• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.51-55
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• 2017

This paper aims to maximize the energy harvesting rate and channel capacity in RF-energy harvesting networks (RF-EHNs) under the constraints of maximum transmit power and minimum quality of service (QoS) in terms of rate capacity for each user. We study a multi-user RF-EHN with frequency division multiple access (FDMA) in a Rayleigh channel. An access point (AP) simultaneously transmitting wireless information and power in the RF-EHN serves a subset of active users which have a power-splitting antenna. To gauge the network performance, we define energy efficiency (EE) and propose an optimization solution for maximizing EE with Lagrangian dual decomposition theory. In simulation results, we confirm that the EE is effectively maximized by the proposed solution with satisfying the given constraints.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.261-269
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• 2016

In this paper, the impact of energy constraints on a two-hop network with a source, a relay and a destination under random medium access is studied. A collision channel with erasures is considered, and the source and the relay nodes have energy harvesting capabilities and an unlimited battery to store the harvested energy. Additionally, the source and the relay node have external traffic arrivals and the relay forwards a fraction of the source node's traffic to the destination; the cooperation is performed at the network level. An inner and an outer bound of the stability region for a given transmission probability vector are obtained. Then, the closure of the inner and the outer bound is obtained separately and they turn out to be identical. This work is not only a step in connecting information theory and networking, by studying the maximum stable throughput region metric but also it taps the relatively unexplored and important domain of energy harvesting and assesses the effect of that on this important measure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.506-512
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• 2016

Recently, energy harvesting technology is considered as a tool to improve the lifetime of sensor networks by mitigating the battery capacity limitation problem. However, the previous work on energy harvesting has failed to provide practical information since it has assumed an ideal channel knowledge model with perfect channel state information at transmitter (CSIT). This paper proposes an energy efficient resource allocation scheme that takes account of the channel estimation process and the corresponding estimation error. Based on the optimization tools, we provide information on efficient scheduling and power allocation as the functions of channel estimation accuracy, harvested energy, and data rate. The simulation results confirm that the proposed scheme outperforms the conventional energy harvesting networks without considering channel estimation error in terms of energy efficiency. Furthermore, with taking account of channel estimation error, the results provides a new way for allocating resources and scheduling devices.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.6-11
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• 2016

In this paper, we studied a spectrum sensing algorithm for the efficient use of available spectrum in RF energy harvesting system combined with backscatter communication. We first looked for white spaces and then, selected low fading channel among white spaces using spectrum sensing algorithm at a transmitter. The transmitter employing the algorithm alleviates signal interference and improves the received signal strength indication through signals transmitted by low fading channel. The proposed RF energy harvesting system combined with backscatter communication is used the transmitter employing the algorithm. As a result of computer simulations, we can find the performance improvements of RF energy harvesting, BER of backscatter communication, and the received signal strength per distance of backscatter tag.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.1-5
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• 2015

Recently, RF energy harvesting technology is a promising technology for small-size IoT(Internet of Things) devices such as sensor to resolve battery scarcity problem. When applied to existing cognitive radio networks, this technology can be expected to increase network throughput through the increase of cognitive user's operating time. This paper proposes a optimal channel-selection policy for RF energy harvesting CR networks model where cognitive users in harvesting zone harvest ambient RF energy from transmission by nearby active primary users and the others in non-harvesting zone choose the channel and communicate with their receiver. We consider that primary users and secondary users are distributed as Poisson point processes and contact with their intended receivers at fixed distances. Finally we can derive the optimal frame duration, transmission power and density of secondary user from the proposed model that can maximize the secondary users's throughput under the given several conditions and suggest future directions of research.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.24-29
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• 2015

Recently, with developments of various networks, devices and various services, energy efficiency has become one of the most crucial issues with respect to sustainability of mobile devices. For connecting to networks seamlessly to offer services, a scenario of RF energy harvesting which supplies energy to wireless devices with RF signals is assumed. To increase the efficiency of RF energy harvesting, this paper proposes a RF energy harvesting algorithm which is based upon a frequency selective fading map. Through the algorithm, a receiver of mobile device can get fading information at each frequency and select a frequency which has the best quality. At the end, the simulation result demonstrates its superiority by showing a 4.45dB improvement in comparison to a deep fading frequency point.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1550-1553
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• 2020

In this paper, we maximize the lifetime of a multi-hop path through a cooperative wireless energy sharing scheme between constituent nodes in a wireless multi-hop communication. Considering a bidirectional multi-hop communication environment, we present an optimization problem to maximize path lifetime by adjusting the amount of energy each node needs to share with its neighboring nodes. On the basis of solidarity property, i.e., the lifetime of the multi-hop path is maximized when the lifetimes of all nodes are the same, we convert the considered optimization problem into a linear programming problem and solve it easily. Simulation result shows that the proposed two-way wireless energy sharing method maximizes the path lifetime of multi-hop communications and approximately doubles the path lifetime compared with the one-way energy sharing method.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1435-1443
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• 2009

In this paper, an energy harvesting sensor network system is modeled and simulated by using the DEVS (Discrete Event System Specification) formalism. The system is composed of a sink (master) node, which is battery or mains powered, and a set of sensor (slave) nodes, each of which harvests ambient energy and converts it into electrical energy. For simulation, (i) the behavior of energy harvesting and storing circuits of the slave node is partitioned into a set of piecewise continuous segments and then each segment is represented as a discrete state; (ii) the interaction among the master node and components of the slave node is investigated preciously; and (iii) the investigated result is modeled and simulated by using the DEVS formalism.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.121-129
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• 2012

In this paper, we consider a source node that operates over a time varying channel with energy harvesting capability. The goal of the source is to maximize the average number of successfully delivered packets per time slot. The source is able to choose whether to transmit a packet or defer the transmission in each time slot. The decision which is chosen by the source depends on the channel information available and the length of the energy queue. We formulate the problem of finding the optimal policy as a Markovian decision problem. We show some properties of the value function that represents the discounted number of successfully delivered packets per time slot. We prove that the optimal policy is a threshold type policy depending on the state of the channel and the length of the energy queue. We also derive an upper bound for the average number of packets per time slots successfully received by the destination. We show using numerical results that this bound is a tight bound on the performance of the optimal policy. And we consider the case of time varying channel but without channel state information (CSI). Then, we study the impact of channel time varying nature and the availability of CSI. In this case, we show that the optimal policy is a greedy policy. The performance of this greedy policy is also calculated.