Article: Channel estimation in OFDM systems based on the Mamdani fuzzy genetic algorithm Journal: International Journal of Sensor Networks (IJSNET) 2025 Vol.47 No.2 pp.98 - 112 Abstract: Utilising compressive sensing technology for channel estimation can effectively enhance the spectrum efficiency of orthogonal frequency division multiplexing (OFDM) systems. However, the computational efficiency of conventional sparse channel estimation algorithms is a concern, and their performance is highly dependent on the quality of the measurement matrix and the sparsity level of the channel. Metaheuristic algorithms, currently, are among the commonly used methods for solving optimisation and search problems. Based on the principles of compressive sensing theory, this paper introduces a novel algorithm, the Mamdani fuzzy genetic algorithm (MGA), for sparse channel estimation by incorporating metaheuristic algorithms. Under basic testing conditions, the MGA algorithm can overcome the drawbacks of excessive reliance on measurement matrices, performing well, particularly in low-sparsity scenarios. Experimental results indicate that, compared to classical channel estimation algorithms, the proposed algorithm is more suitable for achieving estimation accuracy with lower pilot overhead. Inderscience Publishers - linking academia, business and industry through research

Title: Channel estimation in OFDM systems based on the Mamdani fuzzy genetic algorithm

Authors: Lanxue Liu; Teng Fei; Jingyu Zhang; Zhengyu Zhu; Xiaolin Wang

Addresses: School of Information Engineering, Tianjin University of Commerce, Tianjin 300400, China ' School of Information Engineering, Tianjin University of Commerce, Tianjin 300400, China ' China Mobile Communications Group Co., Ltd., Beijing 100000, China ' School of Information Engineering, Tianjin University of Commerce, Tianjin 300400, China ' School of Information Engineering, Tianjin University of Commerce, Tianjin 300400, China

Abstract: Utilising compressive sensing technology for channel estimation can effectively enhance the spectrum efficiency of orthogonal frequency division multiplexing (OFDM) systems. However, the computational efficiency of conventional sparse channel estimation algorithms is a concern, and their performance is highly dependent on the quality of the measurement matrix and the sparsity level of the channel. Metaheuristic algorithms, currently, are among the commonly used methods for solving optimisation and search problems. Based on the principles of compressive sensing theory, this paper introduces a novel algorithm, the Mamdani fuzzy genetic algorithm (MGA), for sparse channel estimation by incorporating metaheuristic algorithms. Under basic testing conditions, the MGA algorithm can overcome the drawbacks of excessive reliance on measurement matrices, performing well, particularly in low-sparsity scenarios. Experimental results indicate that, compared to classical channel estimation algorithms, the proposed algorithm is more suitable for achieving estimation accuracy with lower pilot overhead.

Keywords: compressed sensing; channel estimation; metaheuristics; orthogonal frequency division multiplexing; OFDM.

DOI: 10.1504/IJSNET.2025.144554

International Journal of Sensor Networks, 2025 Vol.47 No.2, pp.98 - 112

Received: 01 Aug 2024
Accepted: 09 Sep 2024
Published online: 19 Feb 2025 *

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Title: Channel estimation in OFDM systems based on the Mamdani fuzzy genetic algorithm

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