Title: Advanced multiuser detector in massive MIMO using reproducing kernel Hilbert space by modified crow search algorithm

Authors: V.M. Manju; R.S. Ganesh

Addresses: Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Kumarakovil, Thuckalay, Tamil Nadu, India ' Department of Electronics and Communication Engineering, R.M.K. Engineering College, Kavaraipettai, Chennai, India

Abstract: In multi-user massive MIMO (MU-MIMO) systems, there exists a wide range of issues to be resolved for developing a low complexity, adaptive and efficient method. The most general characteristics include reduced latency, throughput, and energy efficiency. The complexity that exists in MU-MIMO detection is the correlation of antenna, signal detection, and channel estimation. So, for building up enhanced data transmission in MIMO systems, this study introduced a sophisticated approach for identifying the Gaussian channel matrix. A processing of the output signal is made easy by this Gaussian matrix. Here, achieving a low BER between sent and received bits is the main goal, and to that end, an optimisation approach is incorporated into this study. A Gaussian channel matrix is optimally tuned to obtain the lowest BER among sent and returned bits. A self-adaptive crow search algorithm (SA-CSA) is introduced in this study for optimisation purposes.

Keywords: massive MIMO; channel estimation; bit error rate; BER; Gaussian channel; SA-CSA approach.

DOI: 10.1504/IJBIC.2023.136103

International Journal of Bio-Inspired Computation, 2023 Vol.22 No.4, pp.206 - 216

Received: 01 Apr 2022
Accepted: 10 Jul 2023
Published online: 16 Jan 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article