Research Topic:
Compressed Sensing based Channel Estimation Algorithm for MIMO-OFDM System

Person in charge: Ratih Hikmah Puspita  

Research Brief


A multiple-input multiple-output (MIMO) communication system combined with the orthogonal frequency division multiplexing (OFDM) modulation technique can help in mitigating the effects of multipath fading and achieve reliable high data rate transmission over broadband wireless channels. The channel estimation has an important role in determining the quality of the data transmission from transmitter to receiver. Channel estimation using Compressed Sensing (CS) algorithms can achieve higher correctness of channel status but using small number of pilots than conventional interpolation based methods. This research proposed to reduce the complexity in sensing matrix algorithm for MIMO-OFDM. By using STBC MIMO, the pilot matrixes of 2 antennas are same. So we can share the measurement matrix (A) for CS algorithm process to reduce the computational complexity. To improve the bit error rate (BER) performance, we can use average process by summarize the known received vector (y) to find the correct position of CIR.