Energy efficient joint radio resource management in D2D assisted cellular communication.

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Title: Energy efficient joint radio resource management in D2D assisted cellular communication.
Authors: Orakzai, Farooq Alam1 farooqorakzai@gmail.com, Iqbal, Muhammad1 miqbal1976@gmail.com, Naeem, Muhammad1 muhammadnaeem@gmail.com, Ahmad, Ayaz1 ayaz.uet@gmail.com
Source: Telecommunication Systems. Dec2018, Vol. 69 Issue 4, p505-517. 13p.
Subjects: Cell phone systems, Cellular neural networks (Computer science), Energy consumption, Mixed integer linear programming, Telecommunication
Abstract: Device-to-device (D2D) is one of the promising technology that can be used in association with cellular networks for the provision of high data rates, which is the foremost demand of today's cellular users. The climatic changes due to combustion are posing another big challenge that needs to be addressed by today's technologists to strive for existence of humanity. Thus developing energy efficient schemes for the deployment of such joint venture is a challenging task due to increased system complexity. This paper addresses the mode selection, user admission control and the resource allocation issues related to optimizing the overall Energy Efficiency (EE) of the cellular systems. The contributions that have been made in this paper are (1) Development of a pooled D2D and cellular network optimization model for efficient resource allocation (2) Development of an algorithm for maximization of EE for the proposed joint D2D cellular network. The problem formulated is a Mixed Integer Nonlinear Problem, whereas such problems belong to a class of optimization problems whose computational complexity is quite high that is NP-hard. In such hard problems the computational complexity increases with increasing the number of users that make these problems more challenging. Finding the optimal solution of such hard problems by the brute force and searching the feasible space is also challenging since the complexity increases exponentially by increasing the admitted users. A Mesh Adaptive Direct Search algorithm has been proposed to find the EE resource allocation for this user admission controlled D2D based cellular network. Based on analysis of our simulation results, it can be clearly designated that our proposed solution for increasing the EE for this joint cellular and D2D venture is very much close to optimal solution provided by Exhaustive Search Algorithm. [ABSTRACT FROM AUTHOR]
Copyright of Telecommunication Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Energy efficient joint radio resource management in D2D assisted cellular communication.
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  Data: <searchLink fieldCode="JN" term="%22Telecommunication+Systems%22">Telecommunication Systems</searchLink>. Dec2018, Vol. 69 Issue 4, p505-517. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Cell+phone+systems%22">Cell phone systems</searchLink><br /><searchLink fieldCode="DE" term="%22Cellular+neural+networks+%28Computer+science%29%22">Cellular neural networks (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Mixed+integer+linear+programming%22">Mixed integer linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication%22">Telecommunication</searchLink>
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  Label: Abstract
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  Data: Device-to-device (D2D) is one of the promising technology that can be used in association with cellular networks for the provision of high data rates, which is the foremost demand of today's cellular users. The climatic changes due to combustion are posing another big challenge that needs to be addressed by today's technologists to strive for existence of humanity. Thus developing energy efficient schemes for the deployment of such joint venture is a challenging task due to increased system complexity. This paper addresses the mode selection, user admission control and the resource allocation issues related to optimizing the overall Energy Efficiency (EE) of the cellular systems. The contributions that have been made in this paper are (1) Development of a pooled D2D and cellular network optimization model for efficient resource allocation (2) Development of an algorithm for maximization of EE for the proposed joint D2D cellular network. The problem formulated is a Mixed Integer Nonlinear Problem, whereas such problems belong to a class of optimization problems whose computational complexity is quite high that is NP-hard. In such hard problems the computational complexity increases with increasing the number of users that make these problems more challenging. Finding the optimal solution of such hard problems by the brute force and searching the feasible space is also challenging since the complexity increases exponentially by increasing the admitted users. A Mesh Adaptive Direct Search algorithm has been proposed to find the EE resource allocation for this user admission controlled D2D based cellular network. Based on analysis of our simulation results, it can be clearly designated that our proposed solution for increasing the EE for this joint cellular and D2D venture is very much close to optimal solution provided by Exhaustive Search Algorithm. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Telecommunication Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11235-018-0451-3
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        Text: English
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        PageCount: 13
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        Type: general
      – SubjectFull: Cellular neural networks (Computer science)
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      – SubjectFull: Energy consumption
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      – SubjectFull: Mixed integer linear programming
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            NameFull: Orakzai, Farooq Alam
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            NameFull: Iqbal, Muhammad
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              M: 12
              Text: Dec2018
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