Indexed by:期刊论文
Date of Publication:2017-04-01
Journal:IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Included Journals:SCIE、EI
Volume:16
Issue:4
Page Number:2043-2056
ISSN No.:1536-1276
Key Words:Underwater cognitive acoustic communications; multi-hop transmission; network optimization; Bernstein approximation; mix-integer non-linear programming
Abstract:Acoustic communication is the most versatile and widely used technology for underwater wireless networks. However, the frequencies used by current acoustic modems are heavily overlapped with the cetacean communication frequencies, where the man-made noise of underwater acoustic communications may have harmful or even fatal impact on those lovely marine mammals, e.g., dolphins. To pursue the environmental friendly design for sustainable underwater monitoring and exploration, specifically, to avoid the man-made interference to dolphins, in this paper, we propose a cognitive acoustic transmission scheme, called dolphin-aware data transmission (DAD-Tx), in multi-hop underwater acoustic networks. Different from the collaborative sensing approach and the simplified modeling of dolphins' activities in existing literature, we employ a probabilistic method to capture the stochastic characteristics of dolphins' communications, and mathematically describe the dolphin-aware constraint. Under dolphin-awareness and wireless acoustic transmission constraints, we further formulate the DAD-Tx optimization problem aiming to maximize the end-to-end throughput. Since the formulated problem contains probabilistic constraint and is NP-hard, we leverage Bernstein approximation and develop a three-phase solution procedure with heuristic algorithms for feasible solutions. Simulation results show the effectiveness of the proposed scheme in terms of both network performance and dolphin awareness.
Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Gender:Female
Alma Mater:大连理工大学
Degree:Doctoral Degree
School/Department:信息与通信工程学院
Business Address:海山楼A420
Contact Information:lslwf@dlut.edu.cn
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