Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal

Abstract

The performances of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Designing the physical layer of a reliable data transmission system requires a knowledge of channel characteristics in terms of the specific parameters of the stochastic model. The Wide-Sense Stationary Uncorrelated Scattering (WSSUS) assumption simplifies the stochastic description of the channel, and thus the estimation of its transmission parameters. However, shallow underwater channels may not meet the WSSUS assumption. This paper proposes a method for testing the Wide-Sense Stationary (WSS) part of the WSSUS feature of a UAC channel on the basis of the complex envelope of a received probe Pseudo-Random Binary Sequence (PRBS) signal. Two correlation coefficients are calculated that can be interpreted, together, as a measure that determines whether the channel is WSS or not. A similar wide-sense stationarity assessment can be performed on the basis of the Time-Varying Impulse Response (TVIR) of a UAC channel. However, the method proposed in this paper requires fewer computational operations in the receiver of a UAC system. PRBS signal transmission tests were conducted in the UAC channel simulator and in real conditions during an inland water experiment. The correlation coefficient values obtained using the method based on the envelope of a probe signal and the method of analysing the TVIR estimates are compared. The results are similar, and thus, it is possible to assess if the UAC channel can be modelled as a WSS stochastic process without the need for TVIR estimation.

Reliable OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel

“…The STFCF is obtained as an autocorrelation function of a time-varying transfer function H(t, f ) of the channel, which, in turn, is calculated as Fourier transform of the impulse response h(t, τ). The STFCF is a function of time and frequency differences under the assumption that the TVIR of the channel represents a wide-sense stationary uncorrelated scattering process [11]. Then, it is possible to calculate the 2-dimensional scattering function:…”

Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

“…However, most existing adaptive SI cancellation algorithms aim at the single state of the SI channel, and the performance of some algorithms is greatly reduced when the SI channel changes. Unfortunately, the most SI channel is a time-space-frequency variant channel, such as the underwater acoustic channel [25]. Therefore, an improved IPNSAF algorithm based on the sparsity of the SI channel and the arctangent function has been proposed for the impulsive noise with the variable SI channel, and its application has been considered in ISUDC.…”

Application of Diversity Combining with RLS Adaptive Filtering in Data Transmission in a Hydroacoustic Channel

“…), as well as in the case of a strong stratification of water caused by the temperature or salinity, which can be observed in the basin of the Baltic Sea. It causes many reflections which lengthen the hydroacoustic channel memory and leads to inter-symbol interference including tens or hundreds of symbols, which makes communication much more difficult [ 4 , 5 , 6 ].…”