Print ISSN: 1811-9212

Online ISSN: 2617-3352

Keywords : Genetic Algorithm


Path loss Optimization in WIMAX Network using Genetic Algorithm

Shahad Nafea; Ekhlas Kadum Hamza

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2020, Volume 20, Issue 1, Pages 24-30

The most necessary factors effect on the standard of broadband access services in mobile systems are WIMAX signal throughput and area coverage range. The environment controls are based on the sign power of any radio communication system. The sign power in any base station site relies on the space between the transmitter and the receiver, carrier frequency for the transmitter and the receiver along on the path loss. One of the most generally utilized experimental model to predict the path loss is the COST-231 Hata model. In this paper, the path loss rates have calculated based on the WIMAX criterion frequency at an area with 3.5GHz, that constant distances (7km) of transmitting base station into receive base station in urban, suburban environments. The execution of the COST-231 Hata paradigm and optimized paradigm are rated over the path loss. This model is optimized using Genetic Algorithm Technique using a computational tool MATLAB. Path loss results acquired show that the optimized paradigm rates a little higher than rates standard. The distance (7km)is good because of achieving the lowest value for path loss.

Combining Genetic Algorithm and Direction of Arrival for MIMO Wireless Communication System†

Mohammed Hussein Miry; Dr. Ghaida A. AL-Suhail

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2015, Volume 15, Issue 2, Pages 58-64

Abstract—In the next generation of wireless communications, Multiple Input Multiple Output (MIMO) communication system will be a key technology to enhance the communication efficiency. The popular method for estimating the direction of arrival of sources impinging on an array of MIMO sensors is Multiple Signal Classification (MUSIC) method which is a problem of great interest in MIMO communication system. The iterative searching technique has been shown more likely to converge to a local maximum, causing errors in Direction of arrival (DOA) estimation. A new system is proposed to estimate direction of arrival of sources for Multiple Input Multiple Output (MIMO) communication system by combining Genetic Algorithm and (MUSIC) method. In the proposed model, by using Genetic algorithm the direction of arrival angles can be selected automatically good response by fast convergence, efficiency and yield more accuracy to estimate the direction of arrival of the sources over existing conventional spectral searching methods which is shown by the result of computer simulation for proposed system. The important feature of new system is that, it is observed that Genetic Algorithm (GA) combined with MUSIC method is a powerful alternative in online DOA estimation

Enhanced Genetic Algorithm Based on Node Codes for Mobile Robot Path Planning

Dr. Mohamed Jasim Mohamed; Mrs. Farah S. Khoshaba

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2012, Volume 12, Issue 2, Pages 69-80

Abstract: In this paper, a new Enhanced Genetic Algorithm (EGA) is used to find the best global path planning for a mobile robot according to a specific criterion. The EGA is enhanced by a new encoding method, new initial population creation method, new crossover and mutation operations as well as new additional operations correction operation and classification operation. The study considers the case when the mobile robot works in a known static environment. The new proposed algorithm is built to help the mobile robot to choose the shortest path without it colliding with the obstacles allocated in a working known environment. The use of grid map in the environment helps to locate nodes on the map where all nodes are assigned by coordinate values. The start and the target nodes of the required path are given prior to the proposed algorithm. Each node represents a landmark that the mobile robot either passes through only one time or never passes through during its journey from start node to the target node. Two examples of known static mobile robot environments with many obstacles in each one are studied and the proposed algorithm is applied on them. The results show that the proposed algorithm is very reliable, accurate, efficient and fast to give the best global path planning for the two cases.

Genetic Algorithm Using Sub-path Codes for Mobile Robot Path Planning

Dr. Mohamed Jasim Mohamed

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2012, Volume 12, Issue 1, Pages 104-117

In this paper, a new method for finding global optimal path planning is
proposed using a Genetic Algorithm (GA). A map of known static environment as well
as a start node and a target node connecting an optimal path which is required to be
found are given beforehand. The chosen nodes in a known static environment are
connected by sub-paths among each other. Each path is represented by a series of subpaths
which connect the sequential nodes to form this path. Each sub-path radiating
from each node is labeled by an integer. The chromosome code of a path is a string of
series integers that represent the labels of sub-paths which are passed through traveling
from start node to target node. Two factors are integrated into a fitness function of the
proposed genetic algorithm: the feasibility of collision avoidance path and the shortest
distance of path. Two examples of known static environment maps are taken in this
study with different numbers of obstacles and nodes. Simulation results show the
effectiveness and feasibility of the proposed GA using sub-path codes to find optimum
path planning for mobile robot.

FUZZY-GENETIC CONTROLLER FOR CONGESTION AVOIDANCE IN COMPUTER NETWORKS1

Prof. Dr. Mohammed Z. Al-Faiz; MIEEE; Assistant Lec. Ali M. Mahmood

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2011, Volume 11, Issue 2, Pages 20-27

Abstract:
In this paper a fuzzy proportional-Integral (FPI) controller is designed as an Active Queue Management (AQM) in internet routers to improve the performance of PI controller for congestion avoidance in computer networks. Firstly the parameters of FPI controller are selected by trial and error method, but to get the best controller parameters the Genetic Algorithm (GA) is used as an optimization method for tuning the FPI parameters. The analytical results for linearized TCP/AQM model are presented in MATLAB version 7.0. From the obtained results, a faster response time as well as the regulation of the output to a constant value by the designed FPI controller is clearly observed and it is noted that the FPI controller provides good tracking performance under different circumstances for congestion avoidance in computer networks.