Position determination of acoustic source using higher-order spectral analysis for time of arrival estimation

Pokrajac, P Ivan; Vračar, Miodrag S.; Šević, Tamara; Joksimović, Vasilija

doi:10.5937/str1903041p

Cited by 1 publication

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In non-stationary channels, as PDF and CDF are time-varying, analysis must be complemented with higher order statistics, following the path to performance measurement or evaluation. For most applications, second-order statistics, such as LCR and AFD (average fade), represent enough statistical metrics to express this non-stationarity [ 5 , 6 ] and non-linearity feature [ 7 ]. We put our motivation point to the fact that representative general channel 5G modeling tools lack in second-order statistics analysis, although it may represent crucial metadata between physical channel parameters (velocity, direction angles, etc.)…”

Section: Introductionmentioning

confidence: 99%

A Symbolic Encapsulation Point as Tool for 5G Wideband Channel Cross-Layer Modeling

Stefanovic

Blagojević

Pokrajac

et al. 2020

Entropy

Self Cite

View full text Add to dashboard Cite

Considering that networks based on New Radio (NR) technology are oriented to provide services of desired quality (QoS), it becomes questionable how to model and predict targeted QoS values, especially if the physical channel is dynamically changing. In order to overcome mobility issues, we aim to support the evaluation of second-order statistics of signal, namely level-crossing rate (LCR) and average fade duration (AFD) that is missing in general channel 5G models. Presenting results from our symbolic encapsulation point 5G (SEP5G) additional tool, we fill this gap and motivate further extensions on current general channel 5G. As a matter of contribution, we clearly propose: (i) anadditional tool for encapsulating different mobile 5G modeling approaches; (ii) extended, wideband, LCR, and AFD evaluation for optimal radio resource allocation modeling; and (iii) lower computational complexity and simulation time regarding analytical expression simulations in related scenario-specific 5G channel models. Using our deterministic channel model for selected scenarios and comparing it with stochastic models, we show steps towards higherlevel finite state Markov chain (FSMC) modeling, where mentioned QoS parameters become more feasible, placing symbolic encapsulation at the center of cross-layer design. Furthermore, we generate values within a specified 5G passband, indicating how it can be used for provisioningoptimal radio resource allocation.

show abstract

Section: Introductionmentioning

confidence: 99%