Publication:
Linear/Non-Linear Energy Harvesting Models via Multi-Antenna Relay Cooperation in V2V Communications

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Durak, Ata Lütfiye
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Kosu, Semiha

Babaei, Mohammadreza

Ata, Serdar Özgür

Durak-Ata, Lutfiye

Yanikomeroglu, Halim

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Institute of Electrical and Electronics Engineers (IEEE)

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Vehicle-to-vehicle (V2V) communications is a part of next-generation wireless networks to create smart cities with the connectivity of intelligent transportation systems. Besides, green communications is considered in V2V communication systems for energy sustainability and carbon neutrality. In this scope, radio-frequency (RF) energy harvesting (EH) provides a battery-free energy source as a solution for the future of V2V communications. Herein, the employment of RF-EH in V2V communications is considered where the bit error probability (BEP) of a dual-hop decode-and-forward relaying system is obtained depending on the utilization of antennas at the relay. The multiple antenna power-constraint relay harvests its power by applying dedicated antenna (DA)/power splitting (PS) EH modes and linear (L)/nonlinear (NL) EH models. Moreover, the links between nodes are exposed to double-Rayleigh fading. Finally, the performance of different system parameters is compared using theoretical derivations of BEP. The results provide a comprehensive analysis of the proposed system considering PS/DA-EH modes and L/NL-EH models, as well as deterministic/uniformly distributed placement of nodes. It is observed that PS-EH outperforms DA-EH assuming a placement of an equal number of antennas and distances. Moreover, optimal performance of PS/DA-EH is achieved by allocating more power and increasing the number of antennas for EH, respectively.

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IEEE Transactions on Green Communications and Networking

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OPEN

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Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing

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