A Survey on Deep Learning Based Channel Estimation in Doubly Dispersive Environments

نویسندگان

چکیده

Wireless communications systems are impacted by multi-path fading and Doppler shift in dynamic environments, where the channel becomes doubly-dispersive its estimation an arduous task. Only a few pilots used for conventional approaches to preserve high data rate transmission. Consequently, such estimators experience significant performance degradation mobility scenarios. Recently, deep learning has been employed due low-complexity, robustness, good generalization ability. Against this backdrop, current paper presents comprehensive survey on techniques based deeply investigating different methods. The study also provides extensive experimental simulations followed computational complexity analysis. After considering parameters as modulation order, mobility, frame length, architecture, of studied is evaluated several In addition, source codes made available online order make results reproducible.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2022

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2022.3188111