| Issue |
MATEC Web Conf.
Volume 283, 2019
The 2nd Franco-Chinese Acoustic Conference (FCAC 2018)
|
|
|---|---|---|
| Article Number | 07003 | |
| Number of page(s) | 4 | |
| Section | Ultrasounds, Signal Processing, and NDT/E | |
| DOI | https://doi.org/10.1051/matecconf/201928307003 | |
| Published online | 28 June 2019 | |
Improved proportionate FONLMS algorithm based direct adaptive Turbo equalization for MIMO underwater acoustic communications
1 CNOOC Deepwater Development Limited, 518067, China Acoustic Science and Technology Laboratory, the College of Underwater Acoustic Engineering, Harbin Engineering University
2 Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin, 150001, China
3 Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University), Ministry of Industry and Information Technology ; Harbin, 150001, China
4 College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, 150001, China
* Corresponding author: angleliangtianyi@foxmail.com, zhangyouwen@hrbeu.edu.cn
In this paper, a novel normalized least mean squares (NLMS) algorithm that jointly updates the efficient of the linear equalizer and soft interference canceller (SIC) in an adaptive turbo equalizer for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. To exploit the sparsity of MIMO UWA channels and enhance the convergence speed of adaptive equalization, improved proportionate fast self-optimized NLMS algorithm (IPFONLMS), is proposed to well adapt to sparse channel with the similar complexity as improve proportionate NLMS (IPNLMS) algorithm. Then we extend the proposed algorithm to the adaptive turbo equalization for MIMO UWA communications. The performance of the proposed adaptive algorithm is evaluated by numerical results. Simulation results show that the improved data efficiency and bit error ratio (BER) performance of the proposed receiver is achieved over adaptive turbo equalizer based on the IPNLMS algorithm.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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