Statistical modeling and simulation of the RMS delay spread of indoor radio propagation channels

Hashemi, H.; Tholl, D.

doi:10.1109/25.282271

Cited by 107 publications

(42 citation statements)

References 23 publications

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“…Assuming a fuzzy set of factor set is (6) where represents the degree of influence of factor on judgment, and is the nonempty fuzzy sets of . The comprehensive evaluation result can be obtained by a fuzzy transformation as in (7) where " " indicates the operation defined as in (8) here, is the operation of selecting the smaller number, while chooses the larger number.…”

Section: B Fuzzy Comprehensive Evaluation Modelmentioning

confidence: 99%

“…In our method, SNR, RT, RMS delay spread, kurtosis and skewness are used to identify NLOS based on following reasons: (i) RMS delay spread increases when more multipath components are included in received signal [5], [6]; (ii) signal channel's structure does not change appreciably over short distances, but drastic variation arises when there is an increase in the number of intervening obstructions [6], [7]; (iii) the energy, when signal penetrates through obstructions, will be seriously decayed, but noise increases inversely. These chosen metrics are calculated as in (9)-(13) [2], [5].…”

Section: Nlos Identification and Compensationmentioning

confidence: 99%

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NLOS identification and compensation for UWB ranging based on obstruction classification

Wen

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Non-line-of-sight (NLOS) propagation is one of the major barriers to accurate ranging and positioning based on time of arrival (TOA) in the application of an ultra wideband (UWB) system. This paper proposes a new method for NLOS identification and mitigation based on signal characteristic analysis and fuzzy theory. This method neither requires to build a statistical model nor to create and update a training database, so that it can be used conveniently for different application scenarios. Extensive experiments were conducted and the results show that the cumulative distribution function of the ranging error below 0.5 meter is over 90% when using the proposed mitigation method, while that without using the mitigation method is below 70%. Also, by using the proposed method, the root mean square error (RMSE) of the range measurements is reduced from 0.77 to 0.33 meter. The results demonstrate that this method can effectively identify NLOS and mitigate the NLOS-induced ranging error.

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Section: B Fuzzy Comprehensive Evaluation Modelmentioning

confidence: 99%

Section: Nlos Identification and Compensationmentioning

confidence: 99%

NLOS identification and compensation for UWB ranging based on obstruction classification

Wen

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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“…paths' arrival time, amplitude and phase distributions, and respective characteristic parameters, have decisive impact upon capacity of multipath fading channels [23,[29][30][31]. The RMS-delay-spread parameter, defined [23] as the second central moment of channel's power delay profile…”

Section: Definition-significancementioning

confidence: 99%

Travelling‐wave multipath simulation of two‐conductor HF signalling over indoor power‐line networks and RMS‐delay‐spread dependence

Papaleonidopoulos

Karagiannopoulos

Theodorou

2007

Trans Emerging Tel Tech

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SUMMARYAn efficient, travelling-wave based multipath-simulation technique is presented, suitable for the estimation of Power-Line Communication channels' response in terms of both transfer function and power delay profile. The cable transmission parameters are thereupon requisite, as well as the vicinal network topology. The algorithm applies directly to narrowband single-phase HF signalling over cabling compliant with the two-conductor transmission-line model. Experimental verification throughout the 1.6-30 MHz band on the basis of the quantitative path-incorporation criterion proposed, reveals resultant amplitude-response accuracy of no less than 5 dB. Dependency of the RMS delay spread on the multitude of network's impedance-mismatch points, the overall network length, as well as the carrier frequency, is in addition investigated. Quite clear functional interrelations ensue thereupon, whereat proper analytical descriptions are proposed. Applicability of the multipath approach introduced is indicated for narrowband and wideband channel capacity estimations, and relevant hints towards the treatment of multiconductor line structures are suggested.

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“…Details of the measurements and subsequent analysis of the data have been reported in [2] and [3]. A brief description of the database, which includes only relevant issues, is provided in this section.…”

Section: B the Empirical Databasementioning

confidence: 99%

“…In [2], impulse response modeling of the indoor radio propagation channel has been investigated based upon a large database of 12 000 impulse response estimates of the channel. Distribution of multipath components in each impulse response, distribution of arrival time of multipath components, correlation between path variables, and statistical properties of the rms delay spread are reported in [2] and [3]. Distribution of multipath components' amplitudes over both local and global areas is addressed in [2], and details are presented in [4].…”

mentioning

confidence: 99%

Phase modeling of indoor radio propagation channels

Nikookar

Hashemi

2000

IEEE Trans. Veh. Technol.

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Abstract-Two models for generating phase of individual multipath components in an indoor environment, partly developed in [1], have been studied in detail. In the deterministic phase increment model (model I), phase of each multipath component is updated deterministically using several independent random scatterers. In the random phase increment model (model II), phase of each multipath component is updated by adding independent random phase increments. Performance of these models has been evaluated by means of extensive computer simulations. Statistical properties of narrow-band CW fading signals obtained using each phase model have been compared with the corresponding results for a large empirical wide-band database of 12 000 impulse response estimates of indoor radio propagation channels. A major conclusion is that model I (with five scatterers for each multipath component) and model II (with proper choice for phase increments) provide fading results consistent with those obtained from measurements.In this paper, properties of each phase model are described, and an algorithm for generating each is presented. First-and second-order statistics [amplitude distributions, level crossing rates (LCR's), and average duration of fades (ADF's)] andDoppler spectra of narrow-band CW fading waveforms obtained using simulated phases are reported, and detailed comparison between the simulated and empirical results is carried out. Furthermore, the two models are also compared with each other, and advantages and disadvantages of each are explored. The effect of increasing the number of scatterers and statistical properties of phase increments in model I are studied, simulated, and compared with model II. A major conclusion is that for an appropriate choice of parameters, both models provide satisfactory performance. Computation time of model I is, however, on the average 1.7 times of model II, making it less efficient for generating a large number of impulse response profiles.The results reported in this paper can be used in performance evaluation of wireless indoor communication systems, either directly or by developing a comprehensive channel simulator.

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Statistical modeling and simulation of the RMS delay spread of indoor radio propagation channels

Cited by 107 publications

References 23 publications

NLOS identification and compensation for UWB ranging based on obstruction classification

NLOS identification and compensation for UWB ranging based on obstruction classification

Travelling‐wave multipath simulation of two‐conductor HF signalling over indoor power‐line networks and RMS‐delay‐spread dependence

Phase modeling of indoor radio propagation channels

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