• Electronic Materials Letters
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• v.14 no.6
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• pp.774-783
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• 2018

Full maximum-entropy mobility-spectrum analysis (FMEMSA) is the best algorithm among mobility spectrum analyses by which we can obtain a set of partial-conductivities associated with mobility values (mobility spectrum) by analyzing magnetic-field-dependent conductivity-tensors. However, it is restricted to a direct band-gap semiconductor and should be modified for materials with other band structures. We developed the modified version of FMEMSA which is appropriate for a material with a single anisotropic valley, or an indirect-band-gap semiconductor quantum-well with a single non-degenerate conduction-band valley e.g., (110)-oriented AlAs quantum wells with a single anisotropic valley. To demonstrate the reliability of the modified version, we applied it to several sets of synthetic measurement datasets. The results demonstrated that, unlike existing FMEMSA, the modified version could produce accurate mobility spectra of materials with a single anisotropic valley.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12B
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• pp.1068-1075
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• 2006

Frequency resource value is growing bigger more with the development of the wireless communication. But Frequency shortage phenomenon is risen seriously because the need of Frequency resource is very many compared with the supply in an information society of the future. So we need Cognitive technique Radio which is taking the attention recently to use Frequency resource not to be not using efficiently. We propose efficient Dynamic Spectrum Allocation method in IEEE a 802.22 WRAN environment of CR foundation in this paper. To share spectrum more efficiently, we presented some Dynamic Spectrum Allocation technique to apply the Variable bandwidth, Mobility and verified this through the result of the simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2101-2119
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• 2013

The spectrum allocation is an attractive issue for mobile cognitive radio (CR) network. However, the time-varying characteristic of the spectrum allocation is not fully investigated. Thus, this paper originally deduces the probabilities of spectrum availability and interference constrain in theory under the mobile environment. Then, we propose a prediction mechanism of the time-varying available spectrum lists and the dynamic interference topologies. By considering the node mobility and primary users' (PUs') activity, the mechanism is capable of overcoming the static shortcomings of traditional model. Based on the mechanism, two prediction-based spectrum allocation algorithms, prediction greedy algorithm (PGA) and prediction fairness algorithm (PFA), are presented to enhance the spectrum utilization and improve the fairness. Moreover, new utility functions are redefined to measure the effectiveness of different schemes in the mobile CR network. Simulation results show that PGA gets more average effective spectrums than the traditional schemes, when the mean idle time of PUs is high. And PFA could achieve good system fairness performance, especially when the speeds of cognitive nodes are high.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.347-352
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• 2017

In this paper, we propose a method that reduces mobile user's handover call dropping probability by using cognitive radio technology(CR) in cellular - based wireless cognitive radio networks. The proposed method predicts a cell to visit by Ziv-Lempel algorithm, and then supports mobile user with prediction of spectrum holes based on CR technology when allocated channels are short in the cell. We make neural network predict spectrum hole resources, and make handover calls use the resources before initial calls. Simulation results show CR technology has the capability to reduce mobile user handover call dropping probability in cellular mobile communication networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1324-1343
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• 2014

In recent years, the problem of spectrum mobility in Cognitive Radio (CR) Networks has been widely investigated. In order to utilize spectrum resources completely, many spectrum handoff techniques based on game theory have been proposed, but most studies only concern that users how to achieve better payoffs, without much attention to the diverse needs of users. In this paper, we propose a new channel-switching model based on game theory, using a prioritized approach to meet the diverse needs of users in two different modes (CQ and PS). At the same time, this paper proposes some acceleration techniques to reach the Nash equilibrium more efficiently. We evaluate the performance of the proposed schemes depending on priority using real channel availability measurements, and conclude that the channel quality function (CQ) mode provide better service for priority user but the plan-sorting (PS) mode can be more suitable in multiple priority users exist scene.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.222-227
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• 2013

This paper presents an analytical framework for dynamic spectrum allocation in cognitive radio networks. We propose a distributed queuing based Markovian model each for single channel and multiple channels access for a contending user. Knowledge about spectrum mobility is one of the most challenging problems in both these setups. To solve this, we consider probabilistic channel availability in case of licensed channel detection for single channel allocation, while variable data rates are considered using channel aggregation technique in the multiple channel access model. These models are designed for a centralized architecture to enable dynamic spectrum allocation and are compared on the basis of access latency and service duration.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.90-97
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• 2012

In this paper, the new user mobility model which can be utilized to register user's location for interworking with heterogeneous overlay convergent networks under the time-varying radio propagation environment has been proposed. Thus the user mobility model is considered in order to evaluate the behaviors of users in the overlay convergent networks. This Mobile IP user mobility model will be very useful to model the user mobility behaviors and can be used to estimate the signaling traffic and frequency spectrum demands for massive data transfer for the heterogeneous overlay convergent networks.

• Journal of Radiation Protection and Research
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• v.18 no.1
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• pp.25-35
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• 1993

To develop a technique of theoretical alpha track density calculation for comparison with measured track density, an electrostatic ion spectrometer was specially designed and fabricated. The mobility spectrum of first radon daughter(Po-218) in the range of $0.07{\sim}5.0cm^2/V\;s$ from the radon chamber was measured using-the electrostatic ion spectrometer. Measurement was taken in a radon chamber operated using dry particle free air passed through silica gel, activated charcoal and molecular sieve filters. The mobility of a new-born Po-218 ion measured by the electrostatic ion spectrometer was determined to be $1.92cm^2/V\;s$. A comparison of the theoretical and measured alpha track densities was completed and uncertainties concerning the shape of the spectrum were analyzed. It was found that the discrepancies in track densities are primarily Que to the neglect of wall loss of ions in the theoretical track density calculation.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.83-89
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• 2012

In this paper, the new user mobility management scheme which can be utilized to register user's location for interworking with heterogeneous overlay convergent networks under the time-varying radio propagation environment has been proposed. Thus the user mobility management can be considered in order to model and to evaluate the behaviors of users in the overlay convergent networks. This mobility management scheme will be very useful in characterizing the user mobility behaviors and can be used to estimate the signaling traffic and frequency spectrum demands for massive data transfer for the heterogeneous overlay convergent networks.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.