Ant ColonyPerformance Evaluation and Optimization–based Resource Allocation for D2D Communication
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2019 by IJCTT Journal | ||
| Volume-67 Issue-5 |
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| Year of Publication : 2019 | ||
| Authors : Mohammed Mahmoud Abd El-Hamid Nasr , Mohamed Fared Zaghloul , Reda Abo Elez , Ahmed Rashad Khalifa | ||
| DOI : 10.14445/22312803/IJCTT-V67I5P112 |
MLA Style:Mohammed Mahmoud Abd El-Hamid Nasr , Mohamed Fared Zaghloul , Reda Abo Elez , Ahmed Rashad Khalifa"Ant ColonyPerformance Evaluation and Optimization–based Resource Allocation for D2D Communication" International Journal of Computer Trends and Technology 67.5 (2019): 70-77.
APA Style:Mohammed Mahmoud Abd El-Hamid Nasr , Mohamed Fared Zaghloul , Reda Abo Elez , Ahmed Rashad Khalifa (2019). Ant ColonyPerformance Evaluation and Optimization–based Resource Allocation for D2D Communication International Journal of Computer Trends and Technology, 67(5), 70-77.
Abstract
In the fifth generation (5G), it is anticipated that device-to-device (D2D) operation will be locally incorporated as a part without any bounds. In Device-to-Device D2D network, Device-to-Device (D2D) communication recently has been developed as a new paradigm that supports spectrum reuse inside a cell, and enhancement quality of service (QoS) and leading to expert user experience. Spectrum allocation problem is an important part in the study of D2D communication and represent an open challenges in the spectrum allocation under D2D communication scenario. The resource allocation for D2D design consider the best solution towards this challenge. In this paper, we propose a D2D in which the resource allocation problem is formulated. Then, a resource allocation scheme based on Ant Colony Optimization (ACO) algorithm. . Finally, ACO is considered best solution oriented to identifying interference and establishing D2D links that can optimizing the same resources, consulting a graph representation of the network. Simulation using matlabtool studies and show self-learning nature , which results to a comparable performance to that of an optimal resource allocator. The swarm intelligence algorithm ACO, is adopted to resolve the optimization problem of maximizing the network sum rate while considering the QoS requirements.
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Keywords
Device-to-Device; Ant Colony Optimization; Spectrum allocation; resource allocation; spatial spectrum reuse; QoS requirements; LTE-Advanced