• 정보과학회 논문지
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• 제43권12호
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• pp.1412-1419
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• 2016

인지 무선 센서 네트워크 (CRSNs)에서 보조 사용자가 (SUs) 주 사용자 (PUs)에 간섭을 주지 않고 기회주의적 방식으로 라이선스 대역을 사용할 수 있다. SUs가 스펙트럼 센싱을 통해 PU의 존재 여부를 확인할 수 있다. 그리고 센싱 시간은 스펙트럼 센싱의 중요한 파라미터이다. 센싱 시간은 센싱 성능과 스루풋 간의 균형을 얻을 수 있다. 본 논문에서는 다른 관점에서 이 균형을 탐구하기를 통해 스펙트럼 센싱을 위한 새로운 기법을 제안한다: a) PU의 검출 (SSPD)과 b)스루풋(SSST)을 극대화을 위한 스펙트럼 센싱이다. 제안한 기법에서 현재 프레임의 첫 번째 센싱 결과에 따라 동적인 두 번째 스펙트럼 센싱을 수행한다. CRSNs에서 에너지 제약을 때문에 네트워크 에너지 효율도 센싱 시간의 최적화를 통해 최대화된다. 시뮬레이션 결과를 통하여 제안된 SSPD과 SSST가 각각의 에너지 효율과 스루풋의 성능을 향상시킬 수 있음을 검증하였다.

• 한국위성정보통신학회논문지
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• 제10권1호
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• pp.49-55
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• 2015

인지무선 네트워크에서 스펙트럼 센싱은 우선사용자에게 간섭을 주지 않기 위해 기본적으로 수행해야 하는 단계이다. 스펙트럼 센싱에 요구되는 샘플 수는 2차 사용자의 성능에 직접적으로 영향을 주기 때문에, 2차 사용자의 성능과 우선사용자에 대한 간섭은 트레이드오프 관계에 있다. 스펙트럼 센싱에 필요한 샘플 수는 요구되는 오검출 확률, 검출확률 및 우선 사용자의 최소 요구 SNR로 부터 얻어진다. 우선 사용자 센싱에 요구되는 SNR은 2차 사용자의 전송반경과 관련 있기 때문에, 2차사용자들을 모아 센싱집합으로 구성하고 요구되는 전송영역을 최소화시킴으로써 스펙트럼 센싱에 요구되는 우선사용자의 SNR을 완화시킬 수 있다. 따라서 스펙트럼 센싱에 필요한 최소 샘플 수를 줄임으로써 인지무선 네트워크의 전송량을 향상시킬 수 있다. 본 논문에서는 이를 위해 센싱집합인 클러스터링을 통해 게임이론으로 클러스터의 크기에 따라 얻는 이득과 손실을 트레이드오프로 디자인하고, 시뮬레이션을 통해 제안된 방법의 성능을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권3호
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• pp.984-996
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• 2014

In this paper, optimal sensing time allocation for adaptive multiband spectrum sensing-transmission procedure is investigated. The sensing procedure consists of an exploration phase and a detection phase. We first formulate an optimization problem to maximize the throughput by designing not only the overall sensing time, but also the sensing time for every stage in the exploration and detection phases, while keeping the miss detection probability for each channel under a pre-defined threshold. Then, we transform the initial non-convex optimization problem into a convex bilevel optimization problem to make it mathematically tractable. Simulation results show that the optimized sensing time setting in this paper can provide a significant performance gain over the previous studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권2호
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• pp.184-201
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• 2013

In this paper, we study the problem of designing the power and number of cooperative node (CN) in the cooperation phase to maximize the average throughput for secondary user (SU), under the constraint of the total cooperation and transmission power. We first investigate the scheme of cooperative spectrum sensing without a separated control channel. Then, we prove that there indeed exist an optimal CN power when the number of CNs is fixed and an optimal CN number when CN power is fixed. The case without the constraints of the power and number of CN is also studied. Finally, numerical results demonstrate the characteristics and existences of optimal CN power and number. Meanwhile, Monte Carlo simulation results match to the theoretical results well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권4호
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• pp.1208-1222
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• 2014

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.

• Journal of Communications and Networks
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• 제18권5호
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• pp.784-795
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• 2016

In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the timevarying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V. Extensive simulations are presented to show the effectiveness of our proposed scheme.