Ultra Wideband Systems with MIMO

Kaiser, Thomas; Zheng, Feng

doi:10.1002/9780470740019

Cited by 91 publications

(70 citation statements)

References 205 publications

(416 reference statements)

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“…Анализ последних исследований и публикаций [1][2][3] показал, что поскольку набор случайных и детерминированных факторов, оказывающих существенное влияние на передачу сигналов в декаметровом канале связи, разнообразен, то целесообразно при его моделировании использовать феноменологический подход, так как соответствующие структурно-физические модели из-за своей сложности малопригодны для синтеза алгоритмов приема сигналов. При этом для феноменологических моделей канал рассматривается как «черный ящик», внутренняя структура которого при описании не учитывается, а основное внимание уделяется воспроизведению взаимозависимостей между входными и выходными воздействиями.…”

Section: постановка задачиunclassified

Model Impulse Response High Frequency Communication Channel with the Identifi cation of Parameters of Multipath

Revin¹,

Mezhuev²,

Korennoi³

2016

J. Sib. Fed. Univ. Eng. technol.

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The improved Markov phenomenological model impulse response of the high frequency communication channel are presented in this work. The model allows for the identification of authorized multipath components by analyzing the combinations of possible values of the correlation parameters. Thus obtained impulse response with fixed parameters of the statistical model generates adequate communication channel during each period of quasi-stationary. Keywords: model, multipath, identification, Markov process, the impulse response.Citation: Revin V.S., Mezhuev A.M., Korennoi A.V. Model impulse response high frequency communication channel with the identification of parameters of multipath,

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Section: постановка задачиunclassified

Model Impulse Response High Frequency Communication Channel with the Identifi cation of Parameters of Multipath

Revin¹,

Mezhuev²,

Korennoi³

2016

J. Sib. Fed. Univ. Eng. technol.

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“…With the imposition of the constraint B sig < <f c , the pair of Equations 3 and 4 are equivalent and W H (τ, s) ≡ S H (τ, υ) irrespective of whether the system is wideband or narrowband in this context. In the second aspect which is the focus of this article, no constraint is imposed and narrowband assumption is then made when (B sig /f c ) <B f , where B f (typically 0.2), is called the fractional bandwidth [22,23], otherwise, the system is wideband. For the rest of this article, narrowband and wideband are referred to in the context of this second aspect.…”

Section: System Modelmentioning

confidence: 99%

“…In the case of wideband, this equivalence is invalid and W H (τ, s) is the appropriate valid channel response. Wireless communication systems like UWB [22,23] and UWA channels [24,25] are wideband in this context.…”

Section: System Modelmentioning

confidence: 99%

Time-scale domain characterization of non-WSSUS wideband channels

Chude-Okonkwo

Ngah

Rahman

2011

EURASIP J. Adv. Signal Process.

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To account for nonstationarity, channel characterization and system design methods that employ the non-widesense stationary uncorrelated scattering (non-WSSUS) assumption are desirable. Furthermore, the inadequacy of the Doppler shift operator to properly account for the frequency shift in wideband channel implies that the timefrequency characterization methods that employ the Doppler shift operator are not appropriate for most wideband channels. In this article, the statistical time-scale domain characterization of the non-WSSUS wideband channel is presented. This approach employs the time scaling operator in order to account for frequency spreading, and also emphasizes on the nonstationarity of the wideband channel. The non-WSSUS statistical assumption termed localsense stationary uncorrelated scattering (LSSUS) is presented and employed in characterizing the nonstationary property of the time-varying wideband channel. The LSSUS channel model is then parameterized to provide useful coherence and stationarity/nonstationarity parameters for optimal system design. Some application relevance of the developed model in terms of channel capacity and diversity techniques are discussed. Measurement and simulation results show that the assumption of ergodic capacity and the performance of various diversity techniques depend on the degree of channel stationarity/nonstationarity. It is shown that the quantification of this degree of stationarity through the channel parameters can provide a way of tracking channel variation and allowing for adaptive application of diversity techniques and the channel capacity.

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“…MIMO techniques permit to exploit the rich scattering of short range indoor wireless channel to increase the spectral efficiency linearly. The UWB-MIMO studies can be classified into four categories Kaiser (2009):  MIMO channel modelling and measurement. Spatial characterization of UWB MIMO channel is given in Malik (2008).…”

Section: Mb Ofdm Uwb With Mimo Over the Wireless Channelmentioning

confidence: 99%