Performance evaluation of polar coded neural demapper based 5G MIMO communication system by varying antenna size

Abstract

This paper proposes a Polar-coded neural damapper based 5G multiple-input multiple-output (MIMO) system for M transmitting and N receiving antenna, operating in a flat fading environment. MIMO is a spatial diversity scheme to improve channel performance and mitigate troubling fading issues in urban environments. A neural network-based smart demapper is considered instead of traditional demapper to improve the system's performance. Researchers have recently focused on developing complex neural network (NN)-based demapper on generating soft information for each transmitted bit. Neural demapper also increases spectral efficiency, meaning a symbol-to-bit demapper with higher complexity. This work considers a Polar-coded MIMO 5G communication system with 2×3, 2×4, 4×6 and 4×16 transmitting and receiving antennas, respectively, to evaluate the system performance under QAM modulation (4-QAM, 16-QAM, 256-QAM) techniques. It is evident from the simulated result that our proposed system performs better for lower-order modulation techniques with an increase in the number of transmitting and receiving antenna.