Hybrid Precoding for Multi-Cell mmWave Multiuser Massive MIMO 5G Networks

Abstract

In recent times, there has been a rapid growth in the data traffic demand. The 5G millimeter wave technology has been deployed to offer a large bandwidth resource for cellular systems. However, the millimeter wave communication suffers from high path losses. Therefore, there is a need to implement a high number of antennas to overcome the high propagation losses and offer beam-forming gain. Multiple-Input Multiple-Output is a wireless technology that uses multiple antennas at both the transmitter and receiver to enhance performance by increasing reliability and data speeds. The Multiple-Input Multiple-Output technology has the potential of meeting the need for high network capacity in the next generation cellular networks since it can offer improved power and spectrum efficiency. When massive Multiple-Input Multiple-Output is deployed in a multi-cell environment, inter-cell interference goes up as the cell edge users are approached. It also results in pilot contamination due to the frequent reuse of the pilots in each cell. In this paper, a Single Value Decomposition-based hybrid precoding scheme was formulated as a spectral efficiency maximization problem for multi-cell multi-user millimeter wave massive Multiple-Input Multiple-Output by minimizing channel estimation errors and inter-cell interference. The model was simulated in MATLAB, and the results for the full and partial connection scenarios. The results showed a 1.6381 times improvement in performance in terms of spectrum efficiency and normalized minimum square error when compared to the compressive sensing algorithm.