• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.890-910
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• 2014

This paper investigates the spectrum hole utilization of cooperative schemes for the two-way relaying model in order to improve the utilization efficiency of limited spectrum holes in cognitive radio networks with imperfect spectrum sensing. We propose two specific bidirectional secondary data transmission (BSDT) schemes with two-step and three-step two-way relaying models, i.e., two-BSDT and three-BSDT schemes, where the spectrum sensing and the secondary data transmission are jointly designed. In the proposed cooperative schemes, the best two-way relay channel between two secondary users is selected from a group of secondary users serving as cognitive relays and assists the bi-directional communication between the two secondary users without a direct link. The closed-form asymptotic expressions for outage probabilities of the two schemes are derived with a primary user protection constraint over Rayleigh fading channels. Based on the derived outage probabilities, the spectrum hole utilization is calculated to evaluate the percentage of spectrum holes used by the two secondary users for their successful information exchange without channel outage. Numerical results show that the spectrum hole utilization depends on the spectrum sensing overhead and the channel gain from a primary user to secondary users. Additionally, we compare the spectrum hole utilization of the two schemes as the varying of secondary signal to noise ratio, the number of cognitive relays, and symmetric and asymmetric channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2663-2674
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• 2014

For cognitive radio sensor networks (CRSNs) that use underlay-based spectrum access, the location of the primary user (PU) plays an important role in the power control of the secondary users (SUs), because the SUs must keep the minimum interference level required by the PU. Received signal strength (RSS)-based localization schemes provide low-cost implementation and low complexity, thus it is suitable for the PU localization in CRSNs. However, the RSS-based localization schemes have a high localization error because they use an inexact path loss exponent (PLE). Thus, applying a RSS-based localization scheme into the PU localization would cause a high interference to the PU. In order to reduce the localization error and improve the channel reuse rate, we propose a RSS-based PU localization scheme that uses distance calibration for CRSNs using underlay model-based spectrum access. Through the simulation results, it is shown that the proposed scheme can provide less localization error as well as more spectrum utilization than the RSS-based PU localization using the mean and the maximum likelihood calibration.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.23-28
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• 2011

In this paper, we propose a channel selection scheme for secondary users in cognitive radio sensor networks, which includes learning automata and fuzzy logic system (FLS). In the proposed scheme, FLS is used as the channel selection mechanism while the learning automata algorithm is being used to learn the radio environment such as channel link quality. Signal to noise ratio of the link between primary user (PU) and secondary user (SU), the probability of choosing channel, and signal to noise ratio of the link between secondary users are chosen as input parameters for the FLS to decide one data channel among multiple channels. Simulation results show that the proposed scheme does indeed provide advantages in improving the throughput of CR networks, in comparison with some other previous schemes.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.340-350
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• 2016

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.122-127
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• 2016

In this paper, new spectrum sensing schemes based on analog/RF front-end processing are introduced for IoT wireless sensor networks. While the conventional approaches for wireless channel cognition have been issued in signal processing area, the RF spectrum cognition concept makes it feasible to achieve cognitive wireless sensor networks (C-WSNs). The spectrum cognition at RF processing is categorized as four kinds of sensing mechanisms. Two recent reseaches are described as promising candidates for the C-WSN. One senses spectrum by the frequency discriminating receiver, the other senses and detects from the frequency selective super-regenerative receiver. The introduced systems with simple and low-power RF architectures play dual roles of channel sensing and demodulation. simultaneously. Therefore, introduced spectrum sensing receivers can be one of the best candidates for IoT wireless sensor devices in C-WSN environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.512-519
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• 2016

This paper presents spectrum utilization strategies in cognitive radio (CR) networks powered by multi-antenna based wireless energy transfer. Secondary access point (AP) with multiple antennas should transfer the energy to the secondary sensor nodes with energy beamforming and simultaneously induces no interference to PUs. In addition, sensor nodes can transmit information to the secondary AP using the harvested energy, only when the spectrum is not utilized by PUs. We analyze the achievable rate of the CR sensor networks and propose an interference nulling energy beamforming method to maximize the achievable rate. Finally, we also propose a frame scheduling algorithm in which the durations of wireless energy transfer/information transfer frames (phases) are optimized.

• 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 KIISE
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• v.43 no.12
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• pp.1412-1419
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• 2016

In cognitive radio sensor networks (CRSNs), secondary users (SUs) can occupy licensed bands opportunistically without causing interferences to primary users (PUs). SUs perform spectrum sensing to detect the presence of PUs. Sensing time is a critical parameter for spectrum sensing that can yield a tradeoff between sensing performance and secondary throughput. In this study, we investigate new approaches for spectrum sensing by exploring the tradeoff from a) spectrum sensing for PU detection (SSPD) and b) spectrum sensing for secondary throughput (SSST). In the proposed scheme, the first sensing result of the current frame determines the dynamic performance of the second spectrum sensing. Energy constraint in CRSNs leads to maximized network energy efficiency via optimization of sensing time. Simulation results show that the proposed scheme of SSPD and SSST improves network performance in terms of energy efficiency and secondary throughput, respectively.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.6-10
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• 2015

RF energy harvesting technology is a promising technology for generating the electrical power from ambient RF signal to operate low-power consumption devices(eg. sensor) in wireless communication networks. This paper, motivated by this and building upon existing CR(Cognitive Radio) network model, proposes a optimal control policy for RF energy harvesting CR networks model where secondary users that have low power consumption harvest ambient RF energy from transmission by nearby active primary users, while periodically sensing and opportunistically accessing the licensed spectrum to the primary user's network. 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.11 no.4
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• pp.52-57
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• 2016

The backscatter signals are very weak so they can be easily interfered by signal interferences and channels. In this paper, we propose a two-level classification algorithm for backscatter communications which chooses the idle frequency channel based on cognitive radio systems. The two-level classification algorithm provides an optimal idle frequency channel by obtaining informations about idle frequencies, fading of the channels, and the channels' usage state by primary users. Our simulation results show the improvement of BER and received power performance in backscatter communications by using the proposed algorithm, and the improvement of the algorithm's performance in backscatter communications.