The transmission of acoustic waves is limited because of various factors such as water temperature, salinity and depth in the underwater acoustic communication with a multi-path channel environment. Also the underwater acoustic communication uses low frequency band relative to wireless communication. For the these reasons the performance is limited.
It is well known that underwater channels are often hostile for underwater sensor communications, which impose three major obstacles for coherent transceivers. One is the excessive multipath delay spread in a underwater channel, which usually causes the inter-symbol interference (ISI). Another obstacle is the doppler shift due to the relative motion between the source and the receiver, which causes compression or dilation on the received signals. The last one is the fast time-varying phase drift due to random nature of the underwater acoustic channels.
Various methods to cope with the multipath effect have been developed. A well-known method to counteract ISI is the decision feedback equalizer (DFE), which has been used in many underwater sensor communication applications. However the use of DFE has difficulties when the multipath with a number of arrivals has equal strength or low SNR. The other way to cope with ISI is to use an iterative equalizer which consists of an outer loop in addition to the inner loop BCJR decoder in the receiver. The assembly utilizes the error correcting capability of the convolutional codes to get an efficient equalizer.
Alternatively, to cope with multipath effect, this thesis adjust the packet length according to the channel coherence time. Due to the very short coherence time only small packet size was transmitted. This caused the throughput decreased. To achieve a high throughput, in this thesis divide a long packet into group of small consecutive packets, and use the estimated channel information of previous packets to compensates for the current and next packets.
In this thesis employ an iterative receiver structure with fine-tuned parameters to process experimental data from a fixed source to a fixed receiver at the data transmission rate of 1 k-symbol/s. The results indicate that the proposed algorithm works effectively well and how much coding gains can be obtained as the iteration number increases. Finally, this thesis concluded that proposed effective decoding method is improving the throughput in the time-varying underwater communications.