A Traffic Load-Aware OFDMA-Based MAC Protocol for Distributed Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks (UW-ASNs) have received increasing attention in the civil and military fields. However, due to the unique features of the underwater environment, designing a suitable media access control (MAC) protocol for UW-ASNs is an immense challenge. While orthogonal frequency division multiple access (OFDMA) is a multiple access technology based on orthogonal frequency division multiplexing (OFDM), allocating different subchannels to different users for parallel transmission. In this paper, we propose a traffic load-aware OFDMA-based MAC protocol for UW-ASNs, called TLAO-MAC, that can suit the operational requirements of distributed underwater sensor networks. It uses the exchange of control packets to collect data transmission requests and update the channel resource list. Neighboring nodes rely on receiving nodes to conduct channel negotiation and resource allocation in a distributed manner. In addition, we define the channel busyness index to sense the dynamic traffic load in distributed networks. The proposed TLAO-MAC includes two key schemes: an adaptive channel grouping algorithm based on channel busyness, and a distributed subcarrier and power allocation algorithm. By adaptively adjusting the channel grouping in consideration of the dynamics of the traffic load, TLAO-MAC allows simultaneous transmission between neighboring nodes and avoids conflict in the data channel. Under the premise of meeting the transmission rate requirement of the sender, the transmission power is saved to the greatest extent. The simulation results show that TLAO-MAC can improve network goodput and reduce end-to-end delay, showing better adaptability in distributed networks.

I. Introduction

Recently, human activities in the ocean have developed rapidly, and a large number of sensor nodes have been deployed underwater. Due to their various promising applications, such as marine disaster warning, environmental monitoring and resource exploration [1]–[3], underwater acoustic sensor networks (UW-ASNs) have been attracting increasing research interest.