Orthogonality constrained analytic CMA for blind signal extraction improvement

Fan, Kuangang; Hou, Haonan; Tang, Yaofeng; Liu, Pingchuan

doi:10.1016/j.sigpro.2022.108880

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…In bubble-net attacking stage, the probability parameter P(P ∈ [0, 1]) selects the shrinking, encircling and spiral updating positions strategies. The formula is shown in Equation (7).…”

Section: Bubble-net Attackingmentioning

confidence: 99%

“…Although semi-blind equalization combines certain performance advantages of blind equalization and adaptive equalization, it also inherits the drawbacks of adaptive equalization, such as the inability to handle completely unknown channel conditions compared to blind equalization. In contrast to the other two equalization techniques, blind equalization primarily relies on prior information of the received signal, exhibiting strong robustness and applicability [7,8]. The advantages of blind equalization lie in its minimal bandwidth requirement and strong timeliness, enabling signal recovery and communication to be achieved in the shortest possible time.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Wireless Channel Equalization Method Based on Hybrid Whale Optimization: For Constant Modulus Blind Equalization System

Wang,

Zhang,

Sun

et al. 2023

Mathematics

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This paper proposes a wireless channel equalization method applied to the constant modulus blind equalization system, which addresses the slow convergence and strong randomness in the initialization of equalizer weights in the constant modulus blind equalization algorithm (CMA) by introducing a hybrid arithmetic whale optimization algorithm (HAWOA). The mean square error in the CMA is utilized as the cost function for the HAWOA to obtain a more effective initial weights for the equalizer. To validate the superiority of the hybrid arithmetic whale constant modulus blind equalization algorithm, tests are conducted on the equalization system using 16QAM and 64QAM signals. The simulation results demonstrate that the proposed algorithm achieved better initial weights compared to the CMA and the constant modulus blind equalization algorithm based on the whale optimization algorithm. It can obtain the desired mean square error with a lower symbol error rate in fewer iterations. Furthermore, the hybrid arithmetic whale constant modulus blind equalization algorithm exhibited faster convergence in optimizing initial weights, effectively enhancing the equalization performance of the CMA in wireless channels while ensuring timeliness.

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“…In bubble-net attacking stage, the probability parameter P(P ∈ [0, 1]) selects the shrinking, encircling and spiral updating positions strategies. The formula is shown in Equation (7).…”

Section: Bubble-net Attackingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%