Multipath Effects on High-Frequency Coherent Acoustic Communications in Shallow Water

Abstract

Shallow-water acoustic communication channel, referred to as a multipath-limited channel, produces inter-symbol interference that poses a significant obstacle to reliable communication. Accordingly, signal-to-multipath ratio (SMR), rather than signal-to-noise ratio (SNR), becomes an important factor affecting communication performance. However, it is difficult to estimate SMR from measured communication data, especially at higher frequency (>10 kHz) because many arrivals scattered from rough ocean boundaries produce a significant intrapath time spreading, which acts as random noise in communication. In this paper, the energy fraction of the channel impulse response existing in one symbol duration is proposed as a parameter for estimating the quality of shallow-water communication channels. This parameter is compared with the bit-error-rate performance for data acquired in shallow water off the south coast of Korea, where the water depth is 45 m and the bottom consists of sandy clay sediment. The results imply that the energy fraction in one symbol duration may be used as a parameter for describing shallow-water communication channels and applied to the quick decision of a symbol or bit rate in a shallow-water field for reliable underwater communication.

Dual-Satellite Alternate Switching Ranging/INS Integrated Navigation Algorithm for Broadband LEO Constellation Independent of Altimeter and Continuous Observation

“…(2) Multipath and NLOS error model Due to the multipath effect, NLOS causes pseudorange measurement errors and carrier phase measurement errors, which affect the accuracy of satellite navigation and positioning, therefore, according to the reference [32], we model according to the direct signal relative to the multipath signal amplitude (Signal-to-Multipath Ratio, SMR), which is different from the reference [32]. We model the multipath and NLSO together.…”

Estimate of Passive Time Reversal Communication Performance in Shallow Water

“…The parameter E(t) estimates the relative energy contribution of the multipath with respect to time. After that, Son et al [23] suggested the E 1 parameter by applying the concept of the E(t), which is an energy fraction of the channel impulse response over one symbol duration. They showed that the overall BER performance improved as E 1 increased.…”

“…At site 1 (where the bottom is considered an acoustically slow bottom and the angle of intromission was estimated to be about 18.2 • ), most energy incident on the bottom was transmitted into the sediment, resulting in a large bottom loss. See Reference [23] for a detailed discussion of the channel characteristics of site 1. In contrast, the bottom of site 2 is considered to be a relatively fast bottom, and the critical grazing angle was estimated to be about 24 • .…”

Optimal Deployment of Sensor Nodes Based on Performance Surface of Underwater Acoustic Communication

“…Recursive Least-Squares (RLS) algorithm was used to adaptively update the filter weights of the equalizer, and a forgetting factor was 0.995. The number of feedforward and feedback filter taps in the DFE is related to the delay time spread due to the multipaths in the underwater communication channel [ 10 , 17 ]. In this paper, the tap numbers covering the delay time spread sufficiently were used in the equalizer process.…”

“…Most attempts to find an optimal deployment scheme for sensor nodes have assumed that every sensor node has the same sensing range [ 6 , 7 , 8 , 9 ], which is reasonable in the case of terrestrial wireless communication systems. However, underwater communication performance is significantly influenced by temporal and spatial variations in the ocean environment [ 10 , 11 ]. Underwater acoustic communication presents a challenging problem in that the underwater acoustic communication channel is a time-varying multipath channel formed by multiple interactions of sound with the sea surface and bottom of the ocean, particularly in shallow water.…”