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A Kalman Filter-Based Blind Adaptive Multi-User Detection Algorithm for Underwater Acoustic Networks
- Source :
- IEEE Sensors Journal. 16:4023-4033
- Publication Year :
- 2016
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2016.
-
Abstract
- An underwater acoustic Kalman filter-based blind adaptive multi-user detection algorithm, suitable for underwater acoustic communication networks, is proposed in this paper. The algorithm can be employed to effectively improve the system capacity of multi-user communication in underwater acoustic sensor networks, reduce transmitting power and costs on power control, extend the multi-user communication distance, weaken or eliminate intersymbol interference, multiple access interference and near-far effect, thus effectively utilizing limited underwater frequency band resource. First, the dynamic model of underwater acoustic multi-user communication system and the optimal filter equation of the proposed algorithm are found. Second, computation complexity is analyzed, and convergence analysis is carried out in terms of excess mean output energy. Finally, pool, river, sea, and under-ice asynchronous communication experiments have been carried out for both the scalar and the vector hydrophones. Good experimental results verify the effectiveness of the proposed algorithm.
- Subjects :
- Engineering
010505 oceanography
business.industry
020206 networking & telecommunications
02 engineering and technology
Filter (signal processing)
Kalman filter
Communications system
01 natural sciences
0202 electrical engineering, electronic engineering, information engineering
Electronic engineering
Algorithm design
Electrical and Electronic Engineering
Underwater
Underwater acoustics
business
Instrumentation
Algorithm
Underwater acoustic communication
0105 earth and related environmental sciences
Power control
Subjects
Details
- ISSN :
- 23799153 and 1530437X
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- IEEE Sensors Journal
- Accession number :
- edsair.doi...........4a17108400959b83c05739f836dc7585