A Two-Dimensional Channel Simulation Model for Shadowing Processes

Xiaodong Cai; Georgios B. Giannakis

doi:10.1109/TVT.2003.819627

A Two-Dimensional Channel Simulation Model for Shadowing Processes

Xiaodong Cai, Georgios B. Giannakis

Research output: Contribution to journal › Article › peer-review

77 Scopus citations

Abstract

A Gaussian random process with a given power spectral density (PSD) function can be modeled as a sum of sinusoids (SOS), and has been widely used to simulate Rayleigh-fading communication channels. The conventional one-dimensional (1-D) channel model cannot capture the spatial correlation of shadowing processes. We here develop a two-dimensional (2-D) SOS-based channel model to simulate the shadowing process. Three methods to fit the PSD of the simulated process to the true channel's PSD are explored. Performance of the proposed channel simulator is analyzed in terms of the autocorrelation function of the simulated shadowing process. Simulations illustrate the potential of the proposed channel simulation model.

Original language	English (US)
Pages (from-to)	1558-1567
Number of pages	10
Journal	IEEE Transactions on Vehicular Technology
Volume	52
Issue number	6
DOIs	https://doi.org/10.1109/TVT.2003.819627
State	Published - Nov 2003
Externally published	Yes

Keywords

Channel model
Shadowing
Spatial correlation
Sum of sinusoids

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Networks and Communications

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title = "A Two-Dimensional Channel Simulation Model for Shadowing Processes",

abstract = "A Gaussian random process with a given power spectral density (PSD) function can be modeled as a sum of sinusoids (SOS), and has been widely used to simulate Rayleigh-fading communication channels. The conventional one-dimensional (1-D) channel model cannot capture the spatial correlation of shadowing processes. We here develop a two-dimensional (2-D) SOS-based channel model to simulate the shadowing process. Three methods to fit the PSD of the simulated process to the true channel's PSD are explored. Performance of the proposed channel simulator is analyzed in terms of the autocorrelation function of the simulated shadowing process. Simulations illustrate the potential of the proposed channel simulation model.",

keywords = "Channel model, Shadowing, Spatial correlation, Sum of sinusoids",

author = "Xiaodong Cai and Giannakis, {Georgios B.}",

note = "Funding Information: Manuscript received December 27, 2001; revised April 7, 2003, June 27, 2003, August 21, 2003, and September 4, 2003. This work was supported by the NSF Wireless Initiative Grant 9979443, and prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government.",

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N2 - A Gaussian random process with a given power spectral density (PSD) function can be modeled as a sum of sinusoids (SOS), and has been widely used to simulate Rayleigh-fading communication channels. The conventional one-dimensional (1-D) channel model cannot capture the spatial correlation of shadowing processes. We here develop a two-dimensional (2-D) SOS-based channel model to simulate the shadowing process. Three methods to fit the PSD of the simulated process to the true channel's PSD are explored. Performance of the proposed channel simulator is analyzed in terms of the autocorrelation function of the simulated shadowing process. Simulations illustrate the potential of the proposed channel simulation model.

AB - A Gaussian random process with a given power spectral density (PSD) function can be modeled as a sum of sinusoids (SOS), and has been widely used to simulate Rayleigh-fading communication channels. The conventional one-dimensional (1-D) channel model cannot capture the spatial correlation of shadowing processes. We here develop a two-dimensional (2-D) SOS-based channel model to simulate the shadowing process. Three methods to fit the PSD of the simulated process to the true channel's PSD are explored. Performance of the proposed channel simulator is analyzed in terms of the autocorrelation function of the simulated shadowing process. Simulations illustrate the potential of the proposed channel simulation model.

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