A Comprehensive Standardized Model for Ultrawideband Propagation Channels

Molisch, Andreas F.; Cassioli, Dajana; Chong, Chia‐Chin; Emami, S.; Fort, A.; Kannan, B.; Karedal, J.; Kunisch, J.; Schantz, H.G.; Siwiak, Kazimierz; Win, Moe Z.

doi:10.1109/tap.2006.883983

Cited by 640 publications

(512 citation statements)

References 41 publications

(49 reference statements)

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“…The distribution parameters for the dipole and double loop is gathered in Table 5. The suggested distributions differ from the ones usually seen in the literature, where S is often modeled as a lognormally [11,36] or a normally [14] distributed variable. …”

Section: Path-loss Modelsmentioning

confidence: 80%

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Categorized Uwb on-Body Radio Channel Modeling for Wbans

Kumpuniemi¹,

Hämäläinen²,

Yazdandoost³

et al. 2016

PIER B

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Abstract-A categorized radio channel modeling for wireless ultra-wideband on-body body area networks is discussed. Measurements in an anechoic chamber at fourteen antenna locations are conducted in a 2-8 GHz band. The dipole and double loop antenna types are used. Six link classes are formed based on the antenna spots on the torso, head or limb. The limb-limb and the head-limb links have the lowest and highest path losses, respectively. The head-limb links have the shortest channel impulse responses (CIRs) and limb-limb links the longest ones. The CIR amplitudes follow the inverse Gaussian distribution. The tap indexes and the total excess delays are modeled with the negative binomial distribution. In most cases, the CIRs decay faster for the dipole. Otherwise no major differences exist between the antennas.

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Section: Path-loss Modelsmentioning

confidence: 80%

“…Perhaps the majority of the published papers are related to the various aspects of on-body situations [9][10][11][12]. For instance, in [7,[13][14][15] research related to UWB onbody radio channels are reported. In [7,12,[16][17][18][19], the effect of different antennas or polarizations on the UWB links are investigated.…”

Section: Introductionmentioning

confidence: 99%

Categorized Uwb on-Body Radio Channel Modeling for Wbans

Kumpuniemi¹,

Hämäläinen²,

Yazdandoost³

et al. 2016

PIER B

View full text Add to dashboard Cite

show abstract

“…In the following, the values σ 0 = 0.01 m and β = 0.08 m are considered. These values are obtained in [15] by considering Channel Model 3 described in [16] and the energy detection receiver presented in [17], which is composed by a band-pass filter followed by a squarelaw device and an integrator, with integration interval set to T s = 1 s. The results presented in the following hold under these channel and receiver assumptions.…”

Section: Scenariomentioning

confidence: 99%

A Swarm Intelligence Approach to $$3$$D Distance-Based Indoor UWB Localization

Monica

Ferrari

2015

Applications of Evolutionary Computation

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Abstract. In this paper, we focus on the application of Ultra Wide Band (UWB) technology to the problem of locating static nodes in threedimensional indoor environments, assuming to know the positions of a few nodes, denoted as "beacons." The localization algorithms which are considered throughout the paper are based on the Time Of Arrival (TOA) of signals traveling between pairs of nodes. In particular, we propose to apply the Particle Swarm Optimization (PSO) algorithm to solve the localization problem and we compare its performance with that of the Two-Stage Maximum-Likelihood (TSML) algorithm. Simulation results show that the former allows achieving accurate position estimates even in scenarios where, because of ill-conditioning problems associated with the network topology, TSML fails.

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“…Furthermore, it was validated by Kolmogorov-Smirnov distribution-fitting to measurements at a significance level of 1% that the fading amplitudes can be modelled as Nakagami-m distributed [2].…”

mentioning

confidence: 99%

“…The corresponding wide sense stationary uncorrelated scattering (WSSUS) based channel impulse response (CIR) exhibiting clusters of similar delay paths may be modelled as [2]:…”

mentioning

confidence: 99%

Generic z -domain discrete-time transfer function estimation for ultra-wideband systems

et al. 2008

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Generic z-domain discrete-time transfer function estimation is proposed for ultra-wideband channels, which requires no channel sounding sequence transmission and hence constitutes a blind technique. This is achieved by estimating the channel impulse response with the aid of the information signalling pulses and then equalising the effects of the channel by the corresponding inverse system.Introduction: Ultra-wideband (UWB) communication systems are characterised by distinct clusters of dense multipath faded received components. In [1], channel estimation techniques were proposed for assisting the receiver in recovering the transmitted UWB signal and hypothesising that an inverse system may be found for signal recovery. Hence the novel contribution of this Letter is that this complete inverse system is indeed found and the corresponding recursive equation is provided for channel estimation. The system does not require any extra channel sounding sequence for the recovery of the received channelcontaminated UWB pulses and so avoids any channel-soundingrelated throughput reduction and therefore may be viewed as a blind technique.

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A Comprehensive Standardized Model for Ultrawideband Propagation Channels

Cited by 640 publications

References 41 publications

Categorized Uwb on-Body Radio Channel Modeling for Wbans

Categorized Uwb on-Body Radio Channel Modeling for Wbans

A Swarm Intelligence Approach to $$3$$D Distance-Based Indoor UWB Localization

Generic z -domain discrete-time transfer function estimation for ultra-wideband systems

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