Impact of Interpolation Techniques on Statistical Properties and Speed of Fading Channel Simulators

Interpolation filters are considered to be computationally intensive sections of fading channel simulators. They can be implemented by using linear interpolation or zero-padding followed by low-pass IIR or polyphase filtering. In this work, we will investigate how different interpolation techniques affect statistical properties and speed of the simulator. We will show that use of linear interpolation results in 3 to 6 times improvement in simulation speed while there is negligible degradation in desired statistical accuracy. We will validate this claim by designing a fading channel simulator that uses the above mentioned three interpolation techniques and observing their impact on its first order (probability density functions) and second order (correlation functions) statistical properties. We will also compare the impact of interpolation techniques on the level crossing rate (LCR) and bit error rate (BER) of the fading signal. Finally, we will emphasize our claim by using an advance multiple-tap channel model (gsmTUX6C1) with our simulator (using linear interpolation) and showing that its performance is comparable to corresponding Matlab model that uses polyphase interpolation. We will conclude this work with a recommendation to use linear interpolation for efficient and statistically correct fading channel simulators.