An Efficient Precoding Algorithm for mmWave Massive MIMO Systems
Name
symmetry-11-01099.pdf
Size
2.05 MB
Format
Adobe PDF
Checksum (MD5)
1e72924038bd602f97c83fc08784c9c6
Author(s)
Khan, Imran
Henna, Shagufta
Anjum, Nasreen
Sali, Aduwati
Rodrigues, Jonathan
Khan, Yousaf
Khattak, Muhammad Irfan
Altaf, Farhan
Date Issued
September 2, 2019
Journal
Symmetry
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Khan, Imran, et al., "An Efficient Precoding Algorithm for mmWave Massive MIMO Systems." Symmetry 11, 9 (Sept. 2019): no. 1099 doi 10.3390/sym11091099 ©2019 Author(s)
Version
Final published version
Abstract
Symmetrical precoding and algorithms play a vital role in the field of wireless communications and cellular networks. This paper proposed a low-complexity hybrid precoding algorithm for mmWave massive multiple-input multiple-output (MIMO) systems. The traditional orthogonal matching pursuit (OMP) has a large complexity, as it requires matrix inversion and known candidate matrices. Therefore, we propose a bird swarm algorithm (BSA) based matrix-inversion bypass (MIB) OMP (BSAMIBOMP) algorithm which has the feature to quickly search the BSA global optimum value. It only directly finds the array response vector multiplied by the residual inner product, so it does not require the candidate’s matrices. Moreover, it deploys the Banachiewicz–Schur generalized inverse of the partitioned matrix to decompose the high-dimensional matrix into low-dimensional in order to avoid the need for a matrix inversion operation. The simulation results show that the proposed algorithm effectively improves the bit error rate (BER), spectral efficiency (SE), complexity, and energy efficiency of the mmWave massive MIMO system as compared with the existing OMP hybrid and SDRAltMin algorithm without any matrix inversion and known candidate matrix information requirement. Keywords: beamforming; 5G; massive MIMO; mmWave communications; spectral efficiency
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/sym11091099
