A new deterministic process based generative model for characterizing bursty error sequences

Efficient and accurate generative models are of great importance for the design and performance evaluation of wireless communication protocols as well as error control schemes. In this paper, deterministic processes are utilized to derive a new generative model for the simulation of bursty error sequences encountered in digital mobile fading channels. The proposed deterministic process based generative model (DPBGM) is simply a properly parameterized and sampled deterministic process followed by a threshold detector and two parallel mappers. The target error sequence is generated by a computer simulation of a frequency hopping (FH) convolutionally coded Gaussian minimum shift keying (GMSK) transmission system with Rayleigh fading. Simulation results show that this generative model enables us to match very closely any given gap distribution (GD), error-free run distribution (EFRD), error cluster distribution (ECD), error burst distribution (EBD), error-free burst distribution (EFBD), block error probability distribution (BEPD), and bit error correlation function (BECF) of the underlying descriptive model.