Reliable Underwater Acoustic Telemetry for Ocean Remote Sensing Platforms: Channel-Prediction-Based Adaptive Polar–Raptor Coded OFDM

Long propagation delays, severe multipaths, and narrow bandwidths make feedback-based link adaptation impractical in UWA channels at kilometer ranges, so we replace the feedback step with a prediction step. The transmitter runs a two-layer coded OFDM link in which Polar codes handle bit errors, and Raptor fountain codes handle packet erasures, with the Raptor overhead (OH) as the only real-time knob. The OH is picked from a lookup table indexed by three quantities the receiver can estimate online: SNR, RMS delay spread, and Doppler frequency. Two CSI predictors feed that table: Temporal Multiple Sparse Bayesian Learning (TMSBL), which exploits delay-domain sparsity, and the Square-Root Unscented Kalman Filter (SRUKF), which tracks per-subcarrier variations. We evaluate the system in five channel environments (AWGN, Rayleigh, K-distribution, Bellhop ray-tracing, and synthetic proxies parameterized from the KAM11 and WATERMARK sea-trial statistics). Across the nine Bellhop scenarios, the adaptive link’s throughput gain over a fixed-OH (OH=1.5) baseline at SNR =4 dB spans roughly −4% to +30%, with the largest benefit in the marginal short-range cases (shallow 500 m, +30%) where the fixed baseline is most over-provisioned and near-parity elsewhere. The scheme’s principal benefit is collapse prevention, tracking the Oracle within the safety margin and avoiding the throughput collapse the fixed baseline suffers at low SNRs. This effect is specific to the physically structured Bellhop channels; in the homogeneous Rayleigh and K-distribution channels, both schemes enter deep outage at very low SNRs, so it is not a universal guarantee. A 1000-trial high-resolution Rayleigh campaign sharpens the head-to-head between predictors: at SNR =4 dB, SRUKF + OH reaches PER 0.048 (95% Wilson CI [0.036, 0.063]) and TMSBL + OH reaches 0.071 ([0.057, 0.089]), and at SNR =12 dB, their throughputs (0.748 and 0.746) are statistically indistinguishable from each other (95% Wilson halfwidth ∼±0.014) and lie close to the Oracle’s 0.768 (within ∼0.02). The two predictors therefore occupy overlapping operating regions once the safety margin is matched, and a sparsity-dependent tendency (TMSBL in sparse multipath, SRUKF in dense multipath) appears only in physically structured channels and only at the n=100 screening level, where it is not statistically resolved and would benefit from higher-trial confirmation. A finite-blocklength check confirms that CA-SCL-decoded Polar codes at N=128 stay within 0.5 dB of the Polyanskiy normal approximation, which makes Polar a sensible inner code at UWA block lengths.

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Publication Details

Journal
Remote Sensing
Published
2026-05-29
DOI
https://doi.org/10.3390/rs18111747
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Reliable Underwater Acoustic Telemetry for Ocean Remote Sensing Platforms: Channel-Prediction-Based Adaptive Polar–Raptor Coded OFDM

Hyosong Lee, Saeyong Park, Taeho Im, Seunggyu Kim
Remote Sensing
Underwater Vehicles and Communication Systems
article

Reliable Underwater Acoustic Telemetry for Ocean Remote Sensing Platforms: Channel-Prediction-Based Adaptive Polar–Raptor Coded OFDM

Hyosong Lee, Saeyong Park, Taeho Im, Seunggyu Kim
article en

Abstract

Long propagation delays, severe multipaths, and narrow bandwidths make feedback-based link adaptation impractical in UWA channels at kilometer ranges, so we replace the feedback step with a prediction step. The transmitter runs a two-layer coded OFDM link in which Polar codes handle bit errors, and Raptor fountain codes handle packet erasures, with the Raptor overhead (OH) as the only real-time knob. The OH is picked from a lookup table indexed by three quantities the receiver can estimate online: SNR, RMS delay spread, and Doppler frequency. Two CSI predictors feed that table: Temporal Multiple Sparse Bayesian Learning (TMSBL), which exploits delay-domain sparsity, and the Square-Root Unscented Kalman Filter (SRUKF), which tracks per-subcarrier variations. We evaluate the system in five channel environments (AWGN, Rayleigh, K-distribution, Bellhop ray-tracing, and synthetic proxies parameterized from the KAM11 and WATERMARK sea-trial statistics). Across the nine Bellhop scenarios, the adaptive link’s throughput gain over a fixed-OH (OH=1.5) baseline at SNR =4 dB spans roughly −4% to +30%, with the largest benefit in the marginal short-range cases (shallow 500 m, +30%) where the fixed baseline is most over-provisioned and near-parity elsewhere. The scheme’s principal benefit is collapse prevention, tracking the Oracle within the safety margin and avoiding the throughput collapse the fixed baseline suffers at low SNRs. This effect is specific to the physically structured Bellhop channels; in the homogeneous Rayleigh and K-distribution channels, both schemes enter deep outage at very low SNRs, so it is not a universal guarantee. A 1000-trial high-resolution Rayleigh campaign sharpens the head-to-head between predictors: at SNR =4 dB, SRUKF + OH reaches PER 0.048 (95% Wilson CI [0.036, 0.063]) and TMSBL + OH reaches 0.071 ([0.057, 0.089]), and at SNR =12 dB, their throughputs (0.748 and 0.746) are statistically indistinguishable from each other (95% Wilson halfwidth ∼±0.014) and lie close to the Oracle’s 0.768 (within ∼0.02). The two predictors therefore occupy overlapping operating regions once the safety margin is matched, and a sparsity-dependent tendency (TMSBL in sparse multipath, SRUKF in dense multipath) appears only in physically structured channels and only at the n=100 screening level, where it is not statistically resolved and would benefit from higher-trial confirmation. A finite-blocklength check confirms that CA-SCL-decoded Polar codes at N=128 stay within 0.5 dB of the Polyanskiy normal approximation, which makes Polar a sensible inner code at UWA block lengths.

Remote SensingVol. 18(11)
Hoseo University (KR)
National Research Foundation of Korea
Life below water
Openalex Percentile: Top 7%
Underwater Vehicles and Communication Systems
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