Modeling and Analysis of Land-to-Ship Maritime Wireless Channels at 5.8 GHz

TL;DR

This paper presents a comprehensive study of land-to-ship wireless channels at 5.8 GHz, introducing a novel path loss model, sea-wave-induced fading concept, and enhanced simulation models, supported by extensive measurements and environmental data.

Contribution

It introduces a new physical-based large-scale path loss model, the SWIFT fading concept, and an improved two-ray model incorporating vessel motion, advancing maritime wireless channel understanding.

Findings

The proposed path loss model achieves high accuracy in dynamic environments.

SWIFT fading effectively captures sea surface fluctuation effects.

Small-scale fading varies with sea conditions, with Laplace distribution fitting most scenarios.

Abstract

Maritime channel modeling is crucial for designing robust nearshore communication systems, yet reliable models that account for the dynamic marine environment with varying sea waves, wind conditions, and vessel motions remain scarce. This article investigates land-to-ship maritime wireless channel characteristics at 5.8 GHz based upon an extensive measurement campaign, with concurrent hydrological and meteorological information collection. First, a novel large-scale path loss model with physical foundation and high accuracy is proposed for dynamic marine environments. Then, we introduce the concept of sea-wave-induced fixed-point (SWIFT) fading, a peculiar phenomenon in maritime scenarios that captures the impact of sea surface fluctuations on received power. An enhanced two-ray model incorporating vessel rotational motion is propounded to simulate the SWIFT fading, showing good alignment with measured data, particularly for modest antenna movements. Next, the small-scale fading is studied by leveraging a variety of models including the two-wave with diffuse power (TWDP) and asymmetric Laplace distributions, with the latter performing well in most cases, while TWDP better captures bimodal fading in rough seas. Furthermore, maritime channel sparsity is examined via the Gini index and Rician $K$ factor, and temporal dispersion is characterized. The resulting channel models and parameter characteristics offer valuable insights for maritime wireless system design and deployment.