Inter- and Intrasite Correlations of Large-Scale Parameters from Macrocellular Measurements at 1800 MHz

Jalden, Niklas; Zetterberg, Per; Ottersten, Björn; García, Laura

doi:10.1155/2007/25757

Cited by 50 publications

(58 citation statements)

References 18 publications

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“…Shadowing represents the variability of the logarithm of the received power around its expected value: we denote this quantity S, with VAR{S} < ∞. The small-scale effect of fading has been removed in the spatial dimension by averaging over a local region [45] of about 50 wavelengths [56], [62], that is, approximately 8-34 m for classic cellular channels [18], [24], [25], [27], [29], [37], [38].…”

Section: Types Of Correlationmentioning

confidence: 99%

“…Several field measurements have been performed [18], [24], [28], [29], [33], [34], [36]- [38] to gather data about the true physical correlation model, which we callh. Field measurements produce a set of data points, from which an estimate of the cross-correlation function, which we callĥ, is obtained by fitting the data with plausible-looking simple mathematical functions.…”

Section: B Cross-correlation As Spatial-only Correlationmentioning

confidence: 99%

“…In such cases,ĥ is expressed as a function of a single free variable. The most common forms are the following: 1) absolute distance (between Y 1 and Y 2 ) [24]- [26], [28], [31], [32], [36]- [39]: d = r 1 − r 2 ; 2) angle (not oriented) of arrival separation [24], [28], [33], [34], [36]- [38], [56]:…”

Section: Collapsing Correlation Onto One Dimensionmentioning

confidence: 99%

“…The most common autocorrelation model is a decaying exponential of distance [6], [8], [25], [26], [31], [36], [38]- [40], [42], [45], [48], [49], [51], [52], [56], [62], [70], [73], [74], [78], [80], [84]- [88]. This model is often attributed to Gudmundson [26], although the less-cited work of Marsan et al [25] also proposes this model, and measurements by Graziano [24,Figs.…”

Section: ) Exponential Modelmentioning

confidence: 99%

“…The use of the θ and R dimensions for shadowing correlation models has been argued in [37], [38], [45], [56], [62], and [72], although separability may be a simplistic assumption [56].…”

Section: ) Angle-distance Ratiomentioning

confidence: 99%

See 4 more Smart Citations

On the Feasibility of Wireless Shadowing Correlation Models

Szyszkowicz

Yanıkömeroğlu

Thompson

2010

IEEE Trans. Veh. Technol.

164

125

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Abstract-There is emerging interest in more detailed models for wireless shadowing, which may include nonconstant shadowing variance, non-lognormal shadowing, and, most importantly, correlation between paths; we focus on this last aspect. This paper offers a structured synthesis of the existing literature on autocorrelation and cross-correlation in wireless shadowing and attempts to fill existing gaps in the analysis of correlation models. We make a survey of these models and argue, as has previously been observed, that certain models are not mathematically feasible, which may lead to problems in simulations or analysis. We then state some theorems that test whether the models are positive semidefinite, which is the central necessary condition for feasibility, and evaluate the existing models accordingly. Additionally, we evaluate the models according to their physical plausibility, which leads us to choose one model among many as arguably the best one in existence so far. This paper should be useful as a guide on how to implement shadowing correlation in one's work, how to choose an appropriate correlation model, and how to modify existing models or create new models so that they fulfill mathematical feasibility.

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Section: Types Of Correlationmentioning

confidence: 99%

Section: B Cross-correlation As Spatial-only Correlationmentioning

confidence: 99%

Section: Collapsing Correlation Onto One Dimensionmentioning

confidence: 99%

Section: ) Exponential Modelmentioning

confidence: 99%

“…The use of the θ and R dimensions for shadowing correlation models has been argued in [37], [38], [45], [56], [62], and [72], although separability may be a simplistic assumption [56].…”

Section: ) Angle-distance Ratiomentioning

confidence: 99%

See 3 more Smart Citations

On the Feasibility of Wireless Shadowing Correlation Models

Szyszkowicz

Yanıkömeroğlu

Thompson

2010

IEEE Trans. Veh. Technol.

164

125

View full text Add to dashboard Cite

show abstract

Analysis of fading statistics in cellular mobile communication systems

Loni

Khan

2012

J Supercomput

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Power Adaptation for Cognitive Radio Systems Under an Average SINR Loss Constraint in the Absence of Path Loss Information

Dulek

Gezici

Sawai

et al. 2013

Wireless Pers Commun

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An upper bound is derived on the capacity of a cognitive radio system by considering the effects of path loss and log-normal shadowing simultaneously for a single-cell network. Assuming that the cognitive radio is informed only of the shadow fading between the secondary (cognitive) transmitter and primary receiver, the capacity is achieved via the water-filling power allocation strategy under an average primary signal to secondary interference plus noise ratio loss constraint. Contrary to the perfect channel state information requirement at the secondary system (SS), the transmit power control of the SS is accomplished in the absence of any path loss estimates. For this purpose, a method for estimating the instantaneous value of the shadow fading is also presented. A detailed analysis of the proposed power adaptation strategy is conducted through various numerical simulations.

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Inter- and Intrasite Correlations of Large-Scale Parameters from Macrocellular Measurements at 1800 MHz

Cited by 50 publications

References 18 publications

On the Feasibility of Wireless Shadowing Correlation Models

On the Feasibility of Wireless Shadowing Correlation Models

Analysis of fading statistics in cellular mobile communication systems

Power Adaptation for Cognitive Radio Systems Under an Average SINR Loss Constraint in the Absence of Path Loss Information

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