1,962 research outputs found
Optimal Channel Selection for Simultaneous RF Energy Harvesting and Data Transmission in Cognitive Radio Networks
In this paper, an RF-powered cognitive radio network is considered, in which the secondary users are powered by an RF energy harvester (Rectenna). Unlike most existing works, we consider a realistic Rectenna characteristic function, and derive the actual amount of harvested energy and thus, the resulting actual energy level of the secondary users. We consider a system architecture at which simultaneous energy harvesting and data transmission for each secondary user is possible. We introduce a strategy to manage the challenge of network throughput decreasing due to lack of the secondary users’ energy, via selecting the best possible channels for energy harvesting and simultaneously by allocating the best channels for data transmission. Therefore, we implement cognition in spectrum utilization and in energy harvesting. We show that the amount of harvested energy affects the available energy of the secondary user and consequently the throughput, therefore, the channels selection to maximize energy harvesting affects the network throughput. To maximize the network throughput, the Hungarian algorithm is employed, and then, an algorithm with lower complexity based on the matching theory is proposed. Finally, we compare our proposed approach with some existing benchmarks and show its high performance in energy harvesting and system throughput
RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations
The increasing demand for spectral and energy efficient communication
networks has spurred a great interest in energy harvesting (EH) cognitive radio
networks (CRNs). Such a revolutionary technology represents a paradigm shift in
the development of wireless networks, as it can simultaneously enable the
efficient use of the available spectrum and the exploitation of radio frequency
(RF) energy in order to reduce the reliance on traditional energy sources. This
is mainly triggered by the recent advancements in microelectronics that puts
forward RF energy harvesting as a plausible technique in the near future. On
the other hand, it is suggested that the operation of a network relying on
harvested energy needs to be redesigned to allow the network to reliably
function in the long term. To this end, the aim of this survey paper is to
provide a comprehensive overview of the recent development and the challenges
regarding the operation of CRNs powered by RF energy. In addition, the
potential open issues that might be considered for the future research are also
discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin
Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer
Radio frequency (RF) energy harvesting and transfer techniques have recently
become alternative methods to power the next generation of wireless networks.
As this emerging technology enables proactive replenishment of wireless
devices, it is advantageous in supporting applications with quality-of-service
(QoS) requirement. This article focuses on the resource allocation issues in
wireless networks with RF energy harvesting capability, referred to as RF
energy harvesting networks (RF-EHNs). First, we present an overview of the
RF-EHNs, followed by a review of a variety of issues regarding resource
allocation. Then, we present a case study of designing in the receiver
operation policy, which is of paramount importance in the RF-EHNs. We focus on
QoS support and service differentiation, which have not been addressed by
previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ
Optimal time sharing in underlay cognitive radio systems with RF energy harvesting
Due to the fundamental tradeoffs, achieving spectrum efficiency and energy
efficiency are two contending design challenges for the future wireless
networks. However, applying radio-frequency (RF) energy harvesting (EH) in a
cognitive radio system could potentially circumvent this tradeoff, resulting in
a secondary system with limitless power supply and meaningful achievable
information rates. This paper proposes an online solution for the optimal time
allocation (time sharing) between the EH phase and the information transmission
(IT) phase in an underlay cognitive radio system, which harvests the RF energy
originating from the primary system. The proposed online solution maximizes the
average achievable rate of the cognitive radio system, subject to the
-percentile protection criteria for the primary system. The
optimal time sharing achieves significant gains compared to equal time
allocation between the EH and IT phases.Comment: Proceedings of the 2015 IEEE International Conference on
Communications (IEEE ICC 2015), 8-12 June 2015, London, U
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