Double-Scale Adaptive Transmission in Time-Varying Channel for Underwater Acoustic Sensor Networks

Abstract

The communication channel in underwater acoustic sensor networks (UASNs) is time-varying due to the dynamic environmental factors, such as ocean current, wind speed, and temperature profile. Generally, these phenomena occur with a certain regularity, resulting in a similar variation pattern inherited in the communication channels. Based on these observations, the energy efficiency of data transmission can be improved by controlling the modulation method, coding rate, and transmission power according to the channel dynamics. Given the limited computational capacity and energy in underwater nodes, we propose a double-scale adaptive transmission mechanism for the UASNs, where the transmission configuration will be determined by the predicted channel states adaptively. In particular, the historical channel state series will first be decomposed into large-scale and small-scale series and then be predicted by a novel k-nearest neighbor search algorithm with sliding window. Next, an energy-efficient transmission algorithm is designed to solve the problem of long-term modulation and coding optimization. In particular, a quantitative model is constructed to describe the relationship between data transmission and the buffer threshold used in this mechanism, which can then analyze the influence of buffer threshold under different channel states or data arrival rates theoretically. Finally, numerical simulations are conducted to verify the proposed schemes, and results show that they can achieve good performance in terms of channel prediction and energy consumption with moderate buffer length.

Design and Implementation of a UUV Tracking Algorithm for a USV

“…However, complementary cooperation between USVs and UUVs has recently been emphasized due to extensions of their range of operation [3]. In this complementary cooperation, the USV needs high performance (e.g., duration, velocity, payload, and navigation accuracy) compared to the UUV [4,5].…”

Accurate Channel Estimation and Adaptive Underwater Acoustic Communications Based on Gaussian Likelihood and Constellation Aggregation

“…Channel estimation is one of the key factors to realize reliable adaptive communications. At present, there are mainly three kinds of underwater acoustic channel estimation algorithms, such as channel estimation algorithms based on reference signal, blind estimation algorithms and semi-blind estimation algorithms [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. Among the three kinds of algorithms, the channel estimation capability and channel tracking capability based on the reference signal are the strongest.…”