• 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.

• The Journal of Information Technology
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• v.4 no.3
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• pp.65-75
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• 2001

Code-division multiple access has been widely accepted as the major multiple access scheme in mobile communication systems. Wide-band CDMA and its hybrid associate time-division CDMA are key elements in the mobile communication. Since 10 years ago, there has been enormous research activity in analysis of the capacity of these CDMA-based systems. Recently, upgrading service, high quality and the different service classes in radio resource allocation has recently increased. This paper presents an overview of Radio Resource Allocation on the CDMA-based systems that are flexible, support traffic services, minimize call blocking rate and have acceptable radio resource utilization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3674-3710
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• 2014

In this tutorial, we integrate the concept of cognitive radio technology into game theory and supermarket game theory to address the problem of resource allocation in multiuser multicarrier cognitive radio networks. In addition, multiuser multicarrier transmission technique is chosen as a candidate to study the resource allocation problem via game and supermarket game theory. This tutorial also includes various definitions, scenarios and examples related to (i) game theory (including both non-cooperative and cooperative games), (ii) supermarket game theory (including pricing, auction theory and oligopoly markets), and (iii) resource allocation in multicarrier techniques. Thus, interested readers can better understand the main tools that allow them to model the resource allocation problem in multicarrier networks via game and supermarket game theory. In this tutorial article, we first review the most fundamental concepts and architectures of CRNs and subsequently introduce the concepts of game theory, supermarket game theory and common solution to game models such as the Nash equilibrium and the Nash bargaining solution. Finally, a list of related studies is highlighted and compared in this tutorial.

• Journal of Satellite, Information and Communications
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• v.4 no.2
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• pp.5-11
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• 2009

In this paper, we propose our design of adaptive resource allocation in the cognitive radio network assisted by satellite to improve the performance of Cognitive Radio user. Most of today’s telecommunication network operates in a fixed, licensed frequency band using a specific spectrum access network. However, the spectrum is not always used all the time, all the band. It causes the inefficiency in the spectrum usage. Thus, cognitive radio network is proposed to solve these spectrum inefficiency problems. The cognitive radio users (secondary users) are coexistent with primary users (PUs) who are licensed. That cognitive radio network is considered as lower priority comparing with primary user. So, the operation of the cognitive radio network is limited to interference constraints. Especially, when the number of secondary users increases, CCI among SUs will increase as well as interference to PU. That motivates our objective to improve the performance even if cognitive radio users increase. To solve this problem, we suggest an adaptive resource allocation scheme to improve the performance of cognitive radio network assisted by satellite. Through this algorithm, we can improve the cognitive radio network performance. And the simulation results confirm the effectiveness of our proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4177-4190
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• 2015

Current research on Internet of Things (IoT) has primarily addressed the means to enhancing smart resource allocation, automatic network operation, and secure service provisioning. In particular, providing satisfactory security service in IoT systems is indispensable to its mission critical applications. However, limited resources prevent full security coverage at all times. Therefore, these limited resources must be deployed intelligently by considering differences in priorities of targets that require security coverage. In this study, we have developed a new application of Cognitive Radio (CR) technology for IoT systems and provide an appropriate security solution that will enable IoT to be more affordable and applicable than it is currently. To resolve the security-related resource allocation problem, game theory is a suitable and effective tool. Based on the Blotto game model, we propose a new strategic power allocation scheme to ensure secure CR communications. A simulation shows that our proposed scheme can effectively respond to current system conditions and perform more effectively than other existing schemes in dynamically changeable IoT environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3821-3841
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• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1479-1495
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• 2012

Spectrum scarcity seems to be the most challenging issue to be solved in new wireless telecommunication services. It is shown that spectrum unavailability is mainly due to spectrum inefficient utilization and inappropriate physical layer execution rather than spectrum shortage. Daily increasing demand for new wireless services with higher data rate and QoS level makes the upgrade of the physical layer modulation techniques inevitable. Orthogonal Frequency Division Multiple Access (OFDMA) which utilizes multicarrier modulation to provide higher data rates with the capability of flexible resource allocation, although has widely been used in current wireless systems and standards, seems not to be the best candidate for cognitive radio systems. Filter Bank based Multi-Carrier (FBMC) is an evolutionary scheme with some advantages over the widely-used OFDM multicarrier technique. In this paper, we focus on the total throughput improvement of a cognitive radio network using FBMC modulation. Along with this modulation scheme, we propose a novel uplink radio resource allocation algorithm in which fairness issue is also considered. Moreover, the average throughput of the proposed FBMC based cognitive radio is compared to a conventional OFDM system in order to illustrate the efficiency of using FBMC in future cognitive radio systems. Simulation results show that in comparison with the state of the art two algorithms (namely, Shaat and Wang) our proposed algorithm achieves higher throughputs and a better fairness for cognitive radio applications.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.157-165
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• 2009

In this paper, we investigate a dynamic spectrum sharing problem for the centralized uplink cognitive radio networks using orthogonal frequency division multiple access. We formulate a large-scale joint rate and power allocation as an optimization problem under quality of service constraint for secondary users and interference constraint for primary users. We also suggest admission control to nd a feasible solution to the optimization problem. To implement the resource allocation on a large-scale, we introduce a notion of using the conservative factors $\alpha$ and $\beta$ depending on the outage and violation probabilities. Since estimating instantaneous channel gains is costly and requires high complexity, the proposed algorithm pursues a practical and implementation-friendly resource allocation. Simulation results demonstrate that the large-scale joint rate and power allocation incurs a slight loss in system throughput over the instantaneous one, but it achieves lower complexity with less sensitivity to variations in shadowing statistics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2626-2646
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• 2014

This study presents a power and Physical Resource Blocks (PRBs) joint allocation algorithm to coordinate uplink (UL) interference in the device-to-device (D2D) underlaying Long Term Evolution-Advanced (LTE-A) networks. The objective is to find a mechanism to mitigate the UL interference between the two subsystems and maximize the weighted sum throughput as well. This optimization problem is formulated as a mixed integer nonlinear programming (MINLP) which is further decomposed into PRBs assignment and transmission power allocation. Specifically, the scenario of applying imperfect channel state information (CSI) is also taken into account in our study. Analysis reveals that the proposed PRBs allocation strategy is energy efficient and it suppresses the interference not only suffered by the LTE-A system but also to the D2D users. In another side, a low-complexity technique is proposed to obtain the optimal power allocation which resides in one of at most three feasible power vectors. Simulations show that the optimal power allocation combined with the proposed PRBs assignment achieves a higher weighted sum throughput as compared to traditional algorithms even when imperfect CSI is utilized.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1340-1346
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• 2022

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) using multiple transmit antennas, where the transmit antenna selection scheme is used to reduce the system complexity. Thus, in this paper, we propose radio resource allocation and receiver selection schemes in order to improve the outage probability performance of the downlink NOMA system using the transmit antenna selection scheme. In particular, the receiver selection scheme is a method of grouping the receivers to improve the outage probability performance, and the radio resource allocation scheme is a method of allocating radio resources to each group in order to enhance the outage probability performance. In addition, through the computer simulation under the assumption of independent Rayleigh fading channels, we show that the proposed radio resource allocation and receiver selection schemes can improve the outage probability performance at the expense of the sum rate performance.