Deep Learning-Based Hybrid Precoding Approach in the Massive Multiple-Input Multiple-Output System

Abstract

Precoding is a critical signal processing technique used in wireless communication systems to enhance transmission performance. This paper initially provides a brief overview of various conventional precoding algorithms. The exploration includes various nonlinear precoding algorithms which outperform linear techniques in high signal-to-noise ratio (SNR) scenarios. Moreover, the paper delves into practical considerations and provides insights into selecting the most suitable technique for specific communication scenarios. The deep learning-based hybrid precoder is designed using the MDL-AltMin algorithm and simulated results show a spectral efficiency of (SE) 40.96 dB compared with different precoding algorithms. The precoder model is modified with a Hybrid Precoding Net algorithm with a spectral efficiency of 21.07 dB for high values of SNR such as −30 and again compared with deep learning precoders. The HPNet model is proposed with a spectral efficiency of 23.04 dB with and without CSI (Channel State Information) at the transmitter. Furthermore, the HPNet model is compared with optimal digital precoders.

KEYWORDS:

• Channel matrix
• Deep learning
• Deep neural network
• Massive MIMO
• Precoding

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Srividhya Ramanathan

Srividhya Ramanathan obtained her bachelor's degree in electronics and communication engineering from Anna University in 2014. Then she obtained her master's degree in communication systems from Anna University in 2016. Her specializations include communication systems, MIMO systems, deep learning, and signal processing for wireless communication. Presently, she is doing her PhD, as a full-time scholar in Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai. Corresponding author. Email: [email protected]

Anto Bennet Maria

Anto Bennet Maria is a professor in the department of electronics & communication engineering at Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, India. He completed his BE degree in electronics engineering in 2000 at National Engineering College, and ME degree in applied electronics in December 2001 at Mohammed Sathak Engineering College, India. He completed his doctoral degree in the field of information and communication at Anna University, Chennai, India. His research area is antennas and signal processing. He has published more than 300 research articles in various international and national journals and conferences. He has more than 22 years of experience in teaching and research. He received AlCTE funds, international awards and life member in ISTE, IAENG, and IRED. He organized national conferences, workshops, symposiums, and seminars. He is a reviewer of several international journals. He is an approved supervisor under the faculty of information and communication engineering in Vel tech and Anna University, Tamil Nadu. Email: [email protected]