On the statistical properties of deterministic simulation models for mobile fading channels

Pätzold, Matthias; Killat, Ulrich; Laue, F.; Li, Yingchun

doi:10.1109/25.661052

Cited by 205 publications

(132 citation statements)

References 21 publications

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“…Observe that (22) has the similar form as LCR for Rice fading model given by (21). In the case of Hoyt fading model, N + ϑ (π) has the same form as LCR for the Rayleigh fading [17].…”

Section: Phase Level-crossing Ratementioning

confidence: 80%

“…There are several methods for computation of these quantities. We used Method of Exact Doppler Spread (MEDS) described in [22]. According to MEDS, simulation parameters are given by c i, (17) and (19)) and by simulation.…”

Section: Simulationmentioning

confidence: 99%

“…A deterministic method, based on the Rice's sum of sinusoids and described in [21,22] is used. Recall that in this model, Gaussian processes µ i (t) (i = 1, 2 ) are approximated by the following sum of cosine wavesμ…”

Section: Simulationmentioning

confidence: 99%

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On The Phase Crossing Statistics and Random FM Noise in Generalized Rice Fading Channels

Petković¹,

Stefanović²

2012

Journal of Electrical Engineering

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In this paper we consider phase process second order statistics of generalized Rice (Beckmann) multipath fading channel. Closed-form expression for JPDF of phase and random FM noise is derived. Furthermore expressions for the PDF and CDF of random FM noise are obtained. The level-crossing rate of the phase process is then obtained for any phase crossing level. Obtained expressions reduces to known ones for Hoyt, Rice and Rayleigh fading channels, since these are the special cases of generalized Rice fading channel. Moreover, derived analytical expressions are compared with results obtained by computer simulation where excellent agreement is achieved. Presented results can be applied for analyzing the statistics of FM spikes in the case of data transmission over generalized Rice fading channels.

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“…Observe that (22) has the similar form as LCR for Rice fading model given by (21). In the case of Hoyt fading model, N + ϑ (π) has the same form as LCR for the Rayleigh fading [17].…”

Section: Phase Level-crossing Ratementioning

confidence: 80%

Section: Simulationmentioning

confidence: 99%

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On The Phase Crossing Statistics and Random FM Noise in Generalized Rice Fading Channels

Petković¹,

Stefanović²

2012

Journal of Electrical Engineering

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“…However, in order to reproduce the desired channel characteristics in simulations, a careful selection of the simulator parameters is essential. For this reason, several methods for an accurate computation of the model parameters of SOS simulators have been developed [39,40,[44][45][46][47]. One such method for the parameter computation, which is referred to as the generalized method of exact Doppler spread (GMEDS 1 ) [48], has been employed in this work.…”

Section: Numerical Resultsmentioning

confidence: 99%

Mobile-to-mobile fading channels in amplify-and-forward relay systems under line-of-sight conditions: statistical modeling and analysis

Talha

Pätzold

2010

Ann. Telecommun.

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This paper deals with the modeling and analysis of narrowband mobile-to-mobile (M2M) fading channels for amplify-and-forward relay links under line-of-sight (LOS) conditions. It is assumed that a LOS component exists in the direct link between the source mobile station (SMS) and the destination mobile station (DMS), as well as in the links via the mobile relay (MR). The proposed channel model is referred to as the multiple-LOS second-order scattering (MLSS) channel model. The MLSS channel model is derived from a second-order scattering process, where the received signal is modeled in the complex baseband as the sum of a single and a double scattered component. Analytical expressions are derived for the mean value, variance, probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the received envelope of MLSS channels. The PDF of the channel phase is also investigated. It is observed that the LOS components and the relay gain have a significant influence on the statistics of MLSS channels. It is also shown that MLSS channels include various other channel models as special cases, e.g., double Rayleigh channels, double Rice channels, single-LOS doublescattering (SLDS) channels, non-line-of-sight (NLOS) second-order scattering (NLSS) channels, and single-LOS second-order scattering (SLSS) channels. The correctness of all analytical results is confirmed by simulations using a high performance channel simulator. Our novel MLSS channel model is of significant importance for the system level performance evaluation of M2M communication systems in different M2M propagation scenarios. Furthermore, our studies pertaining to the fading behavior of MLSS channels are useful for the design and development of relay-based cooperative wireless networks.

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“…Markov states are associated with each of the two channels obtained from 4 MIMO channels (2 co-polar and 2 cross-polar) resulting in 4 channels for each MIMO channel. Now Rician factor is defined using polynomial approach for large scale fading and Rician samples are generated by Rice's sum of sinusoids method (Pätzold et al, 1998). The average correlation coefficient value can be calculated on the basis of small scale MIMO channel correlation measurement data.…”

Section: Empirical-statistical Mimo Channel Models For Satellitesmentioning

confidence: 99%

MIMO Channel Modelling for Satellite Communications

Mohammed¹,

Mehmood²

2010

Satellite Communications

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On the statistical properties of deterministic simulation models for mobile fading channels

Cited by 205 publications

References 21 publications

On The Phase Crossing Statistics and Random FM Noise in Generalized Rice Fading Channels

On The Phase Crossing Statistics and Random FM Noise in Generalized Rice Fading Channels

Mobile-to-mobile fading channels in amplify-and-forward relay systems under line-of-sight conditions: statistical modeling and analysis

MIMO Channel Modelling for Satellite Communications

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