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This paper presents a 3D ray-tracing model using geometrical optics and the uniform theory of diffraction in radio channel characterizations of macrocellular environments. On the basis of the environmental information obtained from a digitized map, the model is effectively applied. A technique considering multiple reflections and diffractions through the ray path classification is utilized in this model. Ray paths belonging to each ray category are determined using different methods. The proposed model is justified (the prediction accuracy of the model is better than 6.5 dB) with measurement data for the two scenarios and can provide reliable theory as a basis for radio wave propagation prediction and network planning in urban macrocellular environments. [ABSTRACT FROM AUTHOR]

The traditional malware research is mainly based on its recognition and detection as a breakthrough point, without focusing on its propagation trends or predicting the subsequently infected nodes. The complexity of network structure, diversity of network nodes, and sparsity of data all pose difficulties in predicting propagation. This paper proposes a malware propagation prediction model based on representation learning and Graph Convolutional Networks(GCN) to address the aforementioned problems. First, to solve the problem of the inaccuracy of infection intensity calculation caused by the sparsity of node interaction behavior data in the malware propagation network, a mechanism based on a tensor to mine the infection intensity among nodes is proposed to retain the network structure information. The influence of the relationship between nodes on the infection intensity is also analyzed. Second, given the diversity and complexity of the content and structure of infected and normal nodes in the network, considering the advantages of representation learning in data feature extraction, the corresponding representation learning method is adopted for the characteristics of infection intensity among nodes. This can efficiently calculate the relationship between entities and relationships in low dimensional space to achieve the goal of low dimensional, dense, and real-valued representation learning for the characteristics of propagation spatial data. We also design a new method, Tensor2vec, to learn the potential structural features of malware propagation. Finally, considering the convolution ability of GCN for non-Euclidean data, we propose a dynamic prediction model of malware propagation based on representation learning and GCN to solve the time effectiveness problem of the malware propagation carrier. The experimental results show that the proposed model can effectively predict the behaviors of the nodes in the network and discover the influence of different characteristics of nodes on the malware propagation situation.

Studying information diffusion in SNS (Social Networks Service) has remarkable significance in both academia and industry. Theoretically, it boosts the development of other subjects such as statistics, sociology, and data mining. Practically, diffusion modeling provides fundamental support for many downstream applications (e.g., public opinion monitoring, rumor source identification, and viral marketing). Tremendous efforts have been devoted to this area to understand and quantify information diffusion dynamics. This survey investigates and summarizes the emerging distinguished works in diffusion modeling. We first put forward a unified information diffusion concept in terms of three components: information, user decision, and social vectors, followed by a detailed introduction of the methodologies for diffusion modeling. And then, a new taxonomy adopting hybrid philosophy (i.e., granularity and techniques) is proposed, and we made a series of comparative studies on elementary diffusion models under our taxonomy from the aspects of assumptions, methods, and pros and cons. We further summarized representative diffusion modeling in special scenarios and significant downstream tasks based on these elementary models. Finally, open issues in this field following the methodology of diffusion modeling are discussed. [ABSTRACT FROM AUTHOR]

Studying information diffusion in SNS (Social Networks Service) has remarkable significance in both academia and industry. Theoretically, it boosts the development of other subjects such as statistics, sociology, and data mining. Practically, diffusion modeling provides fundamental support for many downstream applications (e.g., public opinion monitoring, rumor source identification, and viral marketing). Tremendous efforts have been devoted to this area to understand and quantify information diffusion dynamics. This survey investigates and summarizes the emerging distinguished works in diffusion modeling. We first put forward a unified information diffusion concept in terms of three components: information, user decision, and social vectors, followed by a detailed introduction of the methodologies for diffusion modeling. And then, a new taxonomy adopting hybrid philosophy (i.e., granularity and techniques) is proposed, and we made a series of comparative studies on elementary diffusion models under our taxonomy from the aspects of assumptions, methods, and pros and cons. We further summarized representative diffusion modeling in special scenarios and significant downstream tasks based on these elementary models. Finally, open issues in this field following the methodology of diffusion modeling are discussed. [ABSTRACT FROM AUTHOR]

Social media, such as Facebook and WeChat, empowers millions of users to create, consume, and disseminate online information on an unprecedented scale. The abundant information on social media intensifies the competition of WeChat Public Official Articles (i.e., posts) for gaining user attention due to the zero-sum nature of attention. Therefore, only a small portion of information tends to become extremely popular while the rest remains unnoticed or quickly disappears. Such a typical “long-tail” phenomenon is very common in social media. Thus, recent years have witnessed a growing interest in predicting the future trend in the popularity of social media posts and understanding the factors that influence the popularity of the posts. Nevertheless, existing predictive models either rely on cumbersome feature engineering or sophisticated parameter tuning, which are difficult to understand and improve. In this paper, we study and enhance a point process-based model by incorporating visual reasoning to support communication between the users and the predictive model for a better prediction result. The proposed system supports users to uncover the working mechanism behind the model and improve the prediction accuracy accordingly based on the insights gained. We use realistic WeChat articles to demonstrate the effectiveness of the system and verify the improved model on a large scale of WeChat articles. We also elicit and summarize the feedback from WeChat domain experts. [ABSTRACT FROM AUTHOR]

This paper investigates the impacts that open-trench drains make on the accuracy of radio propagation prediction in an urban city environment. Compared with conventional prediction styles that assume the ground to be flat, in this paper, we have considered for the first time the real scenario in many Asian cities to make open-trench drains inclusive in radio propagation modeling. The aims of this paper are twofold. First, to scrutinize one narrow L-shaped structure, modeled after an open-trench drain, by means of comparing ray-tracing simulation results with the actual field measurement results at 2.4 and 5.8 GHz. Second, to compare one city model built without and with the inclusion of open-trench drains for running ray-tracing simulation in yielding radio propagation prediction results. The findings from this paper are especially beneficial to the improvement of mobile communications in extraordinary environments such as open-trench drains, caves, coal mines, underground passageway, and others. Besides, they provide a unique insight into how the presence of the open-trench drains may affect radio wave propagation in an urban city environment.

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Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics. Graphical Abstract: [ABSTRACT FROM AUTHOR]

Notable changes in the next-generation wireless communication system include the fact that the nominal height of base-station antennas becomes lower than the height of typical rooftops. In this scenario, reflection and scattering of waves become more dominant than diffraction in short-range propagation. We first analyze the reflection and scattering loss of propagation by using ray-tracing simulation, and on the basis of the analysis, we propose a propagation prediction model based on geometric optics in the urban street canyon scenario. The proposed model is defined by geometrical parameters such as the street width and the distance to a corner, such that the model can be applied to various environmental scenarios. It can also simultaneously predict propagation losses in many corners. The proposed model is justified with measurement data. [ABSTRACT FROM PUBLISHER]

The article presents a study on the prediction quality of the ITS HF Propagation application suite: VOACAP (Voice of America Coverage Analysis Program), ICEPAC (Enhanced Profile Ionospheric Communications Circuit Analysis and Prediction Program) and REC533 (ITU Recommendation RS 533) for point to point connections of the NVIS (Near Vertical Incidence Sky-wave) type. The simulation results were compared to the measurements obtained on a NVIS direction carried out in Romania and with the measurement results obtained and published by Walden in [1] for a NVIS network established in the UK. Compared with the measurement data obtained in Romania, the results predicted by the three applications have achieved average values of the correlation factors. These low values regarding the quality of a predictive application are due to the short observation period of the ionospheric channel. In these circumstances, REC533 achieved the lowest mean value of the standard deviations compared to VOACAP and ICEPAC. Regarding the measurement results published by Walden, the three applications have achieved strong values. These results lead to high values of the coefficient of determination, ensuring a very good power of prediction. REC533 provided the most correlated values and the lowest average value of standard deviations. The results provided by ICEPAC and VOACAP are highly correlated for each month under review. Of the three applications analysed, the best predictions were obtained by REC533. [ABSTRACT FROM AUTHOR]

An approach that predicts the propagation, models the terrestrial receivers and optimizes the performance of single frequency networks (SFN) for digital video broadcasting in terms of the final coverage achieved over any geographical region, enhancing the most populated areas, is proposed in this paper. The effective coverage improvement and thus, the self-interference reduction in the SFN is accomplished by optimizing the internal static delays, sector antenna gain, and both azimuth and elevation orientation for every transmitter within the network using the heuristic simulated annealing (SA) algorithm. Decimation and elevation filtering techniques have been considered and applied to reduce the computational cost of the SA-based approach, including results that demonstrate the improvements achieved. Further representative results for two SFN in different scenarios considering the effect on the final coverage of optimizing any of the transmitter parameters previously outlined or a combination of some of them are reported and discussed in order to show both, the performance of the method and how increasing gradually the complexity of the model for the transmitters leads to more realistic and accurate results. [ABSTRACT FROM AUTHOR]

In this paper, the validity of Recommendation ITU-R P.1546 in a short-range terrestrial environment is analyzed. Its three versions (P.1546, P.1546-1, and P.1546-2) are compared against simple models and evaluated using measurement results that were obtained by utilizing the pilot signal of a commercial code-division multiple-access mobile telephone network. Measurement results show that P.1546-2, on average, underestimates the field strength by more than 10 dB for typical Australian rural areas. However, it improves the error standard deviation compared to previous versions. The causes of these effects and the suggestions for further development of the Recommendation are discussed and evaluated. [ABSTRACT FROM AUTHOR]

Conventional geometrical database models (GDMs) in ray tracing require vectorization of building information, thus cannot achieve datum-extraction from line-based GIS maps efficiently, in which the building layouts are mainly stored in scalar lines. A novel GDM with an improved algorithm in 2D/2.5D cases is proposed according to this kind of map. A comparison between the simulation and measurement results verifies the validity of the new model and method. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 43: 307–310, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20453 [ABSTRACT FROM AUTHOR]

In mobile communications, such as the cordless telephone, it is important to identify the service area for situations where a base station is installed indoors. However, the mix of walls, columns, and partitions in the typical indoor environment makes it difficult to develop a precise signal propagation estimation formula. The ray-tracing method provides a precise method for the estimation of electric field strengths. Although this method provides a relatively facile way of estimating the electric field strength by simply determining the geometric tracing between sender and receiver, an increase in the number of structural components, such as walls, columns, and partitions, results in a rapid increase in the required processing time. Therefore, the practical utilization of an area prediction system requires an increase in processing speed. This paper proposes a ray-trace-based algorithm that permits high-speed processing. It also describes an indoor area prediction system, IMAP, that has been developed based on the proposed algorithm, and discusses its prediction accuracy. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 86(10): 60–72, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.10189 [ABSTRACT FROM AUTHOR]

In this letter, an integrated application of the prediction for radio wave propagation with the Geographic Information System (GIS) is presented and a real prediction system based on GIS is implemented. [ABSTRACT FROM AUTHOR]

The ray-tracing technique does not take into account the effects of the inner structure of walls for indoor propagation prediction. A numerical approach to consider this problem using the FDTD method is presented. Numerical results of the path loss calculated by the FDTD method are compared to those obtained by the ray-tracing technique. © 2001 John Wiley & Sons, Inc. Microwave Opt Technol Lett 29: 19–21, 2001. [ABSTRACT FROM AUTHOR]