Analytic stochastic propagation model for urban streets (original) (raw)
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Stochastic ray propagation for two parallel urban streets: exact and approximate results
IEEE Antennas and Wireless Propagation Letters, 2008
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An Analysis of a Stochastic Urban Propagation Model Using Ray Tracing Generated Results
MILCOM 2007 - IEEE Military Communications Conference, 2007
A stochastic urban electromagnetic propagation model for non-line-of-sight (NLOS) paths was critically examined by comparing model behavior to ray tracing simulations in four city environments. We focus on the quality of model/data fit and the ability to a priori set model parameters based on city geometry and building materials. The stochastic model was found to fit simulated data well in typical cities. However, relating model parameters to city geometry metrics met with limited success. This is most likely due to the difficulty in characterizing city geometry, and the underlying physics of the model. The complex process of electromagnetic propagation is modeled as a simple one-dimensional random work, leading to diffusion-like behavior. The model does possess utility in its ability to provide easily computed estimates of urban propagation path losses and is an improvement over other empirical models.
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Urban communications systems in the UHF band, such as cellular mobile radio, depend on propagation between an elevated antenna and antennas located at street level. While extensive measurements of path loss have been reported, no theoretical model has been developed that explains the effect of buildings on the propagation. The development of such a model is given in which the rows or blocks of buildings are viewed as diffracting cylinders lying on the earth. Representing the buildings as absorbing screens, the propagation process reduces to multiple forward diffraction past a series of screens. Numerical computation of the diffraction effect yields a power law dependence for the field that is within the measured range. Accounting for diffraction down to street level from the rooftops gives an overall path loss whose absolute value is in good agreement with average measured path loss.
A Statistical Model for Urban Radio Propagation
A statistical model, based on extensive experimental data, statistical model behind. Then, a modified Poisson process was was established to characterize the urban radio propagation medium in presented to model the path arrival time since the simple various urban environments. Describing the medium by a linear filter, the peaks of the multipath response were analyzed statistically concem-Poisson model in [ 5 ] failed to fit some experimental data. ing the distribution of the path the path time. The Though the Simflar models appear in [l 1 -I1 3i , there statistical properties of these quantities depend on the modulation to be no previous work on the statistical model of the Path delay time. The resulting model can be used for simulation,experi-arrival time except [ 51 .
IEEE Transactions on Antennas and Propagation, 2000
A multidimensional analysis of multipath propagation in urban micro-and macro-cellular environment has been carried out. Multidimensional measurement data, including path-loss, delay spread and direction-of-arrival are compared with simulations performed with a 3D ray tracing model which takes diffuse scattering into account. The results are analyzed highlighting the dominant propagation mechanisms in the different cases and model performance/shortcomings. In particular, the results show that diffuse scattering plays a key role in urban propagation, with an impact on both narrowband and wideband parameters in most cases. Also, the accuracy and the characteristics of environment representation can have a significant impact on prediction even in simple topologies.
Microwave and Optical Technology Letters, 2002
The statistics of direction of arrival (DOA) in an urban environment are generated based on measurement and ray tracing simulation. The angular power distributions at different locations of the city are fit into the Gaussian angle-of-arrival model. The following four quantities are then extracted as model parameters: The number of incoming DOA, the normalized amplitude of each incoming signal, the mean direction of the incoming signals, and the standard deviation of the incoming signals about the mean direction. It is shown that the statistics of the above four quantities resulting from the simulation are in good agreement with those from the measurement data.
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IEEE Transactions on Communications, 2001
In order to evaluate the performance of third-generation mobile communication systems, radio channel models are required. The models should be capable of handling nonstationary scenarios with dynamic evolution of multipaths. In this context and due to the introduction of advanced antenna systems to exploit the spatial domain, a further expansion is needed in order to include the nonstationary characteristics of the channel. In an attempt to solve these problems, this paper presents a new stochastic spatiotemporal propagation model. The model is a combination of the geometrically-based single reflection and the Gaussian wide-sense stationary uncorrelated scattering models, and is further enhanced in order to be able to handle nonstationary scenarios. The probability density functions of the number of the multipath components, the scatterers' lifetime, and the angle of arrival are calculated to support these features. The input parameters of the model are based on results from measurement campaigns published in the open literature.
A new statistical approach for urban environment propagation modeling
IEEE Transactions on Vehicular Technology, 2002
Field prediction is an essential component of the planning process of cellular radio systems. This task is particularly time-and moneyconsuming in urban environment, where cell size is of the order of a few hundred meters, and the influence of the city structure (building size and dimension, street width, orientation, etc.) cannot be neglected in the field prediction. For this reason, traditional statistical models such as the wellknown Okumura-Hata, cannot be used in this environment, and the prediction is accomplished by means of accurate but time-consuming methods, such as ray-tracing, which require detailed and very expensive databases of the building and street layout of the city under investigation.
IEEE Transactions on Vehicular Technology, 1999
There is an explosive growth in the market of wireless communications services in urban areas. New regulatory environments as well as competition in the communications industry require that these systems be deployed quickly and at low cost. Computer-based radio propagation prediction tools are strong candidates for this goal. In this paper, we introduce an outdoor radio propagation prediction tool using a ray tracing technique in two dimensions (2-D) and three dimensions (3-D). We have compared the predicted and measured results in various propagation environments. Comparisons indicate that 2-D is adequate for a low transmitter while 3-D is recommended for a high transmitter whose height is comparable with or higher than surrounding buildings. In most locations, the computer tool predicts the correct propagation loss with a mean error of less than 7 dB and a standard deviation of less than 8 dB. He is now in the Special Study Division at AT&T Laboratories, Holmdel, NJ. His research interests cover the characterization and modeling of communication channels, communication system performance analysis, propagation modeling of radio waves in buildings and urban environments, wireless communication system design including cellular, PCS, wireless LAN systems, RF communication through power lines, and electromagnetic theory.