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Journal articles on the topic 'Indoor propagation models'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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1

Bermudez, Hector Fabio, Ramón Sanchez-Iborra, Jose Luis Arciniegas, Wilmar Yesid Campo, and María Dolores Cano. "Indoor propagation models for emulated LTE networks." IET Communications 14, no. 3 (2020): 480–88. http://dx.doi.org/10.1049/iet-com.2019.0365.

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2

Noh, Sun-Kuk, and DongYou Choi. "Propagation Model in Indoor and Outdoor for the LTE Communications." International Journal of Antennas and Propagation 2019 (June 16, 2019): 1–6. http://dx.doi.org/10.1155/2019/3134613.

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Rapidly rising demand for radio communication and the explosion in the number of mobile communications service subscribers have led to the need for optimization in the development of fifth-generation (5G) mobile communication systems. Previous studies on the development of propagation models considering a propagation environment in the existing microwave band have been mainly focused on analyzing the propagation characteristics with regard to large-scale factors such as path losses, delay propagation, and angle diffusions. In this paper, we investigated the concept of spatial and time changes ratios in the measurement of wave propagations and measured RSRP of Long Term Evolution (LTE) signals at three locations considering the time rate of 1% and 50%. We confirmed the concept of spatial and time changes rate based on the results of analyzing the signal data measured and proposed the propagation models 1 and 2 in microcell downtown. The forecast results using proposed models 1 and 2 were better than the COST231 model in both indoor and outdoor measured places. It was predicted between a time rate of 1% and 50% indoor within 400m and outdoor within 200m. In the future, we will study the propagation model of 5G mobile communication as well as the current 4G communication using artificial intelligence technology.
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Al-Saman, Ahmed, Michael Cheffena, Olakunle Elijah, Yousef A. Al-Gumaei, Sharul Kamal Abdul Rahim, and Tawfik Al-Hadhrami. "Survey of Millimeter-Wave Propagation Measurements and Models in Indoor Environments." Electronics 10, no. 14 (2021): 1653. http://dx.doi.org/10.3390/electronics10141653.

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The millimeter-wave (mmWave) is expected to deliver a huge bandwidth to address the future demands for higher data rate transmissions. However, one of the major challenges in the mmWave band is the increase in signal loss as the operating frequency increases. This has attracted several research interests both from academia and the industry for indoor and outdoor mmWave operations. This paper focuses on the works that have been carried out in the study of the mmWave channel measurement in indoor environments. A survey of the measurement techniques, prominent path loss models, analysis of path loss and delay spread for mmWave in different indoor environments is presented. This covers the mmWave frequencies from 28 GHz to 100 GHz that have been considered in the last two decades. In addition, the possible future trends for the mmWave indoor propagation studies and measurements have been discussed. These include the critical indoor environment, the roles of artificial intelligence, channel characterization for indoor devices, reconfigurable intelligent surfaces, and mmWave for 6G systems. This survey can help engineers and researchers to plan, design, and optimize reliable 5G wireless indoor networks. It will also motivate the researchers and engineering communities towards finding a better outcome in the future trends of the mmWave indoor wireless network for 6G systems and beyond.
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Mukti, Fransiska Sisilia. "Comparative study of four indoor empirical propagation models for campus wireless network." Jurnal Teknologi dan Sistem Komputer 7, no. 4 (2019): 154–60. http://dx.doi.org/10.14710/jtsiskom.7.4.2019.154-160.

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Propagation is one of the important factors to understand in wireless communication systems. Prediction of the value of propagation, especially for closed areas, is very necessary to determine success in building wireless networks. Various kinds of propagation modeling were developed to find the best approach to calculate the value of signal losses. A comparative study of 4 types of empirical propagation modeling was made to provide the most suitable propagation modeling analysis for campus wireless networks. The ITU-R model (P.1238) provides predictive results that are closest to the actual data in the field, with a relative error rate of 16.381%.
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Lipinski, Piotr, and Marcin Leplawy. "WiFi Electromagnetic Field Modelling for Indoor Localization." Open Physics 17, no. 1 (2019): 352–57. http://dx.doi.org/10.1515/phys-2019-0039.

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Abstract The aim of this paper is to develop simplified model for WiFi electromagnetic field propagation. The model can be used in preliminary estimation of WiFi transmitter localization for the purpose of WiFi-based indoor localization. It can be particularly useful when designing structural networks.We have developed a simplified linear model of WiFi electromagnetic field modelling and compared it with the most commonly used, more sophisticated models and with measurement results which were carried out in the laboratory. As demonstrated by the results of measurements conducted using various hardware, the accuracy of this simplified model introduced is similar to the commonly used models, but the number of parameters is lower. Therefore, our model easier to implement in real life conditions. The model presented in this paper enables WiFi electromagnetic field modelling when the exact values of propagation parameters and transmitter characteristics is unknown. This is usually the case at the early stage of structural network design,when exact parameters of building construction materials are not known. As the model is very simple, it does not require much effort to deploy, while its accuracy is sufficient for preliminary WiFi transmitter localization. Simplified models of WiFi electromagnetic field propagation are known, but no comparative research combined with measurements has been done in this field. This paper provides a comparison of different electromagnetic field models which can be applied to WiFi electromagnetic field propagation together with measurement results.
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Zhu, Shan, Bang Wang, Wen Yu Liu, and Hui Liang. "An Empirical Indoor Propagation Model for Underground Parking Area." Advanced Materials Research 433-440 (January 2012): 4865–68. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4865.

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This paper presents an empirical indoor propagation model for underground parking area based on our extensive field measurements. Among several candidate empirical models, we choose the modified Keenan-Motley model for calibration, using channel power measurements at the 3G and 4G radio frequencies. Our calibration results can be used to provide a simple propagation model for wireless transmission planning, forecasting and quality control in indoor parking scenarios.
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7

Kuo-Hui Li, M. A. Ingram, and A. Van Nguyen. "Impact of clustering in statistical indoor propagation models on link capacity." IEEE Transactions on Communications 50, no. 4 (2002): 521–23. http://dx.doi.org/10.1109/26.996062.

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8

Lei Jiang and Soon Yim Tan. "Geometrically Based Statistical Channel Models for Outdoor and Indoor Propagation Environments." IEEE Transactions on Vehicular Technology 56, no. 6 (2007): 3587–93. http://dx.doi.org/10.1109/tvt.2007.901055.

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9

Akram, Beenish Ayesha, and Ali Hammad Akbar. "Wi-Fi Fingerprinting Based Room Level Indoor Localization Framework Using Ensemble Classifiers." January 2019 38, no. 1 (2019): 151–74. http://dx.doi.org/10.22581/muet1982.1901.13.

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Over the past decennium, Wi-Fi fingerprinting based indoor localization has seized substantial attention. Room level indoor localization can enable numerous applications to increase their diversity by incorporating user location. Real-world commercial scale deployments have not been realized because of difficulty in capturing radio propagation models. In case of fingerprinting based approaches, radio propagation model is implicitly integrated in the gathered fingerprints providing more realistic information as compared to empirical propagation models. We propose ensemble classifiers based indoor localization using Wi-Fi fingerprints for room level prediction. The major advantages of the proposed framework are, ease of training, ease to set up framework providing high room-level accuracy with trifling response time making it viable and appropriate for real time applications. It performs well in comparison with recurrently used ANN (Artificial Neural Network) and kNN (k-Nearest Neighbours) based solutions. Experiments performed showed that on our real-world Wi-Fi fingerprint dataset, our proposed approach achieved 89% accuracy whereas neural network and kNN based best found configurations achieved 85 and 82% accuracy respectively.
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Loch-Dehbi, Sandra, Youness Dehbi, and Lutz Plümer. "Estimation of 3D Indoor Models with Constraint Propagation and Stochastic Reasoning in the Absence of Indoor Measurements." ISPRS International Journal of Geo-Information 6, no. 3 (2017): 90. http://dx.doi.org/10.3390/ijgi6030090.

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11

Varga, Gábor, and Róbert Schulcz. "Indoor radio location algorithm using empirical propagation models and probability distribution heuristics." Periodica Polytechnica Electrical Engineering 55, no. 1-2 (2011): 87. http://dx.doi.org/10.3311/pp.ee.2011-1-2.10.

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12

López O., Sandra Paulina, Juan David Osorio Betancur, and Andrés Navarro Cadavid. "Graphic Tool for Wireless Networks Modeling, based in Indoor Signal Propagation Models." Sistemas y Telemática 2, no. 4 (2006): 95. http://dx.doi.org/10.18046/syt.v2i4.939.

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13

Agrawal, Anuj. "Evolving CSP Algorithm in Predicting the Path Loss of Indoor Propagation Models." International Journal of Computer Applications Technology and Research 2, no. 2 (2013): 86–90. http://dx.doi.org/10.7753/ijcatr0202.1001.

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14

Lim, C. P., J. L. Volakis, K. Sertel, R. W. Kindt, and A. Anastasopoulos. "Indoor Propagation Models Based on Rigorous Methods for Site-Specific Multipath Environments." IEEE Transactions on Antennas and Propagation 54, no. 6 (2006): 1718–25. http://dx.doi.org/10.1109/tap.2006.875493.

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15

Ayadi, M., and A. Ben Zineb. "Body Shadowing and Furniture Effects for Accuracy Improvement of Indoor Wave Propagation Models." IEEE Transactions on Wireless Communications 13, no. 11 (2014): 5999–6006. http://dx.doi.org/10.1109/twc.2014.2339275.

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16

Morocho-Yaguana, Marco, Patricia Ludeña-González, Francisco Sandoval, Betty Poma-Vélez, and Alexandra Erreyes-Dota. "An Optimized Propagation Model based on Measurement Data for Indoor Environments." Journal of Telecommunications and Information Technology 2 (June 29, 2018): 69–75. http://dx.doi.org/10.26636/jtit.2018.117217.

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Propagation is an essential factor ensuring good coverage of wireless communications systems. Propagation models are used to predict losses in the path between transmitter and receiver nodes. They are usually defined for general conditions. Therefore, their results are not always adapted to the behavior of real signals in a specific environment. The main goal of this work is to propose a new model adjusting the loss coefficients based on empirical data, which can be applied in an indoor university campus environment. The Oneslope, Log-distance and ITU models are described to provide a mathematical base. An extensive measurement campaign is performed based on a strict methodology considering different cases in typical indoor scenarios. New loss parameter values are defined to adjust the mathematical model to the behavior of real signals in the campus environment. The experimental results show that the model proposed offers an attenuation average error of 2.5% with respect to the losses measured. In addition, comparison of the proposed model with existing solutions shows that it decreases the average error significantly for all scenarios under evaluation.
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17

Ferreira, Joao, Ricardo Resende, and Stuart Martinho. "Beacons and BIM Models for Indoor Guidance and Location." Sensors 18, no. 12 (2018): 4374. http://dx.doi.org/10.3390/s18124374.

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This research work uses a simplified approach to combine location information from a beacon’s propagation signal interaction with a mobile device sensor (accelerometer and gyroscope) with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user’s orientation inside unknown buildings and the data stored from different users can provide useful information about users’ movements inside a public building. Beacons installed on the building at specific pre-defined positions emit signals that give a geographic position with an associated imprecision, related with Bluetooth’s range. This uncertainty is handled by building layout and users’ movement in a developed system that maps users’ position, gives guidance, and stores user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user’s smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively.
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18

Huang, Liang, and Zai Yi Liao. "Physical-Rule Based Adaptive Neuro-Fuzzy Inferential Sensor vs. GA-BP Based Prediction Model in Indoor Temperature Predicting." Advanced Materials Research 594-597 (November 2012): 2179–85. http://dx.doi.org/10.4028/www.scientific.net/amr.594-597.2179.

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The previous research on temperature prediction presented different approaches which are physical-rule based adaptive neuro-fuzzy inferential sensor (ANFIS) model and GA-BP (genetic algorithm back propagation) based model to estimate the average indoor temperature in the building environment. Their good prediction performances improved energy efficiency of district heating system and indoor comfort ratio. However, either of these two models has its drawback in a certain condition. In this paper, the two prediction models are reviewed and evaluated by three performance measures (RMSE, RMS, and R2). Their limitations are discussed and potential solution is proposed.
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19

Pascual-García, Juan, Maria-Teresa Martinez-Ingles, Davy P. Gaillot, Leandro Juan-Llácer, and Jose-Maria Molina-Garcia-Pardo. "LoS Theoretical and Experimental MIMO Study from 1–40 GHz in Indoor Environments." Electronics 9, no. 10 (2020): 1688. http://dx.doi.org/10.3390/electronics9101688.

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In this work, line-of-sight multiple-input multiple-output (MIMO) measurements in the frequency range from 1 GHz to 40 GHz are presented for an indoor environment in the scope of new 5G bands. For the sake of comparison, the measured radio channels are reproduced with great accuracy using ray-tracing techniques by tuning all propagation mechanisms. The relative received power, root mean square of the delay spread (RMS DS) and K-factor provide an insight of how propagation behaves in indoor scenarios within a large and contiguous frequency band. Results show that a decay factor behaves nearly constant with frequency and the RMS DS is quite sensible to frequency. From these results, faithful one-slope 5G models are proposed. Finally, the contribution of the simulated propagation mechanisms to the radio channel is investigated which suggests that the simulation of the low-mmW radio channel can be simplified.
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20

Abboubi, Adil El, Fouzia Elbahhar, Marc Heddebaut, and Yassin Elhillali. "Energy Consumption Models For MISO-UWB and TR-MISO-UWB Systems." International Journal of Electronics and Telecommunications 63, no. 3 (2017): 285–91. http://dx.doi.org/10.1515/eletel-2017-0038.

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Abstractthis paper, an energy consumption model is developed and exploited to evaluate the electrical energy consumption of ultra-wideband impulse radio (UWB-IR) systems. We develop the energy consumption models and our comparative study, on the one hand, for a system based single-input singleoutput (SISO) configuration and a multiple-input single-output (MISO) and, on the other hand, for a time reversal TR-MISO configuration and for MISO alone configuration. We consider an indoor propagation environment based on the 802.15.4a channel model. The results show very different behaviors depending on the propagation conditions, the number of antennas used, or on the number of transmitted symbols. Using such a model, a radiofrequency designer can obtain significant inputs to optimally select an adequate configuration to design an adaptive energyaware UWB-IR system.
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Qiu, K. Y., H. Huang, and A. El-Rabbany. "GEOMAGNETIC FIELD-BASED INDOOR POSITIONING USING BACK-PROPAGATION NEURAL NETWORKS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 557–63. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-557-2020.

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Abstract. High-precision indoor positioning in complex environments has always been a hot research topic within the positioning and robotic communities. As one of the indoor positioning technologies, geomagnetic positioning is receiving widespread attention due to its global coverage. Additionally, geomagnetic positioning does not require special infrastructure configuration, its hardware cost is low, and its positioning errors do not accumulate over time. However, geomagnetic positioning is prone to mismatching, which causes serious problems at the positioning points. To tackle this challenge, this paper proposes an indoor localization method based on spectral clustering and weighted back-propagation neural network. The main research contribution is that in the offline phase, the spatial specificity of geomagnetism is used to define the similarity between fingerprints. In addition, a clustering-based reference point algorithm is proposed to divide the sub-fingerprint database, and a positioning prediction model based on back-propagation neural network is trained. Subsequently, in the online stage, the weights of different positioning prediction models are calculated according to the defined fingerprint similarity, weighted average prediction coordinates are obtained, and thereby the positioning accuracy is improved. Experimental results show that, in comparison with other neural network-based positioning methods, the positioning error of our proposed algorithm is reduced by approximately 26.6% and the positioning time is reduced by 24.7%. Experimental results show that the average positioning error of the algorithm is 1.81m.
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Koutitas, George, Varun Kumar Siddaraju, and Vangelis Metsis. "In Situ Wireless Channel Visualization Using Augmented Reality and Ray Tracing." Sensors 20, no. 3 (2020): 690. http://dx.doi.org/10.3390/s20030690.

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This article presents a novel methodology for predicting wireless signal propagation using ray-tracing algorithms, and visualizing signal variations in situ by leveraging Augmented Reality (AR) tools. The proposed system performs a special type of spatial mapping, capable of converting a scanned indoor environment to a vector facet model. A ray-tracing algorithm uses the facet model for wireless signal predictions. Finally, an AR application overlays the signal strength predictions on the physical space in the form of holograms. Although some indoor reconstruction models have already been developed, this paper proposes an image to a facet algorithm for indoor reconstruction and compares its performance with existing AR algorithms, such as spatial understanding that are modified to create the required facet models. In addition, the paper orchestrates AR and ray-tracing techniques to provide an in situ network visualization interface. It is shown that the accuracy of the derived facet models is acceptable, and the overall signal predictions are not significantly affected by any potential inaccuracies of the indoor reconstruction. With the expected increase of densely deployed indoor 5G networks, it is believed that these types of AR applications for network visualization will play a key role in the successful planning of 5G networks.
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Indra Prasetya, AAN Agung, N. Gunantara, and P. K. Sudiarta. "ANALISIS PROPAGASI INDOOR WLAN 802.11g PADA GEDUNG DISHUBKOMINFO KABUPATEN BADUNG." Jurnal SPEKTRUM 4, no. 2 (2018): 130. http://dx.doi.org/10.24843/spektrum.2017.v04.i02.p17.

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In practice the access point can not always cover the maximum range of distance due to signal wave propagation in the room, such as reflection, alteration, or scattering of signals. For the purpose of implementation optimization, this study aims to obtain characteristics of signal level quality and throughput at the Dishubkominfo Building of Badung Regency. The indoor propagation analysis of WLAN IEEE 802.11g is based on 3 models of measurement ie without barrier, wall barrier, and floor barrier. The result of the highest signal level measurement is -40 dBm, while the lowest signal level is -85 dBm. Maximum throughput measurement results 8.05 Mbps, from the maximum available bandwidth of 10 Mbps. While the coverage area based on testers using the software to adjust the floor plan on the building, almost in accordance with the calculation of signal level.
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Ding, Youli, Xianwei Zheng, Yan Zhou, Hanjiang Xiong, and and Jianya Gong. "Low-Cost and Efficient Indoor 3D Reconstruction Through Annotated Hierarchical Structure-from-Motion." Remote Sensing 11, no. 1 (2018): 58. http://dx.doi.org/10.3390/rs11010058.

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With the widespread application of location-based services, the appropriate representation of indoor spaces and efficient indoor 3D reconstruction have become essential tasks. Due to the complexity and closeness of indoor spaces, it is difficult to develop a versatile solution for large-scale indoor 3D scene reconstruction. In this paper, an annotated hierarchical Structure-from-Motion (SfM) method is proposed for low-cost and efficient indoor 3D reconstruction using unordered images collected with widely available smartphone or consumer-level cameras. Although the reconstruction of indoor models is often compromised by the indoor complexity, we make use of the availability of complex semantic objects to classify the scenes and construct a hierarchical scene tree to recover the indoor space. Starting with the semantic annotation of the images, images that share the same object were detected and classified utilizing visual words and the support vector machine (SVM) algorithm. The SfM method was then applied to hierarchically recover the atomic 3D point cloud model of each object, with the semantic information from the images attached. Finally, an improved random sample consensus (RANSAC) generalized Procrustes analysis (RGPA) method was employed to register and optimize the partial models into a complete indoor scene. The proposed approach incorporates image classification in the hierarchical SfM based indoor reconstruction task, which explores the semantic propagation from images to points. It also reduces the computational complexity of the traditional SfM by avoiding exhausting pair-wise image matching. The applicability and accuracy of the proposed method was verified on two different image datasets collected with smartphone and consumer cameras. The results demonstrate that the proposed method is able to efficiently and robustly produce semantically and geometrically correct indoor 3D point models.
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Miramirkhani, Farshad, and Murat Uysal. "Channel modelling for indoor visible light communications." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2169 (2020): 20190187. http://dx.doi.org/10.1098/rsta.2019.0187.

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Visible light communication (VLC) allows the dual use of light-emitting diodes (LEDs) for wireless communication purposes in addition to their primary purpose of illumination. As in any other communication system, realistic channel modelling is a key for VLC system design, analysis and testing. In this paper, we present a comprehensive survey of indoor VLC channel models. In order to set the background, we start with an overview of infrared (IR) channel modelling, which has received much attention in the past, and highlight the differences between visible and IR optical bands. In the light of these, we present a comparative discussion of existing VLC channel modelling studies and point out the relevant advantages and disadvantages. Then, we provide a detailed description of a site-specific channel modelling approach based on non-sequential ray tracing that precisely captures the optical propagation characteristics of a given indoor environment. We further present channel models for representative deployment scenarios developed through this approach that were adopted by the Institute of Electrical and Electronics Engineering (IEEE) as reference channel models. Finally, we consider mobile VLC scenarios and investigate the effect of receiver location and rotation for a mobile indoor user. This article is part of the theme issue ‘Optical wireless communication’.
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Avella-Cely, Sandy Enrique, Juan Carlos Muñoz-Pérez, Herman Antonio Fernández-González, Lorenzo Rubio-Arjona, Juan Ribera Reig-Pascual, and Vicent Miguel Rodrigo-Peñarrocha. "Path Loss Characterization in an Indoor Laboratory Environment at 3.7 GHz in in Line-Of-Sight Condition." Revista Facultad de Ingeniería 29, no. 54 (2020): e12015. http://dx.doi.org/10.19053/01211129.v29.n54.2020.12015.

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The objective of this work is to propose experimental path loss propagation models for communication channels in indoor environments. In this sense, an experimental path loss characterization has been achieved, according to the measurements campaign carried out in a typical scenario of a university campus. These narrowband measurements were collected in the laboratory environment at 3.7 GHz in line-of-sight (LOS) condition. Also, these measurements were carried out at night to simulate stationary channel conditions. Thus, the results obtained show the values of the parameters of the close-in (CI) free space reference distance and floating-intercept (FI) path loss models, in terms of the transmitter and receiver separation distance. It should be noted that these values of the path loss models have been extracted applying linear regression techniques to the measured data. Also, these values agree with the path loss exponent values presented by other researchers in similar scenarios. The path loss behavior can be described with the implementation of these models. However, more measurement campaigns are needed to improve the understanding of propagation channel features, as well as to obtain better precision in the results obtained. This, in order to optimize the deployment and performance of next fifth-generation (5G) networks that combine indoor environments to offer their services and applications.
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Pinem, Maksum, Muhammad Zulfin, S. Suherman, Panangian M. Sihombing, and Sri Indah Rezkika. "Characterization of Outdoor to Indoor Propagation in Urban Area by Using A Combination of COST231 Walfisch-Ikegami and COST231 Multiwall Models in 1800 Mhz and 2100 Mhz." International Journal of Engineering & Technology 7, no. 3.2 (2018): 698. http://dx.doi.org/10.14419/ijet.v7i3.2.15347.

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Increasing numbers of the mobile communication users in urban city; especially indoor users cause the radio coverage prediction of outdoor to indoor becoming important. Obstacles are the main problems for outdoor to indoor propagation that weaken signal level and worsen information detection. This paper proposes a combination of COST231 Walfisch-Ikegami and COST231 Multiwall to predict the received signal. By comparing the predicted and the measured signal level in the Antara building, Medan city for both 1800 MHz and 2100 MHz channels, the proposed model outperforms the compared method in predicting signal level. The proposed model is able to suppress the prediction deviation 11.035 dB lower than the compared method for Sector A and 5.98 dB lower at Sector B.
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Qasem, Nidal. "Enhancing the Capacity of the Indoor 60 GHz Band Via Modified Indoor Environments Using Ring Frequency Selective Surface Wallpapers and Path Loss Models." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3003. http://dx.doi.org/10.11591/ijece.v8i5.pp3003-3020.

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<span>The 60 GHz band has been selected for short-range communication systems to meet consumers’ needs for high data rates. However, this frequency is attenuated by obstacles. This study addresses the limitations of the 60 GHz band by modifying indoor environments with ring Frequency Selective Surfaces (FSSs) wallpaper, thereby increasing its utilization. The ring FSS wallpaper response at a 61.5 GHz frequency has been analyzed using both MATLAB and Computer Simulation Technology (CST) Microwave Studio (MWS) software. ‘Wireless InSite’ is also used to demonstrate enhanced wave propagation in a building modified with ring FSSs wallpaper. The demonstration is applied to Single Input Single Output (SISO) and Multiple Input Multiple Output (MIMO) systems to verify the effectiveness of FSSs on such systems’ capacity. The effectiveness of the suggested modification over delay spread has been studied for the MIMO scenario, as well as the effect of the human body on capacity. Simulation results presented here show that modifying a building using ring FSS wallpaper is an attractive scheme for significantly improving the indoor 60 GHz wireless communications band. This paper also presents and compares two large-scale indoor propagation Path Loss Models (PLMs), the Close-In (CI) free space reference distance model and the Floating Intercept (FI) model. Data obtained from ‘Wireless InSite’ over distances ranging from 4 to 14.31 m is analyzed. Results show that the CI model provides good estimation and exhibits stable behavior over frequencies and distances, with a solid physical basis and less computational complexity when compared to the FI model. </span>
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29

Pimienta-del-Valle, Domingo, Luis Mendo, José Manuel Riera, and Pedro Garcia-del-Pino. "Indoor LOS Propagation Measurements and Modeling at 26, 32, and 39 GHz Millimeter-Wave Frequency Bands." Electronics 9, no. 11 (2020): 1867. http://dx.doi.org/10.3390/electronics9111867.

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Although the deployment of 5G networks has already started, there are still open questions regarding propagation at millimeter-wave frequency bands. Several propagation campaigns have been carried out at several bands previously identified by regulatory organizations, but due to the wide range of allocated segments of spectrum and the variety of possible propagation scenarios, more measurement campaigns are needed. In this regard, the Universidad Politécnica de Madrid (UPM) has taken millimeter-wave measurements at 26, 32, and 39 GHz bands in an indoor corridor scenario in line-of-sight (LOS) conditions with two antenna configurations (a horn antenna has been used in transmission whereas horn and omnidirectional antennas have been used in reception), and the main results are presented in this paper. The obtained path loss results have been compared with existing millimeter-wave propagation models.
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Makara, Árpád László, and László Csurgai-Horváth. "Improved Model for Indoor Propagation Loss in the 5G FR2 Frequency Band." Infocommunications journal 13, no. 1 (2021): 2–10. http://dx.doi.org/10.36244/icj.2021.1.1.

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One of the latest developments today is the 5G, or 5th generation mobile network. In addition to a number of innovations, the new system also includes millimeter-wavelength frequency ranges denoted with FR2, that formerly not applied for these specific purposes. Proper management of the transmitter and receiver antenna beams is required for efficient communication in this frequency range. For future use, the simplest implementation way is electronically shaping the antenna beams by an algorithm to orient the antennas in the best possible direction. The prerequisites for these algorithms are appropriate propagation models, which are currently lacking, and those that publicly available are not accurate enough for practical use.
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31

Artemenko, Oleksandr, Alina Rubina, Adarsh Harishchandra Nayak, Sanjeeth Baptist Menezes, and Andreas Mitschele-Thiel. "Evaluation of different signal propagation models for a mixed indoor-outdoor scenario using empirical data." ICST Transactions on Mobile Communications and Applications 2, no. 7 (2016): 151519. http://dx.doi.org/10.4108/eai.20-6-2016.151519.

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32

Jarvelainen, Jan, Matti Kurkela, and Katsuyuki Haneda. "Impacts of Room Structure Models on the Accuracy of 60 GHz Indoor Radio Propagation Prediction." IEEE Antennas and Wireless Propagation Letters 14 (2015): 1137–40. http://dx.doi.org/10.1109/lawp.2015.2390917.

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33

Cuinas, Inigo, and Manuel Garcia Sanchez. "A Comparison of Empirical and Ray-Tracing Models for Indoor Radio-Wave Propagation [Wireless Corner]." IEEE Antennas and Propagation Magazine 62, no. 2 (2020): 107–15. http://dx.doi.org/10.1109/map.2020.2969253.

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34

Caso, Giuseppe, and Luca De Nardis. "Virtual and Oriented WiFi Fingerprinting Indoor Positioning based on Multi-Wall Multi-Floor Propagation Models." Mobile Networks and Applications 22, no. 5 (2016): 825–33. http://dx.doi.org/10.1007/s11036-016-0749-x.

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35

Al-Samman, Ahmed Mohammed, Tharek Abd. Rahman, Tawfik Al-Hadhrami, et al. "Comparative Study of Indoor Propagation Model Below and Above 6 GHz for 5G Wireless Networks." Electronics 8, no. 1 (2019): 44. http://dx.doi.org/10.3390/electronics8010044.

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It has been widely speculated that the performance of the next generation based wireless network should meet a transmission speed on the order of 1000 times more than the current cellular communication systems. The frequency bands above 6 GHz have received significant attention lately as a prospective band for next generation 5G systems. The propagation characteristics for 5G networks need to be fully understood for the 5G system design. This paper presents the channel propagation characteristics for a 5G system in line of sight (LOS) and non-LOS (NLOS) scenarios. The diffraction loss (DL) and frequency drop (FD) are investigated based on collected measurement data. Indoor measurement results obtained using a high-resolution channel sounder equipped with directional horn antennas at 3.5 GHz and 28 GHz as a comparative study of the two bands below and above 6 GHz. The parameters for path loss using different path loss models of single and multi-frequencies have been estimated. The excess delay, root mean square (RMS) delay spread and the power delay profile of received paths are analyzed. The results of the path loss models show that the path loss exponent (PLE) in this indoor environment is less than the free space path loss exponent for LOS scenario at both frequencies. Moreover, the PLE is not frequency dependent. The 3GPP path loss models for single and multi-frequency in LOS scenarios have good performance in terms of PLE that is as reliable as the physically-based models. Based on the proposed models, the diffraction loss at 28 GHz is approximately twice the diffraction loss at 3.5 GHz. The findings of the power delay profile and RMS delay spread indicate that these parameters are comparable for frequency bands below and above 6 GHz.
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36

Ruiz-Avilés, J. M., S. Luna-Ramírez, M. Toril, et al. "Design of a Computationally Efficient Dynamic System-Level Simulator for Enterprise LTE Femtocell Scenarios." Journal of Electrical and Computer Engineering 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/802606.

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In the context of Long-Term Evolution (LTE), the next generation mobile telecommunication network, femtocells are low-power base stations that efficiently provide coverage and capacity indoors. This paper presents a computationally efficient dynamic system-level LTE simulator for enterprise femtocell scenarios. The simulator includes specific mobility and traffic and propagation models for indoor environments. A physical layer abstraction is performed to predict link-layer performance with low computational cost. At link layer, two important functions are included to increase network capacity: Link Adaptation and Dynamic Scheduling. At network layer, other Radio Resource Management functionalities, such as Admission Control and Mobility Management, are also included. The resulting tool can be used to test and validate optimization algorithms in the context of Self-Organizing Networks (SON).
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37

Douiri, Nisrine, Majdi Khoudeir, and Christian Olivier. "ROUGHNESS CHARACTERIZATION OF AN INDOOR ENVIRONMENT." Image Analysis & Stereology 20, no. 3 (2011): 225. http://dx.doi.org/10.5566/ias.v20.p225-229.

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For a transmission at 60 GHz inside the buildings, the models of propagation currently developed do not take into account the 3D roughness of surfaces under consideration. In this paper, we deal with the evaluation of the 3D roughness of surfaces in this kind of environment. An indoor environment includes different types of surfaces but the most representative of 3D roughness are walls, ceiling and floor. We propose a method to characterise the 3D roughness of these surfaces by constructing an image space made up of the original image, the image of gradient, the image of curvature and the image of the angles between the perpendicular to the grey level surface and the perpendicular to the whole image. The method we have developed is based, first, on the study of correlation variations of our image space, and second on a frequency analysis of the angle image histograms. The elaborated criteria allowed us to classify the surfaces studied.
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38

Phaiboon, Supachai, P. Phokharatkul, and Suripon Somkuarnpanit. "NEW UPPER AND LOWER BOUNDS LINE OF SIGHT PATH LOSS MODELS FOR MOBILE PROPAGATION IN BUILDINGS." ASEAN Journal on Science and Technology for Development 24, no. 4 (2017): 407–18. http://dx.doi.org/10.29037/ajstd.214.

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This paper proposes a method to predict line-of-sight (LOS) path loss in buildings. We performed measurements in two different type of buildings at a frequency of 1.8 GHz and propose new upper and lower bounds path loss models which depend on max and min values of sample path loss data. This makes our models limit path loss within the boundary lines. The models include time-variant effects such as people moving and cars in parking areas with their influence on wave propagation that is very high. The results have shown that the proposed models will be useful for the system and cell design of indoor wireless communication systems.
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Sheikh, Muhammad Usman, Kimmo Hiltunen, and Jukka Lempiainen. "Enhanced Outdoor to Indoor Propagation Models and Impact of Different Ray Tracing Approaches at Higher Frequencies." Advances in Science, Technology and Engineering Systems Journal 3, no. 2 (2018): 58–68. http://dx.doi.org/10.25046/aj030207.

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Batalha, Iury Da Silva, Andrea V. R. Lopes, Jasmine P. L. Araujo, et al. "Indoor Corridor and Office Propagation Measurements and Channel Models at 8, 9, 10 and 11 GHz." IEEE Access 7 (2019): 55005–21. http://dx.doi.org/10.1109/access.2019.2911866.

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41

Shabbir, Noman, Lauri Kütt, Muhammad M. Alam, et al. "Vision towards 5G: Comparison of radio propagation models for licensed and unlicensed indoor femtocell sensor networks." Physical Communication 47 (August 2021): 101371. http://dx.doi.org/10.1016/j.phycom.2021.101371.

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42

Neelakanta, Perambur, and Dolores De Groff. "Conceiving Inferential Prototypes of MIMO Channel Models via Buckingham’s Similitude Principle for 30+ GHz through THz Spectrum." Transactions on Networks and Communications 9, no. 3 (2021): 1–35. http://dx.doi.org/10.14738/tnc.93.10214.

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Facilitating newer bands of ‘unused’ segments (windows) of RF spectrum falling in the mm-wave range (above 30+ GHz) and seeking usable stretches across unallocated THz spectrum, could viably be considered for Multiple Input Multiple Output (MIMO) communications. This could accommodate the growing needs of multigigabit 3G/4G applications in outdoor-based backhauls in picocellular networks and in indoor-specific multimedia networking. However, in contrast with cellular and Wi-Fi, wireless systems supporting sub-mm wavelength transreceive communications in the outdoor electromagnetic (EM) ambient could face “drastically different propagation geometry”; also, in indoor contexts, envisaging pertinent spatial-multiplexing with directional, MIMO links could pose grossly diverse propagation geometry across a number of multipaths; as such, channel-models based on stochastic features of diverse MIMO-specific links in the desired test spectrum of mm-wave/THz band are sparsely known and almost non-existent. To alleviate this niche, a method is proposed here to infer sub-mm band MIMO channel-models (termed as “prototypes”) by judiciously sharing “similarity” of details available already pertinent to traditional “models” of lower-side EM spectrum, (namely, VLF through micro-/mm-wave). Relevant method proposed here relies on the “principle of similitude” due to Edgar Buckingham. Exemplar set of “model-to-(inferential)-prototype” transformations are derived and prescribed for an exhaustive set of fading channel models as well as, towards estimating path-loss of various channel statistics in the high-end test spectrum.
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43

Alwarafy, Abdulmalik, Ahmed Iyanda Sulyman, Abdulhameed Alsanie, Saleh A. Alshebeili, and Hatim M. Behairy. "Path-Loss Channel Models for Receiver Spatial Diversity Systems at 2.4 GHz." International Journal of Antennas and Propagation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/6790504.

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This article proposes receiver spatial diversity propagation path-loss channel models based on real-field measurement campaigns that were conducted in a line-of-site (LOS) and non-LOS (NLOS) indoor laboratory environment at 2.4 GHz. We apply equal gain power combining (EGC), coherent and noncoherent techniques, on the received signal powers. Our empirical data is used to propose spatial diversity propagation path-loss channel models using the log-distance and the floating intercept path-loss models. The proposed models indicate logarithmic-like reduction in the path-loss values as the number of diversity antennas increases. In the proposed spatial diversity empirical path-loss models, the number of diversity antenna elements is directly accounted for, and it is shown that they can accurately estimate the path-loss for any generalized number of receiving antenna elements for a given measurement setup. In particular, the floating intercept-based diversity path-loss model is vital to the 3GPP and WINNER II standards since they are widely utilized in multi-antenna-based communication systems.
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44

Rubio, Lorenzo, Rafael P. Torres, Vicent M. Rodrigo Peñarrocha, et al. "Contribution to the Channel Path Loss and Time-Dispersion Characterization in an Office Environment at 26 GHz." Electronics 8, no. 11 (2019): 1261. http://dx.doi.org/10.3390/electronics8111261.

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In this paper, path loss and time-dispersion results of the propagation channel in a typical office environment are reported. The results were derived from a channel measurement campaign carried out at 26 GHz in line-of-sight (LOS) and obstructed-LOS (OLOS) conditions. The parameters of both the floating-intercept (FI) and close-in (CI) free space reference distance path loss models were derived using the minimum-mean-squared-error (MMSE). The time-dispersion characteristics of the propagation channel were analyzed through the root-mean-squared (rms) delay-spread and the coherence bandwidth. The results reported here provide better knowledge of the propagation channel features and can be also used to design and evaluate the performance of the next fifth-generation (5G) networks in indoor office environments at the potential 26 GHz frequency band.
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45

Hu, Chufeng, and Nanjing Li. "Calculation of Differential Propagation Constant Determined by Plant Morphology Using Polarimetric Measurement." International Journal of Antennas and Propagation 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/718242.

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The morphology of vegetation greatly impacts propagation of polarized electromagnetic wave. In order to validate this phenomenon, the mathematical relation between the differential propagation constant of forest vegetation and of its polarized echo is quantitatively derived by using backscattering power profile. The fluctuation of differential propagation constant with frequency is analyzed by combining the morphological characteristics of vegetation. The accurate copolarized data of 3–10 GHz frequency-domain of small trees are obtained by indoor wideband polarimetric measurement system. The results show that morphological characteristics of vegetation at different frequencies can be obtained by the differential propagation constant of polarized electromagnetic wave. At low frequencies, the plants with structural features presented oriented distribution. However, the plants show random distribution of the echoes at higher frequencies, which is mainly from the canopy. The research provides important information to choose the coherence models employed in the parameters retrieval of vegetations.
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46

Akram, Beenish Ayesha, Ali Hammad Akbar, and Ki-Hyung Kim. "CEnsLoc: Infrastructure-Less Indoor Localization Methodology Using GMM Clustering-Based Classification Ensembles." Mobile Information Systems 2018 (October 1, 2018): 1–11. http://dx.doi.org/10.1155/2018/3287810.

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Indoor localization has continued to garner interest over the last decade or so, due to the fact that its realization remains a challenge. Fingerprinting-based systems are exciting because these embody signal propagation-related information intrinsically as compared to radio propagation models. Wi-Fi (an RF technology) is best suited for indoor localization because it is so widely deployed that literally, no additional infrastructure is required. Since location-based services depend on the fingerprints acquired through the underlying technology, smart mechanisms such as machine learning are increasingly being incorporated to extract intelligible information. We propose CEnsLoc, a new easy to train-and-deploy Wi-Fi localization methodology established on GMM clustering and Random Forest Ensembles (RFEs). Principal component analysis was applied for dimension reduction of raw data. Conducted experimentation demonstrates that it provides 97% accuracy for room prediction. However, artificial neural networks, k-nearest neighbors, K∗, FURIA, and DeepLearning4J-based localization solutions provided mean 85%, 91%, 90%, 92%, and 73% accuracy on our collected real-world dataset, respectively. It delivers high room-level accuracy with negligible response time, making it viable and befitted for real-time applications.
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Kausar, A. S. M. Zahid, Ahmed Wasif Reza, Lau Chun Wo, and Harikrishnan Ramiah. "A Comprehensive Propagation Prediction Model Comprising Microfacet Based Scattering and Probability Based Coverage Optimization Algorithm." Scientific World Journal 2014 (2014): 1–17. http://dx.doi.org/10.1155/2014/601729.

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Although ray tracing based propagation prediction models are popular for indoor radio wave propagation characterization, most of them do not provide an integrated approach for achieving the goal of optimum coverage, which is a key part in designing wireless network. In this paper, an accelerated technique of three-dimensional ray tracing is presented, where rough surface scattering is included for making a more accurate ray tracing technique. Here, the rough surface scattering is represented by microfacets, for which it becomes possible to compute the scattering field in all possible directions. New optimization techniques, like dual quadrant skipping (DQS) and closest object finder (COF), are implemented for fast characterization of wireless communications and making the ray tracing technique more efficient. In conjunction with the ray tracing technique, probability based coverage optimization algorithm is accumulated with the ray tracing technique to make a compact solution for indoor propagation prediction. The proposed technique decreases the ray tracing time by omitting the unnecessary objects for ray tracing using the DQS technique and by decreasing the ray-object intersection time using the COF technique. On the other hand, the coverage optimization algorithm is based on probability theory, which finds out the minimum number of transmitters and their corresponding positions in order to achieve optimal indoor wireless coverage. Both of the space and time complexities of the proposed algorithm surpass the existing algorithms. For the verification of the proposed ray tracing technique and coverage algorithm, detailed simulation results for different scattering factors, different antenna types, and different operating frequencies are presented. Furthermore, the proposed technique is verified by the experimental results.
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48

Bruno, Luigi, Paolo Addesso, and Rocco Restaino. "Indoor Positioning in Wireless Local Area Networks with Online Path-Loss Parameter Estimation." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/986714.

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Location based services are gathering an even wider interest also in indoor environments and urban canyons, where satellite systems like GPS are no longer accurate. A much addressed solution for estimating the user position exploits the received signal strengths (RSS) in wireless local area networks (WLANs), which are very common nowadays. However, the performances of RSS based location systems are still unsatisfactory for many applications, due to the difficult modeling of the propagation channel, whose features are affected by severe changes. In this paper we propose a localization algorithm which takes into account the nonstationarity of the working conditions by estimating and tracking the key parameters of RSS propagation. It is based on a Sequential Monte Carlo realization of the optimal Bayesian estimation scheme, whose functioning is improved by exploiting the Rao-Blackwellization rationale. Two key statistical models for RSS characterization are deeply analyzed, by presenting effective implementations of the proposed scheme and by assessing the positioning accuracy by extensive computer experiments. Many different working conditions are analyzed by simulated data and corroborated through the validation in a real world scenario.
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49

Fayadh, Rashid Ali, Mohd Fareq Abd Malek, Hilal Adnan Fadhil, and Norshafinash Saudin. "Performance Evaluation of Adaptive Indoor Matched Rake Receiver Using Multiple-Combining Techniques." Applied Mechanics and Materials 699 (November 2014): 921–30. http://dx.doi.org/10.4028/www.scientific.net/amm.699.921.

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This paper discusses the enhancement of the wireless rake receiver for high speed and short distance indoor ultra wideband (UWB) propagation with line-of sight (LOS) and non line-of sight (NLOS) channel models. The proposed matched rake receiver uses three main combining techniques, maximum ratio combining (MRC), equal gain combining (EGC), and selective combining (SC) to capture most of the energy of the multi-path components (MPCs). When the wireless communication systems work with high capacity and high speed in transmission and reception scenarios, there will be a serious challenge defined as inter-symbol interference (ISI) during the reception process. The ISI causes increasing in the bit error rate (BER) when the wireless communication systems work with high bit rate propagation. The matched rake receiver scheme was designed to suppress ISI by maximizing the signal to noise ratio (SNR) before constructing the desired signal in decision circuit and effectively the system enhancement is improved. After adding additive white Gaussian noise (AWGN) to the received signal, the improvement is cleared comparing with the theoretical results that has no AWGN. During the comparison of the simulation results, MRC partial rake receiver of less complexity showed better performance than the EGC and SC rake receivers.
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Majed, Mohammed Bahjat, Tharek Abd Rahman, Omar Abdul Aziz, Mohammad Nour Hindia, and Effariza Hanafi. "Channel Characterization and Path Loss Modeling in Indoor Environment at 4.5, 28, and 38 GHz for 5G Cellular Networks." International Journal of Antennas and Propagation 2018 (September 20, 2018): 1–14. http://dx.doi.org/10.1155/2018/9142367.

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The current propagation models used for frequency bands less than 6 GHz are not appropriate and cannot be applied for path loss modeling and channel characteristics for frequency bands above 6 GHz millimeter wave (mmWave) bands, due to the difference of signal propagation characteristics between existing frequency bands and mmWave frequency bands. Thus, extensive studies on channel characterization and path loss modeling are required to develop a general and appropriate channel model that can be suitable for a wide range of mmWave frequency bands in its modeling parameter. This paper presents a study of well-known channel models for an indoor environment on the 4.5, 28, and 38 GHz frequency bands. A new path loss model is proposed for the 28 GHz and 38 GHz frequency bands. Measurements for the indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios were taken every meter over a separation distance of 23 m between the TX and RX antenna locations to compare the well-known and the new large-scale generic path loss models. This measurement was conducted in a new wireless communication center WCC block P15a at Universiti Teknologi Malaysia UTM Johor, Malaysia, and the results were analyzed based on the well-known and proposed path loss models for single-frequency and multifrequency models and for directional and omnidirectional path loss models. Results show that the large-scale path loss over distance could be modeled better with good accuracy by using the simple proposed model with one parameter path loss exponent PLE (n) that is physically based to the transmitter power, rather than using the well-known models that have no physical base to the transmitted power, more complications (require more parameters), and lack of anticipation when explaining model parameters. The PLE values for the LOS scenario were 0.92, 0.90, and 1.07 for the V-V, V-H, and V-Omni antenna polarizations, respectively, at the 28 GHz frequency and were 2.30, 2.24, and 2.40 for the V-V, V-H, and V-Omni antenna polarizations, respectively, at the 38 GHz frequency.
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