Performance of wavelet shrinkage maximum likelihood estimator in 3GPP’s spatial channel model based on OFDM system

This paper deals with the estimation of the channel impulse response (CTR) of spatial channel model (SCM) in the third generation partnership project (3GPP) based on orthogonal frequency division multiplexing (OFDM) system. Maximum likelihood estimation (MLE) contains intrinsic noise, and Bayesian minimum mean square error estimation (MMSEE) is expected to have better performance as it exploits prior information about the CIR, which results difficulty of implementation in practice. We propose a new estimator which processes MLE with wavelet shrinkage algorithm. Filtered by quantization and reconstruction functions, the estimate becomes more accurate than MLE. Simulation results validate that wavelet shrinkage maximum likelihood estimation (WMLE) outperforms MLE in terms of accuracy and bit error rate (BER) without prior channel information.