Radiowave propagation in mobile communications: an overview of European research

Fleury, Bernard Henri; Leuthold, P.E.

doi:10.1109/35.481300

Cited by 76 publications

(36 citation statements)

References 34 publications

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“…This is called uncorrelated scattering (US). Often these two simplifying features are combined (see [7]), leading to the consideration of WSSUS fading channels. For a WSSUS channel, the second moments of have the form (10) Finally, it is often assumed that the random process is a complex Gaussian random process.…”

Section: The Wssus Fading Channelmentioning

confidence: 99%

Broad-band fading channels: signal burstiness and capacity

Subramanian

Hajek

2002

IEEE Trans. Inform. Theory

103

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Abstract-Médard and Gallager recently showed that very large bandwidths on certain fading channels cannot be effectively used by direct sequence or related spread-spectrum systems. This paper complements the work of Médard and Gallager. First, it is shown that a key information-theoretic inequality of Médard and Gallager can be directly derived using the theory of capacity per unit cost, for a certain fourth-order cost function, called fourthegy. This provides insight into the tightness of the bound. Secondly, the bound is explored for a wide-sense-stationary uncorrelated scattering (WSSUS) fading channel, which entails mathematically defining such a channel. In this context, the fourthegy can be expressed using the ambiguity function of the input signal. Finally, numerical data and conclusions are presented for direct-sequence type input signals.Index Terms-Channel capacity, fading channels, spread spectrum, wide-sense-stationary uncorrelated scattering (WSSUS) fading channels.

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Section: The Wssus Fading Channelmentioning

confidence: 99%

Broad-band fading channels: signal burstiness and capacity

Subramanian

Hajek

2002

IEEE Trans. Inform. Theory

103

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“…A propagation model is a mathematical model that predicts some properties of a radio signal at a given location [1], [10], [13], [22], [27], [31]. If the ªoutputº of the model is a probability distribution of the signal's properties, the model is statistical, as opposed to a deterministic model that gives a point estimate for each of the predicted properties.…”

Section: Statistical Modeling Approachmentioning

confidence: 99%

A statistical modeling approach to location estimation

Roos

Myllymäki

Tirri

2002

IEEE Trans. on Mobile Comput.

347

293

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AbstractÐSome location estimation methods, such as the GPS satellite navigation system, require nonstandard features either in the mobile terminal or the network. Solutions based on generic technologies not intended for location estimation purposes, such as the cell-ID method in GSM/GPRS cellular networks, are usually problematic due to their inadequate location estimation accuracy. In order to enable accurate location estimation when only inaccurate measurements are available, we present an approach to location estimation that is different from the prevailing geometric one. We call our approach the statistical modeling approach. As an example application of the proposed statistical modeling framework, we present a location estimation method based on a statistical signal power model. We also present encouraging empirical results from simulated experiments supported by real-world field tests.

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“…The requirement to model many different types of wireless propagation channels has resulted in a large number of different modeling approaches reported in the literature [36]- [38]. One reason for the abundance of modeling approaches is due to the complex phenomena encountered by a transmitted signal.…”

Section: Channel Modeling Approachmentioning

confidence: 99%

Evolution Trends of Wireless MIMO Channel Modeling towards IMT-Advanced

Chong¹,

Watanabe²,

Kitao

et al. 2009

IEICE Trans. Commun.

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SUMMARYThis paper describes an evolution and standardization trends of the wireless channel modeling activities towards IMT-Advanced. After a background survey on various channel modeling approaches is introduced, two well-known multiple-input-multiple-output (MIMO) channel models for cellular systems, namely, the 3GPP/3GPP2 Spatial Channel Model (SCM) and the IMT-Advanced MIMO Channel Model (IMT-Adv MCM) are compared, and their main similarities are pointed out. The performance of MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. Here, we investigate the spatial-temporal correlation characteristics of the 3GPP/3GPP2 SCM and the IMT-Adv MCM in term of their spatial multiplexing and spatial diversity gains. The main goals of this paper are to summarize the current state of the art, as well as to point out the gaps in the wireless channel modeling works, and thus hopefully to stimulate research in these areas.

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Radiowave propagation in mobile communications: an overview of European research

Cited by 76 publications

References 34 publications

Broad-band fading channels: signal burstiness and capacity

Broad-band fading channels: signal burstiness and capacity

A statistical modeling approach to location estimation

Evolution Trends of Wireless MIMO Channel Modeling towards IMT-Advanced

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