Abstract
The core of the OFDM-based wireless communication receiver is channel estimation. MIMO is used in 4G mobile communications to augment the system's capacity by outfitting the transceiver and receiver with multiple antennas using OFDM technology. MIMO-OFDM is a popular modern wireless broadband technology, owing to its large data transmission rate, resistance against multipath fading, and excellent spectral efficiency. This technology offers consistent communication and a broad range of coverage. The precise recovery of CSI and synchronization between the sender and receiver are the two major challenges in the MIMO-OFDM system. Several estimate techniques, including ‘pilot-aided, blind, and semi-blind channel estimating,’ are being used to extract the channel state information. In this survey, different channel estimate methods of the MIMO-OFDM system are reviewed and analyzed. Mainly it emphasis reviewing the various channel estimation methods, their advantages and drawbacks are furnished. The performance metrics in each contribution are also presented, and the recorded best performance is manifested. Finally, research gaps are identified and discussed, paving the way for developing a novel deep learning model for channel estimation in MIMO-OFDM systems.
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