MIM: A new class of hybrid channel error model

Modeling and simulation on channel conditions play an important role in performance evaluation of wireless protocols. Two most widely used channel error model are independent model and Markov model. The former is simple and easy to implement, but cannot capture the bursty nature of channel errors. And we find that, when the bit error rate is relatively small, the existing Markov model cannot efficiently predict channel conditions. For these reasons, we propose MIM, a hybrid channel error model. MIM partitions the received binary indicator sequence into m blocks. And it´s assumed that the occurrence of bit errors within each block conforms to the two-state Markov model, while between blocks, block errors are independent and identically distributed (IID) as one fixed block error probability p_b. We set up an office wireless environment and choose the optimal model parameters based on collected error trace. The analysis of model parameters shows that, our model well conforms to reality.