AWOA: An Advanced Whale Optimization Algorithm for Signal Detection in Underwater Magnetic Induction Multi-Input–Multi-Output Systems

With the increasing exploitation and use of marine resources, the limitations of acoustic, optical, and radio frequency technologies for underwater communications have become increasingly apparent. Magnetic induction (MI) is a new communication technology that enables wireless data transmission via...

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Vydané v:Electronics (Basel) Ročník 12; číslo 7; s. 1559
Hlavní autori: Gao, Guohong, Wang, Jianping, Zhang, Jie
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.04.2023
Predmet:
Acoustics
Algorithms
Antennas
Antennas (Electronics)
Bit error rate
Communications systems
Complexity
Data transmission
Decomposition
Design
Induction, Electromagnetic
Magnetic induction
Marine resources
Marine technology
Mathematical optimization
Mean square errors
MIMO communication
MIMO communications
Optimization
Optimization algorithms
Receivers & amplifiers
Signal detection
Swarm intelligence
Underwater acoustics
Underwater communication
Underwater construction
Wireless communications
China
ISSN:2079-9292, 2079-9292
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Popis
Shrnutí:With the increasing exploitation and use of marine resources, the limitations of acoustic, optical, and radio frequency technologies for underwater communications have become increasingly apparent. Magnetic induction (MI) is a new communication technology that enables wireless data transmission via magnetic field coupling between transmitting and receiving coils. MI offers advantages such as channel stability, small antenna size, and no multi-path loss. Multi-input–multi-output (MIMO) is a multi-antenna technology that significantly increases system capacity and spectrum utilization without increasing bandwidth. The whale optimization algorithm (WOA) is a well-known bio-inspired algorithm that mimics the hunting behavior of whales to optimize swarm intelligence. This paper proposes a model for an underwater MIMO communication system based on magnetic induction. We then construct a signal detection algorithm for MI-MIMO systems using the advanced whale optimization algorithm (AWOA) and conduct simulation experiments to compare the performance and complexity of three standard signal detection algorithms: zero-forcing (ZF), minimum mean square error (MMSE), and maximum likelihood (ML). The experimental results show that AWOA achieves suboptimal results, as its bit error rate (BER) is close to that of the ML algorithm. Furthermore, the complexity of AWOA is comparable to that of the MMSE strategy. This work supports the development of a high-performance MI-based underwater communication system.
Bibliografia:ObjectType-Article-1
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics12071559