We presented an iterative turbo equalization to cope with intersymbol interference induced by reflection of sea level and sea bottom for underwater sensor communication channel. Iterative turbo equalizer consists of inner codes and outer codes; we employ decision feedback equalizer as an outer code and turbo codes as an inner code. Equalizer and decoder are connected through the interleaving and deinterleaving that update each other's information repeatedly. At the receiver side, we resort to powerful turbo equalization algorithms that iteratively exchange probabilistic information between inner decoder and outer decoder, thereby reducing the error rates significantly. Furthermore, we expand iterative turbo equalizer techniques for single-input-singleoutput (SISO) system to multiple-input-multiple-output (MIMO) system in order to increase data rates for underwater sensor communication channel. Based on experimental channel response, we confirmed that the performance is improved as iteration number is increased. The performance is improved by 3.5 [dB] compared to noniteration for SISO channel and by 1 [dB] for MIMO channel, respectively. We also decided that optimal iterations are 3. Very important for a successful decoding is the channel estimation, which is also discussed.
Since the sea-going experiment is expensive, the channel simulator for an underwater acoustic communication (UAC) can be useful in evaluating the performance of an UAC system. In this paper, VirTEX (Virtual Time series EXperiment) is applied to the UAC algorithm. In order to examine the practicality of VirTEX, the statistics of the bit error rate is obtained from sea-going experiments, and compared with the simulated result using VirTEX. The result and discussion are presented.
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