Optimization of Resource Block Allocation with Genetic Algorithm in MIMO-OFDMA

Risenologi : Jurnal Sains, Teknologi, Sosial, Pendidikan, dan Bahasa

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Title Optimization of Resource Block Allocation with Genetic Algorithm in MIMO-OFDMA
 
Creator Utami, Amalia Rizqi
 
Subject Resource Block
Genetic Algorithm
MIMO
 
Description The allocation of resource blocks is very important in wireless communication, there is an allocation of signal dimensions between users in the uplink and downlink channels. In recent years, wireless communications users are increasing day by day, but the challenge is that the available spectrum is very limited. In this article we will discuss the optimal allocation of resource blocks, which is one of the resources in MIMO-OFDMA, using the genetic algorithm (GA). The algorithm determines the number of resource blocks for each user and then transmits the results of the allocation  to each user. This study will also compare the results of the allocation without and with the Genetic Algorithm (GA). The measurement parameters are carried out by changing several parameters: the number of users, the probability of mutation, the number of resource blocks and the probability of crossover. The results showed that with the use of Genetic Algorithm (GA) in the system there was an increase in the capacity value when compared to without GA. Therefore, optimization of resource blocks using Genetic Algorithm (GA) can improve system performance.
 
Publisher Kelompok Peneliti Muda Universitas Negeri Jakarta
 
Date 2021-10-25
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://ejurnal.kpmunj.org/index.php/risenologi/article/view/234
10.47028/j.risenologi.2021.61b.234
 
Source Risenologi; Vol. 6 No. 1b (2021): CASTLE: Conference on Social, Science, Technology, Language and Education Research; 1-5
2720-9571
2502-5643
10.47028/j.risenologi.2021.61b
 
Language eng
 
Relation http://ejurnal.kpmunj.org/index.php/risenologi/article/view/234/127
 
Rights Copyright (c) 2021 Risenologi
https://creativecommons.org/licenses/by/4.0
 

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