A review of channel estimation research methods for massive MIMO systems

In massive MIMO systems, channel estimation is a crucial link. Its accuracy is directly related to the quality of signal recovery, adaptive modulation, and the selection of coding schemes, which in turn affects the performance of the entire communication system. With the continuous development of technology, channel estimation faces more and more challenges. The complexity of channel estimation continues to increase with the increase in the size of the antenna array. Classical channel estimation methods are difficult to accurately estimate, and mainstream channel estimation algorithms also need to be continuously improved. These challenges need to be overcome through continuous research and technological innovation. Nowadays, more and more research works on channel estimation are being conducted in the field of massive MIMO. However, the classification method of literature reviews in this field is roughly a classification of methods in a certain aspect. The overview is not comprehensive enough, or some methods are briefly summarized without detailed classification, thus lacking a systematic introduction and summary. This paper will classify from two aspects: classical algorithms and mainstream algorithms, focusing on the advantages and disadvantages of the two types of algorithms and their related impacts. Finally, the challenges and opportunities faced by channel estimation are discussed, the potential and limitations of emerging technologies such as deep learning in channel estimation are pointed out, and prospects for future research directions are proposed.