Remote underwater acoustic communication method based on soft-demodulation soft-decoding joint iteration

Abstract

The invention provides a remote underwater acoustic communication method based on soft-demodulation soft-decoding joint iteration. The method comprises the following steps that: a transmitting end performs low density parity check (LDPC) coding on a binary information sequence which is sent by a signal source, performs quaternary phase shift keying (QPSK) modulation and Gray mapping, maps code elements to one of four positions in a constellation diagram by taking two code elements as a group, performs Walsh-m composite sequence spectrum spreading to obtain a signal to be transmitted, and converts a digital signal to be transmitted into an underwater acoustic signal; and an underwater acoustic transducer at a receiving end converts the received underwater acoustic signal, de-spreads by using a composite sequence which is the same as that of the transmitting end to obtain a receiving signal, performs self-adaptation decision feedback equalization to obtain an amplitude fading complex signal, performs soft-demodulation soft-decoding joint iteration on the signal, stops joint iteration after set iteration frequency is reached, performs belief propagation (BP) decoding on an LDPC decoder and outputs a bit value to a sink. By the method provided by the invention, the reliability of remote underwater acoustic communication is improved. The method is applicable to the remote underwater acoustic communication.

Description

technical field [0001] The invention relates to an underwater acoustic communication method. In particular, a long-range underwater acoustic communication method. Background technique [0002] In long-distance underwater acoustic communication systems, the signal-to-noise ratio of received signals directly affects the reliability of communication results. Multi-path extension delay and amplitude attenuation both increase with the increase of communication distance. In order to improve communication reliability, the signal-to-noise ratio of the received signal must be improved. Anti-multi-path interference processing on the signal is an effective method. [0003] At present, anti-multipath processing is widely used in long-distance underwater acoustic communication systems at home and abroad. The method is OFDM (Orthogonal Frequency Division Multiplexing) technology. A large communication distance requires an increase in the transmission power, so the requirements for the l...

AI Technical Summary

Problems solved by technology

[0003] At present, anti-multipath processing is widely used in long-distance underwater acoustic communication systems at home and abroad. The method is OFDM (Orthogonal Frequency Division Multiplexing) technology. A large communication distance requires an increase in the transmission power, so the requirements for the linear amplification range of the underwater acoustic transducer are very strict

[0004] In 1998, in the article "Spread Spectrum Underwater Acoustic Telemetry", M.Stojanovic proposed the multipath diversity reception technology based on the Rake receiver. The method is: after the Rake receiver compensates the multipath effect of the channel, it highlights the main path components in the signal. Improve the signal-to-noise ratio of the direct sound, so that the impulse response function of the channel approaches the σ function form, thereby suppressing the interference of the multi-path effect in the received signal. The disadvantage is that it is difficult to realize in real time and apply to engineering practice

[0005] In the article "Channel Coding for Underwater Acoustic Communication System" in 2006, an underwater acoustic channel coding technology using convolutional codes and RS (Reed-Solomon) codes was proposed. The method is to use convolutional codes and RS codes to correct residual errors. The disadvantage is that the noise generated by the undulations in the underwater acoustic channel is a common burst noise, and the convolutional code and the RS code have a good ability to correct random errors, but they are not corrected in the underwater acoustic channel. The ability to burst errors is not good, so there is still a high bit error rate after decoding

Images