A survey of various propagation models for mobile communication

Abstract

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.

Performance Analysis of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

“…The physical radio characteristics of each node such as the transmitting power, signal to noise and interference ratio and antenna gain, are chosen to mimic the commercial Lucent's OriNOCO Wireless LAN PC Card [16] with a nominal bit rate of 11Mb/s and a transmission range of 100 meters with an Omni-directional antenna. To gain more realistic signal propagation than with the deterministic free space or tworay ground reflection models [17], the shadowing model is used as a radio propagation [18]. The simulation is allowed to run for 900 seconds for each simulation scenario to avoid immature termination and to keep the simulation time manageable.…”

On the Performance of Counter-Based Broadcast Scheme for Mobile Ad Hoc Networks

“…The physical radio characteristics of each node such as the transmitting power, signal to noise and interference ratio and antenna gain, are chosen to mimic the commercial Lucent's OriNOCO Wireless LAN PC Card (2000) with a nominal bit rate of 11Mb/s and a transmission range of 100 meters with an Omni-directional antenna. To gain more realistic signal propagation than with the deterministic free space or two-ray ground reflection models (Sakar et al, 2003), the shadowing model is used as a radio propagation (Rappaport, 2001). The simulation is allowed to run for 900 seconds for each simulation scenario to avoid immature termination and to keep the simulation time manageable.…”

Teletraffic Performance Analysis of Multi-class OFDM-TDMA Systems with AMC

“…Many models have been proposed at separate layers, e.g., the Rayleigh, Rician and Nakagami fading models at the physical layer [8], and queuing models at the data link layer [6]. In traditional channelized multiple access systems, e.g., TDMA and FDMA, each user is assigned a fixed amount of bandwidth during the whole service time, and the Erlang capacity can be easily obtained by using the well-known Erlang-B formula.…”