Recovery of compressed audio signal over a sparse channel in MIMO-OFDM systems

Performance Analysis of Compressive Sensing based LS and MMSE Channel Estimation Algorithm

“…In [23], the effect of varying Fast Fourier Transform (FFT) size in OFDM on the performance of LS-CS channel estimation algorithm is observed. In [24], performance of LS-CS is analyzed based on the recovery of transmitted audio signal over a sparse noisy channel. It is observed that with LS-CS channel estimation technique, an appropriate reconstruction of transmitted data is possible at the receiver by just sensing a few channel coefficients in a very noisy channel, by selecting the optimum FFT size.…”

“…In this paper, we have developed and implemented MMSE-CS channel estimation algorithm. We have compared the performance of MMSE-CS algorithm with LS-CS algorithm implemented in [22] and its performance to recover audio data was analyzed in [24]. To accentuate the importance of compressive sensing in channel estimation, we have also compared the performance of MMSE-CS in terms of BER with classical LS and MMSE channel estimation algorithms.…”