A parametric replay-based framework for underwater acoustic communication channel simulation

Abstract

This paper lays the foundation of an underwater acoustic channel simulation methodology that is halfway between parametric modeling and stochastic replay of at-sea measurements of channel impulse responses. The motivation behind this approach is to extend the scope of use of replay-based methods by allowing some parameterization of the channel properties while complying with some level of realism. Based on a relative entropy minimization between the original channel impulse response and the simulated one, the idea is to deliberately distort the original channel statistics in order to meet some specified constraints.

Analysis of High-Frequency Communication Channel Characteristics in a Typical Deep-Sea Incomplete Sound Channel

“…The Doppler frequency shift in the received signals was removed as described in [14]. The temporal coherence of channels at different receiving depths was then calculated using Equation (7). The temporal coherence results at different receiving depths are shown in Figure 15.…”

“…Previous studies have focused on three characteristic channel parameters: amplitude, delay spread, and channel temporal coherence. As a basis for statistical channel modeling, the distribution of the envelope amplitude has been fitted to Rayleigh distribution [5][6][7], Rice distribution [8][9][10][11], lognormal distribution [12,13], K distribution [14,15], and Burr distribution [16]. Most of these studies analyze specific experimental data for statistical modeling of channel amplitudes and fading, providing references for channel prediction and channel tracking.…”

Statistical Channel Model and Systematic Random Linear Network Coding Based QoS Oriented and Energy Efficient UWSN Routing Protocol

“…A number of studies have been conducted to design a stochastic UWA channel model [17][18][19][20][21][22][23][24][25][26][27][28] based on the assessment of the experimental acoustic data retrieved at certain specific locations. Authors have suggested Ricean fading [17,18] or Rayleigh fading [19][20][21], however, in some works, log-normal distribution [22,23] and the Ricean shadowed distribution [26] to enable better fit for measurement. The majority of these approaches apply experiment-specific characteristics, including location of the network deployment and the kind of signals to be applied to perform the test.…”

Parametric Replay-Based Simulation of Underwater Acoustic Communication Channels

“…A preliminary version of this paper has been presented at the Conference on Underwater Communications and Networking (UComms) held in Sestri Levante, Italy, in September 2014 [1]. DRAFT conduct.…”

“…stochastic replay). 1 From a single measurement, it is thus possible to compare competing transmission schemes when faced with the same realistic environment [5]. Thanks to Monte-Carlo simulations, design and validation metrics such as bit error rate [3]- [5], capacity bounds [6]- [8] or fading statistics [4] can be computed with a good accuracy.…”