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.
In order to increase energy efficiency over transmissions channels, common approach for optimization tasks is by means of channel’s second-order statistics. Actual channel modeling tools for 5G networks end with channel’s first-order statistics, although these metrics are not sufficient when channel conditions are rapidly changing, either in time, frequency or space. In this paper, we establish a tool for evaluation and comparision of energy efficiency of mobile radio channel using its second-order statistics, especially level crossing rate (LCR) and average fade durations (AFD), as they can implicitly pinpoint to transmission configurations that are energy efficient or, as oposit, become a waste of energy. Using both deterministic and stochastic channel modeling, we present results after simulations of Rayleigh channel for narrowband case and further extend it to passband cases, suitable for 5G scenario. We conclude about the energy efficiency of different transmission schemes used by the 5G physical layer observing LCR and AFD values.
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