• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권10호
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• pp.2455-2472
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• 2012

Although underlay spectrum sharing has been shown as a promising technique to promote the spectrum utilization in cognitive radio networks (CRNs), it may suffer bad secondary performance due to the strict power constraints imposed at secondary systems and the interference from primary systems. In this paper, we propose a two-phase based cooperative transmission protocol with the interference cancellation (IC) and best-relay selection to improve the secondary performance in underlay models under stringent power constraints while ensuring the primary quality-of-service (QoS). In the proposed protocol, IC is employed at both the secondary relays and the secondary destination, where the IC-based best-relay selection and cooperative relaying schemes are well developed to reduce the interference from primary systems. The closed-form expression of secondary outage probability is derived for the proposed protocol over Rayleigh fading channels. Simulation results show that, with a guaranteed primary outage probability, the proposed protocol can achieve not only lower secondary outage probability but also higher secondary diversity order than the traditional underlay case.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.197-199
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• 2016

최근 약 10년 동안, 인지무선환경에서 1차사용자와 2차사용자간의 스펙트럼 공유를 시장 (market) 논리와 접목시키는 연구들이 활발하게 진행되어 왔다. 즉, 1차사용자가 자신이 소유하고 있는 주파수 자원을 2차사용자에게 금전적 보상을 받고 대여하는 형태를 고려하는 것이다. 그리고, 이에 대한 시장의 평형 (market equilibrium)을 이론적으로 제시하는 것이 그 연구들의 주요 목표이다. 우리는 이 논문에서, 1차사용자들은 2차사용자들에게 자신들의 유휴 채널의 사용권을 대여 또는 판매하는데, 1차사용자들은 허용가능한 간섭의 양을 정해놓고, 2차사용자가 그 간섭의 양을 초과하게 되면 금전적인 보상을 받는 시장 모델을 고려한다. 그리고, 각 2차사용자는 자신들이 1차사용자들에게 지급할 수 있는 예산에는 제한이 있는 상황도 추가 고려한다. 2차사용자의 재화는 자유공간상에서 획득 가능한 전송률이고 1차사용자의 재화는 금전적인 순이득 (net profit)이다. 우리는 이러한 인지무선네트워크 시장을 확장된 Fischer 마켓으로 모델링하고, Eisenberg-Gale convex program을 통해 마켓 균형을 찾는 방법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.