A Comprehensive Review and Comparative analysis of 5G and 6G based MIMO Channel Estimation Techniques

A wireless network's overall performance is greatly impacted by the accuracy of its channel estimate. Deep learning has also shown to be a significant advancement in improving communication reliability and lowering processing complexity for 5G and beyond networks. Massive multiple-input multiple-output (MIMO) and mmWave communications are disruptive technologies that have been implemented into fifth-generation (5G) and subsequent wireless communication standards, such as 6G, in order to handle the increasing wireless data traffic and maintain connections. MIMO systems use space multiplex by using a variety of antennas to increase efficiency at a specifically used bandwidth. MIMO allows for numerous sources and sinks to share a single communication channel. The characteristics of these networks are their spectral variety and their ability to multiplex spatially. This study still provided an overview of MIMO, examined MIMO channel estimation methods based on the 5G and 6G wireless communication standards, and analysed MIMO channel estimation methods for the coexistence of these two wireless network generations.