2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484) 2003
DOI: 10.1109/vetecf.2003.1285991
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Variable orthogonality factor: a simple interface between link and system level simulation for high speed downlink packet access

Abstract: Detailed simulations of the full physical layer operation of a cellular network are usually performed in two stages, link level and system level. Emergence of new link adaptation and radio resource management techniques together with need for higher modeling accuracy are blurring the line separating these stages. In this paper we address the issue of performing a link level/system level separation and defining the interface between them for simulating High Speed Downlink Packet Access (HSDPA), a part of WCDMA … Show more

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Cited by 9 publications
(6 citation statements)
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“…The residual intracell interference (after Rake processing), arriving at the receiver from the serving base station, is given by [6],…”
Section: B Hsdpa Modelingmentioning
confidence: 99%
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“…The residual intracell interference (after Rake processing), arriving at the receiver from the serving base station, is given by [6],…”
Section: B Hsdpa Modelingmentioning
confidence: 99%
“…O →Ō and L m,i →L m . The orthogonality factor, α, can be calculated in a simple way as described in [6],…”
Section: Release 4 Modelingmentioning
confidence: 99%
“…Figure 2 illustrates the considered system, modeling a MIMO OFDM system incorporating closed loop power allocation algorithms. Equation 15 can be reordered to express the input-output relation as a set of P matrices that involve only one sub-carrier each:…”
Section: Application Of Closed Loop Schemes To Ofdm Wireless Lansmentioning
confidence: 99%
“…Other methodologies can be found in [14] based on PER-prediction indicator, in [15] based on Variable Orthogonality Factor, in [16] based on SINR estimation and [17] based on postdetection SNR. A different approach is described in [18] where a link-to-system interface is developed based on an information theoretic metric and specifically, channel capacity.…”
Section: Convolutionalmentioning
confidence: 99%
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