Propagation channel characterization for mobile communication based on measurement campaign and simulation (original) (raw)
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IEEE Antennas and Propagation Magazine, 2003
In order to estimate the signal parameters accurately for mobile systems, it is necessary to estimate a system's propagation characteristics through a medium. Propagation analysis provides a good initial estimate of the signal characteristics. The ability to accurately predict radio-propagation behavior for wireless personal communication systems, such as cellular mobile radio, is becoming crucial to system design. Since site measurements are costly, propagation models have been developed as a suitable, low-cost, and convenient alternative. Channel modeling is required to predict path loss and to characterize the impulse response of the propagating channel. The path loss is associated with the design of base stations, as this tells us how much a transmitter needs to radiate to service a given region. Channel characterization, on the other hand, deals with the fidelity of the received signals, and has to do with the nature of the waveform received at a receiver. The objective here is to design a suitable receiver that will receive the transmitted signal, distorted.due to the multipath and dispersion effects of the channel, and that will decode the transmitted signal. An understanding of the various propagation models can. actually address both problems. This paper begins with a review of the information available on the various propagation models for both indoor and outdoor environments. .The existing models can be classified into two major classes: statistical models and site-specific models. The main characteristics of the radio channelsuch as path loss, fading, and time-delay spreadare discussed. Currently, a third alternative, which includes many new numerical methods, is being introduced to propagation prediction. The advantages and disadvantages of some of these methods are summarized. In'addition, an impulse-response characterization for the propagation path is also presented, including models for small-scale fading. Finally, it is shown that when two-way communication ports can be defined for a mobile system, it is possible to use reciprocity to focus the energy along the direction of an intended user without any explicit knowledge of the electromagnetic environment in which the system is operating, or knowledge of the spatial locations of the transmitter and the receiver.
Bulletin of the National Research Centre
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 a...
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This paper presents the performance analysis of different empirical radio propagation models used in wireless cellular networks. It particular, the parameters such as path loss and cell coverage area are studied for different cellular networks from second generation (2G) to fifth generation (5G). Accurate prediction of path loss and coverage area is highly desirable for planning of any wireless communication systems. Considering the urban terrain, the comparison is made between Hata model, Stanford University Interim (SUI) model, and modified SUI models. As a motivation for new millimeter wave (mm-wave) cellular systems, i.e., for 5G communication, the analysis is performed at 28 GHz. Considering -75 dBm as the desired minimum received power, it is observed that 2G communication (at 900 MHz using Hata model) experiences the lowest path loss and thus results into largest coverage area. The path loss is observed to be maximum for the future mm-wave systems (at 28 GHz using modified SU...
Review On Classification Of Channel Models And Determination Of The Parameters For Channel Modeling
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Communicating knowledge from one location to different locations needs some type of medium. These communication media, uses 2 varieties of media: Wired and Wireless. The medium is employed to convey the knowledge in analog or digital format from one or many senders or transmitters, to one or many receivers. When the information is propagating from source to destination, it under goes different changes because of diverse sorts of disorders, errors brought in as a result of the clamor into the information, delay spread, numerous reflections and so forth. The received information won't be same as the information that has been transmitted by the source. Many of the channel parameters will affect the data that is being communicated to the receiver. This paper presents parametric analysis of a communication system and presents the method of selection of parameters that together present a composite communication system.
International Journal of Electrical and Computer Engineering (IJECE), 2023
Pathloss is a key element that causes signal deterioration in the channel as the signal power reduces inversely with propagation distance, this deterioration experienced by the channel is majorly as a result of reflection, absorption, and scattering of the signal. This study however takes into consideration the radio path loss for precise base station (BS), frequency, and power adjustment prediction evaluated over a frequency of 2.3 GHz. With a distance range between 0.1 and 1.5 km for collection of data on the measured received signal strength (MRSS), five empirical models and a modified model were used to validate the measured data to determine their suitability for pathloss prediction