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    Energy efficient spectrum allocation and mode selection for mission-critical D2D communications

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    Date
    2016
    Author
    Apostolos, Galanopoulos
    Konstantinos, Kousias
    Aikaterini, Nikolaidou
    Foukalas, Fotis
    Khattab, Tamer
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    Abstract
    Device-to-device (D2D) communications is considered as a key enabling technology in future cellular networks and thus, it has become an intriguing topic for research. It refers to an innovative technology that enables User Equipments (UEs) to communicate directly with each other without using the eNodeB. This is indeed a challenging technique for mission-critical communications, e.g. in public protection and disaster relief (PPDR) application. In such a critical application, energy efficiency is an important factor for long and reliable communication. This can be achieved using more spectrum applying the D2D paradigm in Heterogeneous Networks (HetNet). In this work, we simulate an LTE-Advanced (LTE-A) HetNet consisting of both macro and pico Base Stations (BSs). Spectrum allocation and mode selection is devised for the associated UEs in order to enhance their energy efficiency that will lead to higher lifetime. In particular, a number of Component Carriers (CC) are considered available for allocation to the BSs in order to utilize Carrier Aggregation (CA) of LTE-A while mode selection decisions are made by each BS in order to balance between power consumption minimization and UE target data rate achievement. Under this framework, a power minimization problem is formulated in order to provide a joint spectrum allocation and mode selection. This problem is solved using a state of the art optimization method known as proximal minimization algorithm. The obtained simulation results reveal the energy efficient spectrum allocation and mode selection according to channels' quality that can balance between achieving high data rate requirements and power minimization as an important factor to mission-critical applications such as PPDR services. 2016 IEEE.
    DOI/handle
    http://dx.doi.org/10.1109/INFCOMW.2016.7562116
    http://hdl.handle.net/10576/21115
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    • Electrical Engineering [‎2846‎ items ]

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