] considèrent des mesures radio à différentes positions pour calibrer les paramètres du modèle et quelques informations sur l'environnement afin de prédire l'affaiblissement. Ces modèles représentent un bon compromis entre simplicité et précision. ...
La prédiction de cartes de couvertures radio en indoor et en outdoor reste un défi de grand intérêt grâce au grand nombre d’applications qu’elle permet. De nombreuses méthodes existent pour cette tâche. Cependant, chacune d’elle a ses limites(temps de calcul, précision, niveau de détails requis en entrée, généralisation à différents environnements). De plus, le problème semble moins étudié en indoor qu’en outdoor. Dans cet article, nous proposons un modèle multi-matériaux pour la prédiction de cartes radio indoor à l’aide de réseaux de neurones antagonistes génératifs (cGAN) et d’images de plan en entrée. La validité et l’efficacité de notre méthode sont vérifiées sur des données simulées. Les résultats numériques montrent que notre approche est plus performante que les méthodes de l’état de l’art.
... Semi-deterministic path loss models consider measurements at given positions to calibrate the model parameters and a few information on the environment in order to predict the path loss. Motley Keenan's [7] and Dominant Path Model (DPM) [8] models are examples of this category. These models represent a good balance between simplicity and precision. ...
... WSN can be well used for forest protection and timely prevention of fires. With the development of smart homes [3], more and more homes and offices deploy WSN to control indoor temperature, light, humidity, and flow of people [4]. In addition, in some industrial production scenarios, WSN can be deployed to detect essential parameters in the production process. ...
Wireless Sensor Network (WSN) is a powerful tool to help humans monitor a specific area, and the deployment strategy of sensors profoundly determines the performance of WSN. How to find the best deployment method has become the research topic for many scholars. The deployment strategy aims to expand the deployment scope, reduce energy consumption, and reduce duplicate coverage areas. Many multiobjective heuristic algorithms have been proposed to solve this problem. This paper proposes a multiobjective adaptive fish migration optimization (MAFMO) algorithm, which adds an adaptive-based repository and crowding degree-selection strategy for multiobjective optimization. The simulation results reveal that the MAFMO algorithm has more advantages in malleability and distribution than other famous algorithms. Finally, the algorithm is applied to the WSN deployment problem, and the simulation results are compared with other algorithms. The results show that a better solution can be found using MAFMO.
... Next, we apply the Floor Attenuation Factor (FAF) model originally presented in [45] and [46]. The simple idea is to add a predetermined attenuation factor that changes depending on the number of penetrated floors. ...
Packet-based simulation is a key tool for the research and development of Vehicular Ad-hoc Networks (VANETs). Over the last decade, many models throughout the communication stack have been presented, which have increased the degree of realism that can be achieved with popular simulation frameworks. Nevertheless, the three-dimensional aspects of many real-world traffic situations barely find consideration. In this paper, we present a holistic approach to simulate large-scale three-dimensional VANET scenarios. We briefly summarize our previously presented models covering different aspects of communication in 3D scenarios, including an environmental diffraction model, an n-ray ground interference model, and the consideration of multi-floor communication. We then describe the principle of a model selector, which applies the appropriate models depending on the environment of the currently transmitted packet. Subsequently, we use the outlined methodology implemented in our Veins 3D framework to simulate a large urban reference scenario. The results differ significantly from comparable 2D simulations, demonstrating the necessity of three-dimensional considerations. However, they also show strongly increased execution times. Therefore, we further suggest different approaches to improve the simulation performance. Based on these optimizations, simulation durations in the same order of magnitude as a comparable 2D simulation can be achieved.
... That is, the sending power P T X of the sensor node is still greater than or equal to the receiving power P T SH of the sink node after passing through the energy PL of the part lost in the transmission process. We set sink j (0<j <=p) as a node in the set SINK, and use the multi-wall model (MWM) proposed by Keenan et al. (1990) to obtain the path loss formula is shown in Eq. (5). ...
At present, wireless sensor networks are developing rapidly, but they will also face many challenges. In the deployment problem, many problems such as cost, coverage, connectivity, energy, network life cycle and so on need to be considered, while the traditional multi-objective algorithm does not perform well in dealing with many-objective problems. How to quickly find high-quality solutions is the focus of research today. This paper proposes a deployment method for wireless sensor networks based on a many-objective evolutionary algorithm with guided mutation. This method improves the mutation strategy of the algorithm according to the characteristics of wireless sensor network deployment based on a many-objective evolutionary algorithm based on the projection plane. Experiments show that using this algorithm in a many-objective environment can quickly get a high-quality solution set with fewer nodes, high coverage, good connectivity and balanced energy consumption.
... Then, by comparison we conclude that for 7-channels case the interference effect is even lower. The Keenan-Motley [18] pathloss model is considered for link budget analysis; this model is formulated based on the number of walls and floors between the TX and RX endpoints and their corresponding losses: ...
Wi-Fi spectrum scarcity is a challenge for popular wireless applications that require a high data rate, low latency, and high reliability in different environments. AR/VR applications for e-education in a school is a good example of a challenging scenario where a large number of AR/VR devices have high data rate and latency-sensitive traffic, and require reliable wireless connectivity. In order to accommodate such emerging applications, several leading countries including the USA, South-Korea, Brazil and Canada released 1200 MHz of the spectrum in the 6 GHz band for the unlicensed use cases. Other countries, including European Union member states, only released the lower 500 MHz of the 6 GHz band and have yet to decide on the future use of the upper 6 GHz band. In this paper, we quantify the impact of spectrum scarcity on the feasibility of the AR/VR applications for e-education. Practically, we compare the maximum number of AR/VR devices supported in each classroom of a given school, depending on whether 500 MHz or 1200 MHz are available for unlicensed use cases.
... There are several models that tediously find special parameters that are environment-dependent [51]. Because the simulation of signal propagation is too computationally expensive and noisy, strong model simplifications are required. ...
Sensors have become ubiquitous in buildings but are rarely connected to a network, and their potential to analyse the performance, use, and interaction with a building is not yet fully realised. In the coming years, we expect sensors in buildings to become part of the Internet of Things (IoT) and grow in numbers to form a Dense Indoor Sensor Network (DISN) that allows for unprecedented analysis of the performance, use, and interaction with buildings. Multiple technologies vie for leading this transformation. We explore Long Range Wide Area Network (LoRaWAN) as an alternative for creating indoor sensor networks that extends beyond its original long-distance communication purpose. For the present paper, we developed a DISN with 390 sensor nodes and four gateways and empirically evaluated its performance for two years. Our analysis of more than 86 million transmissions revealed that DISNs achieve a much lower distance coverage compared to estimations from previous research indicating that more gateways are required. In addition, the deployment of multiple gateways decreased the loss of transmissions due to environmental and network factors. Given the complexity of our system, we received few colliding concurrent messages, which demonstrates a gap between the projected requirements of LoRaWAN systems and the actual requirements of real-world applications given sufficient gateways. We also contribute to the modelling of transmissions with our comparison of attenuation models derived from multiple methodologies. Across all models, we find that robust coverage in an indoor environment can be maintained by placing a gateway every 30 m and every 5 floors. Finally, we also investigate the application of DISNs for the passive sensing and visualization of human presence using a Digital Twin (DT) and a Fused Twins (FT) representation in Augmented Reality (AR). A passive sensing approach allows us to gather relevant data on human use of a building while still preserving privacy via the aggregation process. Immersive in situ visualizations in FT allow for new interactions and new forms of participation. We conclude that DISNs are already technologically feasible today and basing them on Low Power Wide Area Network (LPWAN) offers intriguing possibilities to reduce energy consumption, maintenance cost, and bandwidth use while also enabling new forms of human-building interaction.
... This is a well-known and commonly used model for indoor environments. It combines One-Slope and Motley-Keenan models [39]. The multiwall model was chosen as it is less complex than ray tracing. ...
Numerous indoor positioning technologies and systems have been proposed to localize people and objects in large buildings. Wi-Fi and Bluetooth positioning systems using fingerprinting have gained popularity, due to the wide availability of existing infrastructure. Unfortunately, the implementation of fingerprinting-based methods requires time-consuming radio surveys to prepare databases (RSSI maps) that serve as a reference for the radio signal. These surveys must be conducted for each individual building. Here, we investigate the possibility of using simulated RSSI maps with fingerprinting-based indoor localization systems. We discuss the suitability of the two popular radio wave propagation models for the preparation of RSSI reference data: ray tracing and multiwall. Based on an analysis of several representative indoor scenarios, we evaluated the performance of RSSI distribution maps obtained from simulations versus maps obtained from measurement campaigns. An experimental positioning system developed by the authors was used in the study. Based on Bluetooth Low Energy beacons and mobile devices (smartphones), the system uses fingerprinting followed by a particle filter algorithm to estimate the user’s current position from RSSI measurements and a reference spatial RSSI distribution database for each Bluetooth beacon in the building. The novelty of our contribution is that we evaluate the performance of the positioning system with RSSI maps prepared both from measurements and using the two most representative indoor propagation methods, in three different environments in terms of structure and size. We compared not only the three RSSI maps, but also how they influence the performance of the fingerprint-based positioning algorithm. Our original findings have important implications for the development of indoor localization systems and may reduce deployment times by replacing reference measurements with computer simulations. Replacing the labor-intensive and time-consuming process of building reference maps with computer modeling may significantly increase their usefulness and ease of adaptation in real indoor environments.
... Although the WHIPP network planning tool also features common and simple path loss models like one-slope models or the Motley-Keenan multi-wall model [35], the Indoor Dominant Path Loss (IDP) model [12,33,34] was specifically designed for more accurate path loss estimations. This model forms a compromise between semi-empirical models, only considering the direct ray between transmitter and receiver, and ray-tracing models, where hundreds of rays and their interactions with the environment are investigated. ...
Accurate wireless network planning is crucial for the deployment of new wireless services. This usually requires the consecutive evaluation of many candidate solutions, which is only feasible for simple path loss models, such as one-slope models or multi-wall models. However, such path loss models are quite straightforward and often do not deliver satisfactory estimations, eventually impacting the quality of the proposed network deployment. More advanced models, such as Indoor Dominant Path Loss models, are usually more accurate, but as their path loss calculation is much more time-consuming, it is no longer possible to evaluate a large set of candidate deployment solutions. Out of necessity, a heuristic network planning algorithm is then typically used, but the outcomes heavily depend on the quality of the heuristic. Therefore, this paper investigates the use of Machine Learning to approximate a complex 5G path loss model. The much lower calculation time allows using this model in a Genetic Algorithm-based network planning algorithm. The Machine Learning model is trained for two buildings and is validated on three other buildings, with a Mean Absolute Error below 3 dB. It is shown that the new approach is able to find a wireless network deployment solution with an equal, or smaller, amount of access points, while still providing the required coverage for at least 99.4% of the receiver locations and it does this 15 times faster. Unlike a heuristic approach, the proposed one also allows accounting for additional design criteria, such as maximal average received power throughout the building, or minimal exposure to radiofrequency signals in certain rooms.
... Les auteurs de ce modèle, A.J. Motley et J.M. Keenan ont constaté que dans un environnement de type bureau, l'affaiblissement de propagation du signal correspondait à la propagation en espace libre auquel il fallait ajouter les affaiblissements correspondant à la traversée de chaque étage et de chaque mur qui se trouve sur le trajet direct [KM90]. ...
Products meeting the IEEE 802.11b and 802.11g (2.4 GHz band) and 802.11a (5 GHz band) standards are currently marketed and deployed in public places (hot spot areas) and also in private homes (ADSL WIFI terminals). If currently the systems operating in the 2.4 GHz band dominate the market, the increase in traffic could lead to the saturation of this band (only 3 separate channels) and also lead operators to move towards the 5 band. GHz. The different WLAN standards make it possible to provide raw speeds ranging from 1 to 54 Mbits/s (or even more than 100 Mbits/s with 802.11n being standardized). They therefore technically offer a large number of deployment possibilities. One of the difficulties for operators is choosing the appropriate standard based on deployment constraints for coverage and capacity. As traffic increases, densification needs also appear, which must be met with the appropriate standards. It is essential to be able to identify their limitations, in order to better guarantee the quality of service on the networks currently deployed and above all to foresee the problems which may appear during the increase in load as and when usage increases.The subject of the thesis therefore relates to a detailed analysis of the limitations of WLAN networks based on various selection criteria, including in particular the range, capacity and robustness to interference. It is then a question of concluding on recommendations and engineering rules for their deployment in areas of high traffic density. For systems operating in the 2.4 GHz band, which is a free band, interference between equipment of different standards and also between networks of competing operators are the key factors limiting the quality of service and data rates. The first step is to identify the possible sources of interference in the 2.4 GHz and 5 GHz bands, and to model the main parameters related to the jammers considered in the link budget and coverage calculations. The experimental approach was adopted to characterize the effect of jammers on the performance of 802.11 systems. A jammer model was extracted from our measurements and then we used a statistical approach to provide engineering rules to guarantee the performance of WLAN networks. At the same time, we have developed an 802.11 network simulator to realistically take into account the phenomena of WLAN propagation and interference. Thanks to this simulator, we studied the performance of these networks in a multi-user context and the effects of scaling up. The results obtained were compared to our measurements and to theoretical models.
... The model offers a fast and easy way to predict loss of path in an indoor environmental quality. Therefore, this was useful for predicting the primary coverage (Keenan and Motley 1990). ...
Background
The development of powerful and flexible management addresses is due to the improvement of deeply reliable gadgets and the advancement of the concept of cellular. The cellular principle was a major way of solving the wavelength crowding problem and the user capacity. It offered high capacity without major technological changes with limited allocation in spectrum. Wireless communication is an innovation in media transmission that allows remote transmission in all types of terrain between convenient gadgets. For estimating a transmitter 's radio coverage area, propagation models that anticipate the mean signal strength for an arbitrary transmitter–receiver separation distance are crucial as they are called large-scale propagation models so even though they define the average signal strength over long periods of time and large distances from the transmitter.
Results
Developed propagation models are presented according to the measured path loss values in exemplary urban and suburban areas at the operating frequency of 3.5 ghz by using the regression analysis. The measurements are implemented by using a spectrum analyzer FSH6 to get the channel response as shown in the stated tables and graphs. Based on the obtained results, it was observed that the path loss could be calculated as a function of distance and during the practical measurements 32 m was precise as a presumption for the break point distance. The values of path loss exponent ( n ) are defined and calculated for both of urban and suburban regions. Measurements results are analyzed and compared in order to study their influence for every specific environment. It was noticed that any radio signal will suffer attenuation when it travels from the transmitter to the receiver as a variety of various phenomena give rise to this radio path loss.
Conclusions
The interaction between both the electromagnetic radiation and the environment tends to decrease the quality of the signal being sent from the transmitter to the destination which causes the loss of the path. Propagation models are the basis for channel estimation, as they attempt to identify how a radio transmission changes from the transmitter to the receiver throughout its path. The gained results from this research will be supportive for the arrangement of network planners and researchers as proof and directory materials before future location establishment.
... As atividades de implementação prática desempenham um papel importante no ensino de engenharia, tendo resultados significativos na eficiência de aprendizagem, também é possível notar que resultados abstratos podem obter melhor efeito quando acompanhados de ilustrações gráficas ao invés de equações matemáticas clássicas (DUAN et al., 2015). Neste sentido foi utilizado o PyLayers, um simulador dinâmico para propagação e localização indoor baseado na descrição de gráficos (AMIOT et al., 2013) KEENAN, 1990). ...
... where f is the carrier frequency in Hz, and h t , h r are transmitter and receiver heights in meters. For a moderately sized city, Subsequent to this, other models were developed such as the COST 231 Walfish-Ikegami model [49,50] and the Motely-Keenan model [51], respectively. The former model is also suitable for microcells and small macrocells, since it has fewer restrictions on the distance between the BS and MS, as well as antenna heights. ...
Propagation models constitute a fundamental building block of wireless communications research. Before we build and operate real systems, we must understand the science of radio propagation, and develop channel models that both reflect the important propagation processes and allow a fair comparison of different systems. In the past five decades, wireless systems have gone through five generations, from supporting voice applications to enhanced mobile broadband. To meet the ever increasing data rate demands of wireless systems, frequency bands covering a wide range from 800 MHz to 100 GHz have been allocated for use. The standardization of these systems started in the early/mid 1980s in Europe by the European Telecommunications Standards Institute with the advent of Global System for Mobile Communications. This motivated the development of the first standardized propagation model by the European Cooperation in Science and Technology (COST) 207 working group. These standardization activities were continued and expanded for the third, fourth, and fifth generations of COST, as well as by the Third Generation Partnership Project, and the International Telecommnunication Union. This paper presents a historical overview of the standardized propagation models covering first to fifth-generation systems. In particular, we discuss the evolution and standardization of pathloss models, as well as large and small-scale fading parameters for single antenna and multiple antenna systems. Furthermore, we present insights into the progress of deterministic modelling across the five generations of systems, as well as discuss more advanced modelling components needed for the detailed simulations of millimeter-wave channels. A comprehensive bibliography at the end of the paper will aid the interested reader to dig deeper.
... Previous research on radio propagation in indoor environments [28] represented all penetrated walls, using individual penetration losses depending on their category, which was classified in terms of the thickness and material. Walls within the same category were found to contribute a constant loss, irrespective of whether other walls or floors had been penetrated before. ...
Over the past few decades, attempts had been made to build a suitable channel prediction model to optimize radio transmission systems. It is particularly essential to predict the path loss due to the blockage of the signal, in indoor radio system applications. This paper proposed a multiwall path-loss propagation model for an indoor environment, operating at a transmission frequency of 2.45 GHz in the industrial, scientific, and medical (ISM) radio band. The effects of the number of the walls to be traversed along the radio propagation path are considered in the model. To propose the model, the previous works on well-known indoor path loss models are discussed. Then, the path loss produced by the intervening walls in the propagation path is measured, and the terms representing the loss factors in the theoretical pathloss model are modified. The analyzed results of the path loss factors acquired at 2.45 GHz are presented. The proposed path-loss model simplifies the loss factor term with an admissible assumption of the indoor environment and predicts the path-loss factor accurately.
... Subsequent to this, other models were developed such as the COST 231 Walfish-Ikegami model [47,48] and the Motely-Keenan model [49], respectively. The former model is also suitable for microcells and small macrocells, since it has fewer restrictions on the distance between the BS and MS, as well as antenna heights. ...
Propagation models constitute a fundamental building block of wireless communications research. Before we build and operate real systems, we must understand the science of radio propagation, and develop channel models that both reflect the important propagation processes and allow a fair comparison of different systems. In the past five decades, wireless systems have gone through five generations, from supporting voice applications to enhanced mobile broadband. To meet the ever increasing data rate demands of wireless systems, frequency bands covering a wide range from 800 MHz to 100 GHz have been allocated for use. The standardization of these systems started in the early/mid 1980's in Europe by the European Telecommunications Standards Institute with the advent of Global System for Mobile Communications. This motivated the development of the first standardized propagation model by the European Cooperation in Science and Technology (COST) 207 working group. These standardization activities were continued and expanded for the third, fourth, and fifth generations of COST, as well as by the Third Generation Partnership Project, and the International Telecommunication Union. This paper presents a historical overview of the standardized propagation models covering first to fifth-generation systems. In particular, we discuss the evolution and standardization of pathloss models, as well as large and small-scale fading parameters for single antenna and multiple antenna systems. Furthermore, we present insights into the progress of deterministic modelling across the five generations of systems, as well as discuss more advanced modelling components needed for the detailed simulations of millimeter-wave channels. A comprehensive bibliography at the end of the paper will aid the interested reader to dig deeper.
... In the described setting, the density balance is low as users are concentrated in a small area and the APs in the conference room have many users to serve while other APs are idle. We set the controller period to 1. 4 We model the user-AP links using the Keenan-Motley model [51]. The channel SNRs are updated at the beginning of each time slot based on the user's location and the channel model. ...
... The wide range of values of n makes the use of the simplified path loss model (one slope model) inadequate and hence these authors proposed other models to be considered for the effect of walls and floors, including consideration of their types and number. The loss in dB is given by [75,76]: (9) where (L FS , L C , N w , N f , L w , L f , i, j) are the free space loss, constant term (loss at d 0 = 1m), number of walls, number of floors, wall loss factor, floor loss factor, type of wall and type of floor respectively. It is noteworthy that L w and L f were found to be lower as the number of interleaving walls or floors increased [77,78]. ...
A survey of indoor propagation characteristics is presented, including different models for path loss, shadowing and fast fading mechanisms, different channel parameters including signal strength, power delay, coherence bandwidth, Doppler spread and angle of arrival. The concepts of MIMO channels are also covered. The study also explores many types of deterministic channel modelling, such as Finite Difference Time Domain, Finite Integration Method, Ray tracing and the Dominant path model. Electromagnetic properties of building materials, including frequency dependence, are also investigated and several models for propagation through buildings are reviewed.
... It is probably because the thickness of glass in [18] is different from that in our experimental building which is about 2cm. It is also interesting to note that the average FAF is not a linear function of the number of floors between the transmitter and receiver as also found in [19], [20]. It is possible that different floors cause different amounts of path loss, and there may be other factors such as multi-path reflections from surrounding buildings that affect the path loss. ...
In recent years, we have witnessed the rapid development of LoRa technology, together with extensive studies trying to understand its performance in various application settings. In contrast to measurements performed in large outdoor areas, limited number of attempts have been made to understand the characterization and performance of LoRa technology in indoor environments. In this paper, we present a comprehensive study of LoRa technology in multi-floor buildings. Specifically, we investigate the large-scale fading characteristic, temporal fading characteristic, coverage and energy consumption of LoRa technology in four different types of buildings. Moreover, we find that the energy consumption using different parameter settings can vary up to 145 times. These results indicate the importance of parameter selection and enabling LoRa adaptive data rate feature in energy-limited applications. We hope the results in this paper can help both academia and industry understand the performance of LoRa technology in multi-floor buildings to facilitate developing practical indoor applications.
... 1) Modified Keenan-Motley Model: also named as multiwall model, it was proposed in COST 231 [2] and gives the path loss as the free space loss added with losses introduced by the walls and floors penetrated by the direct path between the transmitter and the receiver. The modification inserted in the Keenan-Motley model [3] is a floor correction gain and the possibility of using different types of wall and floors. The path loss (L) equation used in our tests, with only walls on between the transmitter and the receiver is: ...
... Moreover, environment specific models concerning physical details provided by building drawings have also been developed [11]. For example, [12] and [13] provide a simple way of path loss prediction by counting the number of partition walls on the line segment between transmitter and receiver, and using empirically derived attenuation factors on each wall for correction. However, to our best knowledge, there is no study on the propagation model which is applicable to the "above-ceiling" environment. ...
We have been working on automatic location estimation of HVACs utilizing the RSSI of BLE (Bluetooth Low Energy) to improve the time-consuming process in the HVAC system network setting where technicians need to identify the location of each HVAC one by one to assign a network address to the HVAC. This short paper particularly reports an initial attempt of training a BLE propagation prediction model adaptive to "above-ceiling" environment, which is a key enabler for automation of the assignment process. Based on the 1.3 million RSSI sample data collected in a real building for one week, we trained the model with different parameters and discovered that RMSE of RSSI prediction has the following trend: 1) it decreases with the introduction of the obstacle features-the number of beams and the number of HVAC machines, and 2) it decreases with the increase of polynomial term degree. The best model so far has an RMSE of 4.832 dBm tested by 10-fold cross-validation. The methodology and quantified result of this initial attempt provide reference not only for the network assignment process but also for building BLE-mesh networks in the above-the-ceiling environment, which can be exploited for HVACs management or sensor data aggregation.
... Using the Motley-Keenan model [14], LP|dB is computed as: ...
LoRa (Long Range) is one of the most promising candidate technology for Internet of Things (IoT). It supports a high number of communication devices spread across large areas. In this paper, we present some indoor measurements performed in a standard office environment using LoRa links. The aims of the work is to assess the indoor propagation performance of LoRa technology and to indicate the best model to be used for a preliminary design of a LoRa based radio link in an office environment. The measured data highlights that LoRa technology can be used in office environment to realize a wireless sensor network. Five commonly used propagation models were also analyzed and their results compared with the measurements. This analysis highlighted that the Motley-Keenan's is the best model to describe indoor propagation.
... It is probably because the thickness of glass in [18] is different from that in our experimental building which is about 2cm. It is also interesting to note that the average FAF is not a linear function of the number of floors between the transmitter and receiver as also found in [19], [20]. It is possible that different floors cause different amounts of path loss, and there may be other factors such as multi-path reflections from surrounding buildings that affect the path loss. ...
In recent years, we have witnessed the rapid development of LoRa technology, together with extensive studies trying to understand its performance in various application settings. In contrast to measurements performed in large outdoor areas, limited number of attempts have been made to understand the characterization and performance of LoRa technology in indoor environments. In this paper, we present a comprehensive study of LoRa technology in multi-floor buildings. Specifically, we investigate the large-scale fading characteristic, temporal fading characteristic, coverage and energy consumption of LoRa technology in four different types of buildings. Moreover, we find that the energy consumption using different parameter settings can vary up to 145 times. These results indicate the importance of parameter selection and enabling LoRa adaptive data rate feature in energy-limited applications. We hope the results in this paper can help both academia and industry understand the performance of LoRa technology in multi-floor buildings to facilitate developing practical indoor applications.
... Le modèle Motley-Keenan [68] est aussi utilisé pour analyser la propagation des ondes en milieu indoor. Ce modèle de prédiction empirique tient compte de l'influence des murs mais aussi des étages sur le signal sur la propagation. ...
Les besoins de nouveaux services dans les rames ferroviaires ( le comptage, l’efficience énergétique, le confort et la sécurité des passagers etc.), risquent de saturer à terme les systèmes de communication filaires mis en place il y a une vingtaine d’années. Les réseaux de capteurs sans fil, par leurs avantages (déploiement facile, capacité à s’adapter à plusieurs types d’environnements, faible consommation d’énergie), ouvrent de nombreuses perspectives pour les systèmes de gestion énergétique. Le but de ce travail de thèse est d’étudier et mettre en oeuvre un réseau de capteurs sans fil à l’intérieur des trains pour l’efficience énergétique. Ainsi, quelques protocoles de communication dédiés à la gestion énergétique ont été présentés puis une étude comparative des différents réseaux de communication sans fil réalisée. Cette étude comparative a permis de faire le choix du réseau ZigBee comme étant le plus adéquat pour la plateforme. L’architecture hybride proposée permet l’utilisation du réseau IP existant comme colonne vertébrale de l’ensemble des réseaux ZigBee. Afin de tenir compte de l’effet de l’environnement ferroviaire dans la planification et le déploiement du réseau, une étude du canal de propagation, basée sur des mesures réalisées dans un métro et un wagon de RER a été menée. L’impact de la coexistence entre le ZigBee et le WiFi et de la présence humaine sur la communication du réseau sans fil a été démontré. Le prototype d’une plateforme basée sur le réseau ZigBee allant de la collecte des données à l’affichage des informations a été réalisé et testé.
... .6.1.3 -Modèle de Motley -KeenanLe modèle de Motley-Keenan[18] s'applique pour les cas NLOS dans un environnement de type bureau. L'affaiblissement de parcours s'exprime en fonction d'un terme de perte en espace libre auquel on ajoute les pertes dues aux obstacles traversés par le rayon direct (murs, portes, fenêtres, dalles). ...
L'évolution continue des systèmes de communications sans fil en indoor rend nécessaire le développement des outils de caractérisation et de modélisation de la propagation des ondes électromagnétiques; afin de répondre aux problématiques et besoins d'ingénieur et de garantir une meilleure planification et un fonctionnement optimal des systèmes communicants. Les travaux effectués dans le cadre de cette thèse portent sur la modélisation du rayonnement des antennes en tenant compte de la complexité environnementale. La méthode de modélisation basée sur la FDTD, détaillée au cours de ce manuscrit, permet d'obtenir d'une manière efficace et précise les niveaux de champs, en tenant compte des phénomènes de propagation et d'interaction des ondes radioélectriques dans un environnement quelconque. Des améliorations ayant deux objectifs essentiels, ont été apportées à ce code. Le premier s'est consacré à améliorer ses performances, et le deuxième s'est intéressé à l'intégration d'un modèle de corps humain et d'autres sources d'émission, dans le but d'assurer plus de réalisme à la modélisation effectuée avec ce code. La validation du code FDTD a été menée par des études comparatives réalisées dans trois environnements différents. La première étude a porté sur une communication sans fil à travers des portes étanches métalliques à bord d'un navire. Une bonne précision du code FDTD a été relevée en comparant les résultats obtenus par ce code avec ceux obtenus par des mesures. La deuxième a porté sur la caractérisation du rayonnement d'antennes dans un bureau universitaire. Les résultats obtenus par des mesures effectuées dans cet environnement ont été confrontés aux ceux obtenus par le code FDTD et par d'autres outils de simulation (HFSS et un outil de tracé de rayons "Wireless lnsite"). Ils ont permis de montrer la capacité du code FDTD à fournir les résultats les plus proches des mesures avec un temps de calcul acceptable et sans avoir besoin de grandes ressources informatiques. La dernière étude a porté sur l'effet de la présence humaine dans une chambre en acier. Une comparaison entre les résultats fournis par le code FDTD et ceux obtenus expérimentalement a été réalisée et un bon accord a été observé.
Multi-story parking garages are an important and widespread part of (urban) traffic, which will also benefit from the intelligent transportation systems (ITS) of the future. Concerning the communication aspects, they constitute a special environment. In this paper, we describe a combination of models to offer the possibility of investigating parking garage scenarios with the help of vehicular network simulators. We outline how inter-floor communication, small-scale fading as well as obstacles can be taken into consideration. To evaluate this approach, we performed two kinds of measurements in two multi-story parking garages. Based on these data, we first determine the floor attenuation factors for both buildings. Second, we compare the path loss captured during two test drives to the results of corresponding simulation runs, which show good agreement. Finally, the proposed extensions are used to simulate a sample large-scale scenario, investigating the influence of different bitrates on the communication conditions in a parking garage.
WiFi fingerprinting-based indoor positioning system is vulnerable to the dynamic environment, which makes the positioning accuracy decrease and the fingerprint map invalid. To address these issues, an accurate indoor positioning system (AIPS) with fingerprint map adaptation is proposed. For online positioning, it treats the received signal strength (RSS) from each access point (AP) individually and can be divided into two steps: 1) coarse and 2) fine positioning. In coarse positioning, a novel clustering algorithm based on
attenuation is proposed. In fine positioning, signal noise is considered to construct AP ring, and the reference point (RP) contained by the largest number of rings is selected as nearest RP, and then the RPs with larger number are searched out by region growing algorithm to estimate the location of test point (TP). For the fingerprint map adaptation,
K
-means is adopted to divide APs into two types, based on the number of rings, and to find which APs’ information has been changed by the dynamic environment, and then update them through Gaussian process regression. The experimental results show that the positioning algorithm in AIPS can improve the positioning accuracy compared with other algorithms, and the fingerprint map adaptation scheme in AIPS can reduce the online running time while keeping accuracy.
Small cells are now widely deployed indoors to address hot-spot areas where capacity uplift is needed. This deployment leads to the increase of wireless networks as a challenge to service demands of personal communication systems, which has inspired the scientific community to work towards understanding and predicting in-building radio wave propagation performance. Despite this, only a few reviews have attempted to overview channel modeling for specific indoor environments and even fewer outline remarks that include a methodology for designing and planning indoor radio systems. Consequently, a comprehensive survey of indoor narrowband channel models is presented, spanning more than 30 years of continuous research to overview and contrast significant developments including their disadvantages, and proposing a new taxonomy to analyze them. Finally, remarks on indoor radio propagation modeling with a vision for future research opportunities are presented.
Indoor Ultra‐high Broadband Access with high traffic densities inside office buildings brings the indoor office channel into the focus. Whereas in the past decade the indoor office channel in the UHF range was subject to intense channel modeling and channel characterization approaches, with the advent of 5G mmWave channels are raising attention. After introducing the key characteristics and main differences of propagation in the UHF and mmWave frequency range, respectively, the first part of the article indoor office channels describes empirical, semiempirical, and deterministic path loss models for both the UHF and the mmWave frequency range. A detailed description is provided for the semiempirical Motley–Keenan model and its various extensions. These models allow a narrowband channel characterization and provide the large‐scale characteristics. These models are relevant for the planning and optimization of radio access points as well as an enabler for system‐level simulations. The second part introduces channel models capable of providing temporal and spatial channel characteristics. This includes approaches to derive models for double‐directional channels, which are required to simulate and investigate multi‐antenna systems and beam‐forming algorithms especially in the mmWave range. Furthermore, an approach to describe the impact of human blockage is provided. As exemplary approaches, the extended Saleh–Valenzuela model and the TGad channel model are described.
New bands of frequency spectrum are being exploited as prospective bands for 5G, the next generation of mobile communication. This work presents a study in the 10 GHz band proposing an optimal value for the distance attenuation coefficient for classical literature models and a new model in the literature that work in the 10 GHz frequency band. Data were modeled using Optimization obtaining satisfactory results and with RMSE value suitable for the studied environment.
Nowadays, WiFi infrastructures and WiFi-enabled mobile devices have been ubiquitous in our daily lives, and are promising to provide both network services and indoor positioning and navigation services due to its simplicity and low costs. But, it is evident that AP placement is critical to both localization and network coverage, so that it is helpful to find the optimal AP placement scheme in terms of both localization and coverage. This paper tackles this problem by leveraging the widely used Cramer-Rao lower bound (CRLB) and heuristic genetic algorithm to develop an efficient AP optimization method. To be specific, the CRLB is used as the metric for localization and a multiple degree criterion is defined as the metric for coverage, which is incorporated into the fitness function in the genetic algorithm. Furthermore, instead of using the idea log distance path loss (LDPL) model, the more practical Motley-keenan model is adopted to reflect the influences of obstacles which are widespread in indoor environments. Finally, extensive simulations are conducted, and comparisons between the proposed method and the other three popular methods confirm the efficiency and effectiveness of the proposed method.
The WiFi landscape is rapidly changing over the last years, responding to the new needs of wireless communications. IEEE 802.11ax is the next fast-approaching standard, addressing some of today's biggest performance challenges specifically for high-density public environments. It is designed to operate at 2.4 GHz and 5 GHz bands, the latter being rapidly adopted worldwide after its inclusion in IEEE 802.11ac, and with expected growing demand in the next 10 years. This paper assesses empirically the suitability of the available IEEE 802.11ax path loss models at 5 GHz on some real testbeds and proposes a new model with higher abstraction level; i.e., without requiring from a previous in situ analysis of each considered receiver's location. The proposed TMB path loss model, used in combination with generated data sets, is able to obtain an estimation of RSSI, selected modulation and coding scheme (MCS), and number of spatial streams in function of the AP configuration and the AP-STA distance. We aim to use the model to compare IEEE 802.11ac/ax performance simulation results with experimental ones.
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