Volume 4, Issue 1, 2022, Pages 61 - 67

Author(s) : Mohammad Ali Abedi* ¹

Abstract :
Abstract Due to the limited scattering of local scatterers on the BS side in fifth-generation massive multiple-input multiple-output systems, the channels tend to be sparse. As a result, it is better to extract the potential sparsity in the channel estimation process and use compressive sensing as a very good working method for estimation efficiency. For this reason, in this paper, after analyzing the structure of massive multiple-input multiple-output systems, we examine the method of compressive sampling and compressive measurement sizes, and follow the methods of retrieval of sparse signals, including BP and LASSO, and then from it, we analyze the challenges of implementing massive multiple-input multiple-output systems and the work done in this field, and at the end, we simulate the proposed channel estimation solution, in which using compressive sensing in these systems and compared with other proposed methods, we realize the superiority of the proposed method.

Keywords :
compressive sensing, sparse signal, compressive measurement, sparse recovery.