In this work we present a fully stochastic model of performance analysis of single- and multi-carrier modulations (SCM and MCM) in communication systems affected by impulsive noise. The key performance of the model is the symbol error rate (SER), which is fully determined as a function of the system parameters, including the frame length, symbol power, white noise power, impulsive noise power, and the probability of the impulse events. We derive closed-form analytical expressions for the systems SER and compare them with simulation results, showing very good agreement for all the impulsive noise scenarios. Specifically, we show under which conditions a MCM system performs better than a SCM one, and vice versa, which can be used to apply an optimal switching policy that minimizes SER. The model developed for SCM and MCM systems is conceptually applied to the Covid-19 phenomenology and, consequently, the results obtained for SCM and MCM scenarios are interpreted to inform decision and management policies of social distancing (lock/roam). Specifically, we also show when the "roam" strategy performs better than the "lock" strategy, and vice versa, thus enabling the design of an optimal control policy that minimizes the mortality rate (MR). However, the proposed model for Covid-19, which assumes a similarity with SCM/MCM systems, may not be easy to be tested in practice in the absence of adequate statistical data. Therefore, any management decision should not be based (only) on the proposed model adapted to Covid-19, and necessarily requests the integration of experts opinions.

Single- and Multi-Carrier Systems Affected by Impulsive Noise: Covid-19 View

Banelli, P;
2022

Abstract

In this work we present a fully stochastic model of performance analysis of single- and multi-carrier modulations (SCM and MCM) in communication systems affected by impulsive noise. The key performance of the model is the symbol error rate (SER), which is fully determined as a function of the system parameters, including the frame length, symbol power, white noise power, impulsive noise power, and the probability of the impulse events. We derive closed-form analytical expressions for the systems SER and compare them with simulation results, showing very good agreement for all the impulsive noise scenarios. Specifically, we show under which conditions a MCM system performs better than a SCM one, and vice versa, which can be used to apply an optimal switching policy that minimizes SER. The model developed for SCM and MCM systems is conceptually applied to the Covid-19 phenomenology and, consequently, the results obtained for SCM and MCM scenarios are interpreted to inform decision and management policies of social distancing (lock/roam). Specifically, we also show when the "roam" strategy performs better than the "lock" strategy, and vice versa, thus enabling the design of an optimal control policy that minimizes the mortality rate (MR). However, the proposed model for Covid-19, which assumes a similarity with SCM/MCM systems, may not be easy to be tested in practice in the absence of adequate statistical data. Therefore, any management decision should not be based (only) on the proposed model adapted to Covid-19, and necessarily requests the integration of experts opinions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1532433
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