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

Abstract

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.

Interference immunity and energy efficiency of digital communications systems in multipath channel with fading

“…Depending on the nature of the radio propagation environment, there are different models that describe the statistical behavior of the multipath channel. See Rhattoy [14] and Stefanovic et al [15] for the mechanisms of formation of small-scale fading and their description using the Nakagami, Rice, and Rayleigh distributions, and for the average duration of fading. The Rayleigh distribution can be described as shown in: i) no line-of-sight between antennas, only reflected signals are received; ii) is caused by Gaussian noise with Doppler shift; and iii) signal power is distributed exponentially.…”

Information Theory and Symbolic Analysis: Theory and Applications

“…Finally, Stephanovic et al [7] are concerned with technology services and their quality. How can a model forecast a targeted value for Quality of Service (QoS) in a changing physical channel?…”