Iterative channel estimation and equalization for underwater acoustic MIMO SFBC OFDM communication

Serious mutual channel interference and large time delays in underwater acoustic MIMO-OFDM communication systems usually lead to inferior performance and high data error. Also the time varying characteristic of underwater acoustic channels brings great challenges to precise channel estimation. To solve these problems, this paper proposes an iterative channel estimation and equalization algorithm for space frequency block coding based on the MIMO-OFDM transmission system. In this algorithm, taking advantage of the space frequency orthogonal characteristics, the channel estimation is first implemented for each tranceiver pair. Then Turbo equalization is introduced for iterative symbol detection, in which joint soft information of the multichannel carrier pairs is provided iteratively as prior information feedback to update the block channel estimation and obtain a new symbol estimation. Simulation and analysis show that the proposed method gains about 4dB for the STBC system and 2dB for the SFBC system at 1e-4 bit error ratio (BER) after two iterations. This method also achieves great output signal to noise ratio (SNR) improvement, which could be seen from the convergence of the constellations, and shows visible benefit in the bit error ratio through decoding.