• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.666-675
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• 2008

The IEEE 802.22 standard is being developed with the target of improving the efficiency of spectrum utilization and importing the new wireless communication service. The WRAN standard based on Cognitive Radio is being processed for sharing TV bands. In this paper, the efficient spectrum allocation scheme and the optimal power allocation scheme, Partial Constant Power Water Filling (PCPWF), are proposed to maximize the channel capacity and spectrum efficiency and minimize the interference between adjacent cells. And we maximize the system throughput and fairness by using proposed dynamic cell plan that efficiently allocates channel. The results of the simulations are presented to verify the utilization of our proposed scheme.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.15-23
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• 2018

Spectrum allocation is a key operation in cognitive radio networks (CRNs), where secondary users (SUs) are usually selfish - to achieve itself utility maximization. In view of this context, much prior lit literature proposed spectrum allocation base on non-cooperative game models. However, the most of them proposed non-cooperative game models based on complete information of CRNs. In practical, primary users (PUs) in a dynamic wireless environment with noise uncertainty, shadowing, and fading is difficult to attain a complete information about them. In this paper, we propose a non-cooperative game joint hidden markov model scheme for spectrum allocation in CRNs. Firstly, we propose a new hidden markov model for SUs to predict the sensing results of competitors. Then, we introduce the proposed hidden markov model into the non-cooperative game. That is, it predicts the sensing results of competitors before the non-cooperative game. The simulation results show that the proposed scheme improves the energy efficiency of networks and utilization of SUs.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.627-638
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• 2014

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and non-uniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1532-1553
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• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1192-1207
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• 2014

Dynamic spectrum sharing is a key technology to improve spectrum utilization in wireless networks. The elastic spectrum management provides a new opportunity for licensed primary users and unlicensed secondary users to efficiently utilize the scarce wireless resource. In this paper, we present a game-theoretic framework for dynamic spectrum allocation where the primary users rent the unutilized spectrum to the secondary users for a monetary profit. In reality, due to the ON-OFF behavior of the primary user, the quantity of spectrum that can be opportunistically shared by the secondary users is limited. We model this situation with the renewal theory and formulate the spectrum pricing scheme with the Bertrand game, taking into account the scarcity of the spectrum. By the Nash-equilibrium pricing scheme, each player in the game continually converges to a strategy that maximizes its own profit. We also investigate the impact of several properties, including channel quality and spectrum substitutability. Based on the equilibrium analysis, we finally propose a decentralized algorithm that leads the primary users to the Nash-equilibrium, called DST. The stability of the proposed algorithm in terms of convergence to the Nash equilibrium is also studied.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.155-159
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• 2008

비능률적인 스펙트럼 이용률과 제한적인 스펙트럼 밴드 사용의 문제점을 해결하기 위하여, Cognitive Radio가 중요한 솔루션으로써 많은 연구가 진행되고 있다. 본 논문에서는 다중 채널 무선 네트워크에서의 QoS 보장을 위하여 Cognitive Radio 기반의 동적인 스펙트럼 할당 (Dynamic Spectrum Allocation)을 이용한 새로운 MAC 프로토콜을 제안한다. 사용자의 요청에 따라서, 유동적인 스펙트럼은 DSA 메커니즘을 통한 QoS 보장을 위하여 할당 된다. 그리고 동적인 스펙트럼 할당 (DSA)은 컨트롤 채널의 FRQ/FRP/ACK-hello와 데이터 채널의 DATA/ACK에 의하여 동작한다. 스펙트럼 공유의 성능을 증가시키기 위한 협력 검출 (Cooperative Detection)을 위하여, MAC 프로토콜에서는 Hello 메시지가 주기적으로 교환된다. 추가적으로, 성능 평가를 통하여 본 논문에서 제안한 DSA-MAC이 IEEE 802.11 MAC에 비하여 높은 데이터 처리량을 보임을 증명했다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1606-1612
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• 2012

Cognitive radio technology enables us to utilize the extra spectrum which is not used by the primary users by sensing the channel condition. To use such an extra spectrum, spectrum allocation is one of the important issues in the cognitive radio networks. The network is dynamic and the available channels are changeable, and the opportunistic channel allocation is required to use the resource efficiently without interference to the primary networks. In this paper, modified proportional fairness scheduling is proposed for cognitive radio networks to satisfy the both fairness and system throughput, and the modified scheduling was designed to reduce the interference to the primary users.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.833-841
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• 2011

In this paper, we propose uncoordinated dynamic frequency(channel) allocation schemes based on cognitive radio in mobile cellular networks(MCNs). Under the assumptions that mobile base stations are equipped with cognitive radio(CR) function and they construct uncoordinated network, the proposed scheme enables the MCNs by suppression of successive channel switching and management of channel allocation in a dynamic and distributed manner. The proposed scheme is composed of two phase processes. In the first phase, highly orthogonal sequences are generated and assigned to mobile base stations. In the second phase, each mobile base station is allocated a channel according to the pre-assigned orthogonal sequences. Simulation results show that the number of successive spectrum switching is reduced significantly compared with the random switching scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.1976-1997
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• 2016

This paper investigates the problem of co-tier interference mitigation for dynamic small- cell networks, in which the load of each small-cell varies with the number of active associated small-cell users (SUs). Due to the fact that most small-cell base stations (SBSs) are deployed in an ad-hoc manner, the problem of reducing co-tier interference caused by dynamic loads in a distributed fashion is quite challenging. First, we propose a new distributed channel allocation method for small-cells with dynamic loads and define a dynamic interference graph. Based on this approach, we formulate the problem as a dynamic interference graph game and prove that the game is a potential game and has at least one pure strategy Nash equilibrium (NE) point. Moreover, we show that the best pure strategy NE point minimizes the expectation of the aggregate dynamic co-tier interference in the small-cell network. A distributed dynamic learning algorithm is then designed to achieve NE of the game, in which each SBS is unaware of the probability distributions of its own and other SBSs' dynamic loads. Simulation results show that the proposed approach can mitigate dynamic co-tier interference effectively and significantly outperform random channel selection.