The COST 259 Directional Channel Model-Part II: Macrocells

Asplund, Henrik; Glazunov, Andrés Alayón; Molisch, Andreas F.; Pedersen, Klaus I.; Steinbauer, M.

doi:10.1109/twc.2006.256967

Cited by 168 publications

(124 citation statements)

References 48 publications

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…Each visibility region is a circle of radius R C . The probability distributions that determine the placing of the scatterers and their corresponding visibility regions are specified in [16], [18]. A mobile located within a scatterer's visibility region experiences multipath dispersion due to that scatterer cluster.…”

Section: A Cost259 Channel Model For Macrocellsmentioning

confidence: 99%

“…For this purpose, we use the COST259 stochasticgeometric macrocellular channel model proposed by the European Cooperation on Science and Technology (COST) project. The model is among the most comprehensive models available currently [16]- [18]. It builds upon the COST231 studies, is widely supported for realistic simulations of WCDMA, and incorporates the results of several extensive measurement campaigns, e.g., [11], [12], [15], [19].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Macrocell-Wide Behavior of the Orthogonality Factor in WCDMA Downlinks

Mehta

Molisch

Greenstein

2006

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

The orthogonality factor (OF) quantifies the loss of orthogonality between the signals transmitted simultaneously on a wideband code division multiple access (WCDMA) downlink due to multipath dispersion. It is one of the fundamental parameters that determines the signalto-interference-plus-noise ratio at the output of the Rake receiver and, consequently, it has a significant impact on downlink system capacity. The OF depends greatly on the delay profile of the multipath channel between the mobile and its serving base station; this profile varies considerably from one location in the cell to another. In this paper, we study how the statistical properties of the small-scale-fading-averaged OF vary over the entire macrocellular area. We use an ensemble of channel profiles at different locations in a cell generated from an implementation of the comprehensive COST259 channel model, which incorporates results from several experimental investigations. We show that the small-scale-fading-averaged OF is itself a random variable whose statistics depend on the mobile's distance from its serving base station. The large observed variance of the OF indicates that using a single value for all users in downlink capacity analyses and simulations, as has been the practice, may lead to erroneous conclusions. Finally, we propose a simple model that closely matches the statistics of the OF as a function of mobileto-base distance, thus obviating the need to set up the complicated channel model every time OF values are to be generated. IEEE Transactions on Wireless Communications (2006)This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Abstract-The orthogonality factor (OF) quantifies the loss of orthogonality between the signals transmitted simultaneously on a wideband code division multiple access (WCDMA) downlink due to multipath dispersion. It is one of the fundamental parameters that determines the signal-to-interference-plus-noise ratio at the output of a Rake receiver and, consequently, it has a significant impact on downlink system capacity. The OF depends greatly on the delay profile of the multipath channel between the mobile and its serving base station; this profile varies considerably from one location in the cell to another.In this paper, we study how the statistical properties of the small-scale-fading-averaged OF vary over the entire macrocellular area. We use an ensemble of channel profiles ...

show abstract

Section: A Cost259 Channel Model For Macrocellsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Macrocell-Wide Behavior of the Orthogonality Factor in WCDMA Downlinks

Mehta

Molisch

Greenstein

2006

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

show abstract

“…This consideration originates from our efforts to contribute to the RCM development within COST projects, namely parameterization for COST 259 and COST 273 models [1][2][3]. In spite of these models being quite well defined, specific and detailed, there is a permeating lack of parameter definitions.…”

Section: Motivationmentioning

confidence: 99%

“…Historically, these reference channel models would in essence look like random radio-channel generators that would generate random radio-channel characteristics, based upon some previously calculated parameters [1][2][3][4][5]. These parameters themselves were calculated from statistical analysis of available sets of measured radio-channels (data with desired geographical similarities, like sets for indoor scenario, urban scenario, suburban scenario etc.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Benefits and Challenges of Deterministic Reference Channel Models

Mucalo¹,

Zentner

Mataga³

2012

Automatika

View full text Add to dashboard Cite

Original scientific paperThe paper introduces a new paradigm for reference channel models. Current reference channel models are designed as platforms that generate radio channels for testing using random values for their parameters. These parameters follow some pre-established distribution based on process called parameterization, i.e. statistical processing of previous real measurements or accurate ray tracing simulations. The paper argues that random generated channels give either no new insight or even delusive information and should be replaced with the initial set of radio channels that was used for parameterization. Therefore a deterministic reference channel model, as an emulator of previously recorded real radio channels, is proposed and its potential elaborated.Key words: COST 259, COST 273, Reference radio channel models, MIMO Pogodnosti i izazovi determinističkog referentnog modela radijskog kanala. U radu se uvodi nova paradigma za referentni model radijskog kanala. Postojeći referentni modeli radijskog kanala dizajnirani su kao platforma koja generira radio kanale za testiranje pomoću slučajnih vrijednosti za svoje parametre. Ovi parametri prate neke unaprijed utvr ene raspodjele koje potječu iz procesa parametrizacije, odnosno statističke obrade prethodnih mjerenja ili točnih simulacija metodom slije enja zrake. U radu se tvrdi da slučajno generirani kanali ili ne daju nove uvide iličak daju obmanjujuće informacije i valja ih zamijeniti s početnim skupom radijskih kanala koji je korišten za parametrizaciju. Stoga je predložen deterministički referentni model radijskog kanala, kao emulator prethodno snimljenih stvarnih radio kanala, te je njegov potencijal razra en.Ključne riječi: COST 259, COST 273, referentni model radijskog kanala, MIMO

show abstract

Ray entity based postprocessing of ray‐tracing data for continuous modeling of radio channel

Mataga¹,

Zentner

Mucalo³

2014

Radio Science

View full text Add to dashboard Cite

Ray-tracing data are usually given as angles of arrival and departure, transmitter and receiver coordinates, ray length and delay, received power level, and polarity. Usually, these values are given in raw data with some resolution that covers the area of interest where the simulation is performed. There are two main drawbacks of such approach: first, a huge amount of storage capacity is typically needed and second, although the area of interest is covered by a certain resolution, it is nearly impossible to interpolate between sample points and new time, and memory consuming simulations are necessary in order to increase the resolution of the simulations. This paper addresses the two mentioned drawbacks of ray tracing, suggesting a procedure based on the concept of ray entities both to enable continuous interpolation of ray-tracing data and reduce the memory needed for storing data. Ray entity is a set of rays that all undergo the same series of propagation phenomena (direct ray, diffraction, reflection, or scattering) on the same objects (building walls or edges). The method is given and illustrated for reflection and diffraction phenomena, and diffuse scattering was not included, but discussion is easily extended to this propagation type as well. The paper gives detailed statistics of entities' length and rays' count per simulated receiver point in few illustrative examples and provides an insight on how to interpolate angles of arrival and departure, ray length, and received power level in order to provide a continuous description of the radio environment.

show abstract

The COST 259 Directional Channel Model-Part II: Macrocells

Cited by 168 publications

References 48 publications

Macrocell-Wide Behavior of the Orthogonality Factor in WCDMA Downlinks

Macrocell-Wide Behavior of the Orthogonality Factor in WCDMA Downlinks

Benefits and Challenges of Deterministic Reference Channel Models

Ray entity based postprocessing of ray‐tracing data for continuous modeling of radio channel

Contact Info

Product

Resources

About