Assessment of Channels Modelling, Demodulation, Coding in 5g Wireless Communication System Using Two-State Markov Chain

Abstract

In fifth-generation (5G) wireless communications, efficient data transmission is hindered by burst errors and packet losses resulting from multipath fading. To enhance reliability and mitigate degradation in 5G networks, it is crucial to analyze error patterns and sequences. This paper investigates and develops a two-state Markov-based error model tailored for 5G networks to capture the statistical characteristics of the error process. The model is derived from simulations of 5G wireless networks employing various modulation schemes—Quadrature Phase Shift Keying (QPSK), 16 Quadrature Amplitude Modulation (16-QAM), and 64 Quadrature Amplitude Modulation (64-QAM)—combined with Low-Density Parity-Check (LDPC) and Turbo coding methods. By comparing the burst or gap error statistics from our 5G simulation with those generated by the two-state Markov error model, we demonstrate that the Markov model accurately reflects the error behaviors observed in coded Orthogonal Frequency Division Multiplexing (OFDM) 5G simulations. The two-state Markov model provides valuable insights into the error processes of 5G communications and allows for the evaluation of error control strategies with reduced computational complexity and shorter simulation durations. This approach facilitates a deeper understanding of error dynamics in 5G systems and supports the development of more effective error management techniques.