Design of an OFDMA-Based MAC Protocol for an Underwater Glider Network With Motion Prediction | Zendy

Yishan Su | Zendy; Rong Fan | Zendy; Zhigang Jin | Zendy; Xiaomei Fu | Zendy

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Design of an OFDMA-Based MAC Protocol for an Underwater Glider Network With Motion Prediction

Author(s) -

Yishan Su,

Rong Fan,

Zhigang Jin,

Xiaomei Fu

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2876028

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Underwater glider is a cost-effective underwater unmanned vehicle with high endurance for applications in both civilian and military fields. Mobile underwater acoustic sensor networks are consisted of underwater gliders confront with several unique challenges, including high spatial-temporal uncertainty and long propagation delay of acoustic signal. In this paper, we propose an OFDMA-based MAC protocol named G-MAC for an underwater glider network, which leverages dynamic sub-channel allocation and transmission power adjustment. G-MAC is a multichannel MAC protocol dedicated for using in underwater centralized networks, which aims to maximize the network's goodput. To solve the optimal problem, G-MAC allows for concurrent data transmissions by applying Nash equilibrium to allocate transmission subchannel and related power adjustment. In addition, to reduce the negative impact from spatial uncertainty, a motion prediction method based on the characteristic of underwater glider is applied. Simulation results document that G-MAC outperforms the existing solutions in terms of network goodput and energy consumption in the representative network scenario.

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