Modeling and Analysis of Error Process in 5G Wireless Communication Using Two-State Markov Chain

In fifth-generation wireless communications, data transmission is challenging due to the occurrence of burst errors and packet losses that are caused by multipath fading in multipath transmissions. To acquire more efficient and reliable data transmissions and to mitigate the transmission medium degradation in the 5G networks, it is important to study the error patterns or burst the error sequences that can provide insights into the behavior of 5G wireless data transmissions. In this paper, a two-state Markov-based 5G error model is investigated and developed to model the statistical characteristics of the underlying error process in the 5G network. The underlying 5G error process was obtained from our 5G wireless simulation, which was implemented based on three different kinds of modulation methods, including QPSK, 16QAM, and 64QAM, and was employed using the LDPC and TURBO coding methods. By comparing the burst or gap error statistics of the reference error sequences from the 5G wireless simulations and those of the generated error sequences from the two-state Markov error model, we show that the error behaviors of the coded OFDM 5G simulations can be adequately modeled by using the two-state Markov error model. Our proposed two-state Markov-based wireless error model can help to provide a more thorough understanding of the error process in 5G wireless communications and to evaluate the error control strategies with less computational complexity and shorter simulation times.