Improvement of communication quality using compressed sensing in underwater acoustic communication system with orthogonal signal division multiplexing

Abstract

We propose the use of compressed sensing for an underwater acoustic (UWA) communication system with orthogonal signal division multiplexing (OSDM) to achieve reliable communication in UWA channels with large delay and Doppler spreads. However, OSDM does not fully exploit the characteristics of UWA channels, which have long but sparse reverberation tails. Hence, we propose an OSDM channel estimator using compressed sensing and evaluate its performance in simulations and experiments. The simulations revealed that the optimal gain determining the performance of the channel estimator depends on standard deviation of noise σ, and OSDM using compressed sensing outperforms normal OSDM. We also evaluate OSDM performance using compressed sensing in field testing in the coastal area of Suruga Bay, Japan. The experimental results suggest that compressed sensing can boost OSDM performance; the number of OSDM error blocks using compressed sensing is half that in normal OSDM. Thus, OSDM using compressed sensing provides reliable communication.

Underwater acoustic communication using orthogonal signal division multiplexing with windowing

“…The Tx transmits a message as follows. Note that signal processing procedures 1-3 in the Tx and 2-3 in the Rx are the same as in the previous D-OSDM 43,[45][46][47][48][49][50] and that processing procedure 1 in the Rx is newly introduced in this study.…”

“…The simulation system is the same as that used in our previous studies. 48,49) Figure8 shows the simulation environment, which is a shallow-water field whose depth is 40 m. The Tx and RX are set at depths of 2 m and 12 m, respectively. The Rx is fixed and the Tx moves at a velocity of 2 m s −1 between the Tx and Rx, the distance between which becomes 50-600 m. The Rx uses two hydrophones (R = 2).…”

“…The experimental data are the same as those used in our previous studies. 48,49) Figure 10 shows the experimental environment and apparatus. The experimental environment is almost the same as the simulation environment in Sect.…”

“…D-OSDM-CS can estimate a channel impulse response containing less additive noise in the time domain by utilizing the sparsity of UWA channels (in underwater, a channel impulse response has many zero taps and a few active taps). 48) Moreover, in 2021 we proposed an advanced D-OSDM-CS that can improve communication quality by optimizing the regularization parameter of CS even when the Doppler spread is larger than the guardband (an unused part of the signal spectrum between a pilot and message signals to prevent them from interfering with each other). 49) However, the communication quality of D-OSDM has room for improvement, as follows.…”

Indoor self-localization using multipath arrival time measured by a single acoustic ranging sensor

“…[15][16][17][18][19] Various time-of-flight (ToF) measurement methods have been proposed by applying digital communication technology. [20][21][22][23][24][25][26][27] Numerical methods for moving sources have also been proposed for the design of sensors and measurement algorithms. 28) A method using ultrasonic sensors can detect transparent objects and is not much affected by optical scatterers.…”