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Underwater acoustic channels (UWA) are usually sparse, which can be exploited for adaptive equalization to improve the system performance. For the shallow UWA channels, based on the proportional minimum symbol error rate (PMSER) criterion, the adaptive equalization framework requires the sparsity selection. Since the sparsity of the *L*_{0} norm is stronger than that of the *L*_{1}, we choose it to achieve better convergence. However, because the *L*_{0} norm leads to NP-hard problems, it is difficult to find an efficient solution. In order to solve this problem, we choose the Gaussian function to approximate the *L*_{0} norm. Simulation results show that the proposed scheme obtains better performance than the *L*_{1} based counterpart.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E106-A No.6 pp.947-951

- Publication Date
- 2023/06/01

- Publicized
- 2022/12/06

- Online ISSN
- 1745-1337

- DOI
- 10.1587/transfun.2022EAL2069

- Type of Manuscript
- LETTER

- Category
- Communication Theory and Signals

Tian FANG

Shanghai Maritime University

Feng LIU

Shanghai Maritime University

Conggai LI

Shanghai Maritime University

Fangjiong CHEN

South China University of Technology

Yanli XU

Shanghai Maritime University

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Tian FANG, Feng LIU, Conggai LI, Fangjiong CHEN, Yanli XU, "L0-Norm Based Adaptive Equalization with PMSER Criterion for Underwater Acoustic Communications" in IEICE TRANSACTIONS on Fundamentals,
vol. E106-A, no. 6, pp. 947-951, June 2023, doi: 10.1587/transfun.2022EAL2069.

Abstract: Underwater acoustic channels (UWA) are usually sparse, which can be exploited for adaptive equalization to improve the system performance. For the shallow UWA channels, based on the proportional minimum symbol error rate (PMSER) criterion, the adaptive equalization framework requires the sparsity selection. Since the sparsity of the *L*_{0} norm is stronger than that of the *L*_{1}, we choose it to achieve better convergence. However, because the *L*_{0} norm leads to NP-hard problems, it is difficult to find an efficient solution. In order to solve this problem, we choose the Gaussian function to approximate the *L*_{0} norm. Simulation results show that the proposed scheme obtains better performance than the *L*_{1} based counterpart.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2022EAL2069/_p

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@ARTICLE{e106-a_6_947,

author={Tian FANG, Feng LIU, Conggai LI, Fangjiong CHEN, Yanli XU, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={L0-Norm Based Adaptive Equalization with PMSER Criterion for Underwater Acoustic Communications},

year={2023},

volume={E106-A},

number={6},

pages={947-951},

abstract={Underwater acoustic channels (UWA) are usually sparse, which can be exploited for adaptive equalization to improve the system performance. For the shallow UWA channels, based on the proportional minimum symbol error rate (PMSER) criterion, the adaptive equalization framework requires the sparsity selection. Since the sparsity of the *L*_{0} norm is stronger than that of the *L*_{1}, we choose it to achieve better convergence. However, because the *L*_{0} norm leads to NP-hard problems, it is difficult to find an efficient solution. In order to solve this problem, we choose the Gaussian function to approximate the *L*_{0} norm. Simulation results show that the proposed scheme obtains better performance than the *L*_{1} based counterpart.},

keywords={},

doi={10.1587/transfun.2022EAL2069},

ISSN={1745-1337},

month={June},}

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TY - JOUR

TI - L0-Norm Based Adaptive Equalization with PMSER Criterion for Underwater Acoustic Communications

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 947

EP - 951

AU - Tian FANG

AU - Feng LIU

AU - Conggai LI

AU - Fangjiong CHEN

AU - Yanli XU

PY - 2023

DO - 10.1587/transfun.2022EAL2069

JO - IEICE TRANSACTIONS on Fundamentals

SN - 1745-1337

VL - E106-A

IS - 6

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - June 2023

AB - Underwater acoustic channels (UWA) are usually sparse, which can be exploited for adaptive equalization to improve the system performance. For the shallow UWA channels, based on the proportional minimum symbol error rate (PMSER) criterion, the adaptive equalization framework requires the sparsity selection. Since the sparsity of the *L*_{0} norm is stronger than that of the *L*_{1}, we choose it to achieve better convergence. However, because the *L*_{0} norm leads to NP-hard problems, it is difficult to find an efficient solution. In order to solve this problem, we choose the Gaussian function to approximate the *L*_{0} norm. Simulation results show that the proposed scheme obtains better performance than the *L*_{1} based counterpart.

ER -