Massive multiple-input-multiple-output 5g wireless network using multiple objective selforganizing sand cat swarm optimization
The establishment of a fifth-generation (5G) Wireless Network (WN) is a worldwide effective research area. The network of 5G allows significant upgrades with the current system of wireless. While the combination of Massive Multipleinput-Multiple-Output (MIMO) in WN enables one to meet 5G technic...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2024
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/11796/1/P17002_29d51428029b10027b19d4a1d9da4c9b.pdf%206.pdf http://eprints.uthm.edu.my/11796/ http://10.1109/ICICACS60521.2024.10498384 |
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| Summary: | The establishment of a fifth-generation (5G)
Wireless Network (WN) is a worldwide effective research area.
The network of 5G allows significant upgrades with the current
system of wireless. While the combination of Massive Multipleinput-Multiple-Output (MIMO) in WN enables one to meet 5G
technical network necessities, it can manage various difficulties
to enhance performances. In this research, a multiple objective
Self-Organizing Sand Cat Swarm Optimization (SOMSCSO)
approach is proposed to address multiple objective functions
like average user rate, average area rate, the efficiency of
energy, and Spectral Efficiency (SE) of 5G WN with Massive
MIMO. Then, the fuzzy decision maker is employed for
choosing a solution vector to acquire the best compromising
outcomes. When compared to the existing approach like Selforganizing Particle Swarm Optimization (SOMPSO), the
proposed SOMSCSO approach achieves better performance of
30.451 (Mbps/user), 53.487 (Gbps/km2), 12.547 (Mbits/J),
49.567 (bps/Hz), and 25.89 sec in F1
, F2
, F3
, F4
and
computational time respectively |
|---|