Inter-symbol Anti-interference Algorithm for 5G Communication System Based on Deep Learning

Abstract

As a matter of fact, the fifth generation (5G) wireless technology requires huge capacity to ensure normal use of communications, and a large amount of data will cause interference between wireless communication systems. With this in mind, to reduce inter-symbol interference in wireless systems, MIMO-OFDM is employed, the rapid growth of deep learning has the potential to significantly enhance wireless system performance. In reality, applying deep learning to estimate channels in MIMO-OFDM systems can reduce channel errors as well as improve channel quality, thereby greatly reducing inter-code interference between systems. On this basis, this paper introduces various DL-based channel estimation and demonstrates its improvement in the efficiency of the system. According to the analysis, the usage of deep learning in 5G wireless communication systems has great advantages. In addition, the limitations and defects are also discussed at the same time. Overall, these results shed light on guiding further exploration of 5G communication.