Indian Journal of Science and Technology

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As Least Square (LS) and Minimum Mean Square Error (MMSE) do not give the satisfactory result to justify the features of the wireless channel, Compressed Sensing (CS) based on Discrete Sine Transform (DST) for channel impulse response has been studied which gained much more importance in digital signal processing. We have used Compressed Sensing to estimate the channel coefficients of the fading channel; then we have performed the CS recovery algorithm to estimate the channel and to nullify the fading effect, the thus much better result are obtained in the simulation which satisfies the better performance of the system as compared to the traditional method. Simulation results show a considerable improvement in Bit Error Rate (BER) performance on employing the Compressed Sensing approach in comparison to LS and MMSE. The improvement of the order of 2-9 dB of SNR is for a particular value of BER.

Keywords

Channel Estimation, Compressed Sensing, DST, LS, MMSE, OFDM.
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