Simple, accurate and computationally efficient wireless channel m odeling algorithm

We propose simple and computationally efficient wireless channel modeling algorithm. For this purpose we adopt the special case of the algorithm initially proposed in [1] and show that its complexity significantly decreases when the time-series is covariance stationary binary in nature. We show that for such time-series the solution of the inverse eigenvalue problem returns unique transition probability matrix of the modulating Markov chain that is capable to match statistical properties of empirical frame error processes. Our model explicitly takes into account autocorrelational and distributional properties of empirical data. We validate our model against empirical frame error traces of IEEE 802.11b wireless access technology operating in DCF mode over spread spectrum at 2Mbps and 5.5 Mbps bit rates. We also made available the C code of the model as well as pre-compiled binaries for Linux and Windows operating systems at http://www.cs.tut.fi/(similar to)moltchan.