Receiver-Initiated Spectrum Management for Underwater Cognitive Acoustic Network

Abstract

Cognitive acoustic (CA) is emerging as a promising technique for environment-friendly and spectrum-efficient underwater communications. Due to the unique features of underwater acoustic networks (UANs), traditional spectrum management systems designed for cognitive radio (CR) need an overhaul to work efficiently in underwater environments. In this paper, we propose a receiver-initiated spectrum management (RISM) system for underwater cognitive acoustic networks (UCANs). RISM seeks to improve the performance of UCANs through a collaboration of physical layer and medium access control (MAC) layer. It aims to provide efficient spectrum utilization and data transmissions with a small collision probability for CA nodes, while avoiding harmful interference with both “natural acoustic systems”, such as marine mammals, and “artificial acoustic systems”, like sonars and other UCANs. In addition, to solve the unique challenge of deciding when receivers start to retrieve data from their neighbors, we propose to use a traffic predictor on each receiver to forecast the traffic loads on surrounding nodes. This allows each receiver to dynamically adjust its polling frequency according to the variation of a network traffic. Simulation results show that the performance of RISM with smart polling scheme outperforms the conventional sender-initiated approach in terms of throughput, hop-by-hop delay, and energy efficiency.