• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.890-910
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• 2014

This paper investigates the spectrum hole utilization of cooperative schemes for the two-way relaying model in order to improve the utilization efficiency of limited spectrum holes in cognitive radio networks with imperfect spectrum sensing. We propose two specific bidirectional secondary data transmission (BSDT) schemes with two-step and three-step two-way relaying models, i.e., two-BSDT and three-BSDT schemes, where the spectrum sensing and the secondary data transmission are jointly designed. In the proposed cooperative schemes, the best two-way relay channel between two secondary users is selected from a group of secondary users serving as cognitive relays and assists the bi-directional communication between the two secondary users without a direct link. The closed-form asymptotic expressions for outage probabilities of the two schemes are derived with a primary user protection constraint over Rayleigh fading channels. Based on the derived outage probabilities, the spectrum hole utilization is calculated to evaluate the percentage of spectrum holes used by the two secondary users for their successful information exchange without channel outage. Numerical results show that the spectrum hole utilization depends on the spectrum sensing overhead and the channel gain from a primary user to secondary users. Additionally, we compare the spectrum hole utilization of the two schemes as the varying of secondary signal to noise ratio, the number of cognitive relays, and symmetric and asymmetric channels.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.6-10
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• 2015

RF energy harvesting technology is a promising technology for generating the electrical power from ambient RF signal to operate low-power consumption devices(eg. sensor) in wireless communication networks. This paper, motivated by this and building upon existing CR(Cognitive Radio) network model, proposes a optimal control policy for RF energy harvesting CR networks model where secondary users that have low power consumption harvest ambient RF energy from transmission by nearby active primary users, while periodically sensing and opportunistically accessing the licensed spectrum to the primary user's network. We consider that primary users and secondary users are distributed as Poisson point processes and contact with their intended receivers at fixed distances. Finally we can derive the optimal frame duration, transmission power and density of secondary user from the proposed model that can maximize the secondary users's throughput under the given several conditions and suggest future directions of research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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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 the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.453-461
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• 2019

In this paper, we focus on the study of multi-node rendezvous on one common channel among multiple channels before transmitting in CRAHNs (Cognitive Radio Ad-hoc Networks) for the efficient use of inefficient frequency resources. Most existing researches have dealt with the channel rendezvous between two nodes. But, it can be time-consuming to apply them to three or more nodes. In addition, it cab be impossible to communicate with each other. Therefore, in this paper, we propose a Multi-Node Sequence (MNSEQ), which allows three or more nodes to rendezvous on a single common channel in a short period of time. And, CSMA/CA was applied for data exchange after rendezvous. By performance evaluation through very extensive simulations, we have demonstrated that the proposed MNSEQ outperforms the existing scheme in terms of communication completion time and transmission efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3172-3193
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• 2022

Cognitive radio-simultaneous wireless information and power transfer (CR-SWIPT) has attracted much interest since it can improve both the spectrum and energy efficiency of wireless networks. This paper focuses on the resource sharing between a point-to-point primary system (PRS) and a multiuser multi-antenna cellular cognitive radio system (CRS) containing a large number of cognitive users (CUs). The resource sharing optimization problem is formulated by jointly scheduling CUs and adjusting the transmit power at the cognitive base station (CBS). The effect of accessing CUs' spatial channel correlation on the possible transmit power of the CBS is investigated. Accordingly, we provide a low-complexity suboptimal approach termed the semi-correlated semi-orthogonal user selection (SC-SOUS) algorithm to enhance the spectrum efficiency. In the proposed algorithm, CUs that are highly correlated to the information decoding primary receiver (IPR) and mutually near orthogonal are selected for simultaneous transmission to reduce the interference to the IPR and increase the sum rate of the CRS. We further develop a spatial correlation-based resource sharing (SC-RS) strategy to improve energy sharing performance. CUs nearly orthogonal to the energy harvesting primary receiver (EPR) are chosen as candidates for user selection. Therefore, the EPR can harvest more energy from the CBS so that the energy utilization of the network can improve. Besides, zero-forcing precoding and power control are adopted to eliminate interference within the CRS and meet the transmit power constraints. Simulation results and analysis show that, compared with the existing CU selection methods, the proposed low-complex strategy can enhance both the achievable sum rate of the CRS and the energy sharing capability of the network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.23-28
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• 2011

In this paper, we propose a channel selection scheme for secondary users in cognitive radio sensor networks, which includes learning automata and fuzzy logic system (FLS). In the proposed scheme, FLS is used as the channel selection mechanism while the learning automata algorithm is being used to learn the radio environment such as channel link quality. Signal to noise ratio of the link between primary user (PU) and secondary user (SU), the probability of choosing channel, and signal to noise ratio of the link between secondary users are chosen as input parameters for the FLS to decide one data channel among multiple channels. Simulation results show that the proposed scheme does indeed provide advantages in improving the throughput of CR networks, in comparison with some other previous schemes.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.352-354
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• 2011

The performance of multihop cognitive radio networks (CRN) can be improved significantly by using multiple channels in spectrum underlay fashion. However, interference due to the sharing of common radio channel and congestion due to the contention among those flows that share the same links become an obstacle to meet this challenge. How to control efficiently congestion and allocate power optimally to obtain a high end-to-end throughput is a key objective in this work. We reexamined the Network Utility Maximum (NUM) problem with a new primary outage constraint and proposed a novel resource allocation strategy to solve it effectively and efficiently.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.319-321
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• 2015

인지무선네트워크 (Cognitive Radio Networks) 환경에서 스펙트럼의 원소유주인 1차사용자가 전송을 개시하는 경우, 같은 채널을 사용하는 2차사용자의 TCP (Transmission Control Protocol) 는 전송 불능 상태가 되어 심각한 성능저하가 발생한다. 이러한 성능저하는 1차사용자의 등장으로 인해 채널이 사용 불가능 해지는 상태를 패킷 손실로 판단하여 재전송 타임아웃이 발생하기 때문에 발생된다. 우리는 이 문제를 링크 또는 물리 계층 (하위계층) 과 TCP간의 크로스레이어링을 통하여 해결하고자 한다. 하위 계층은 1차사용자의 전송이 감지되면, 이를 TCP에게 시그널링하고, TCP는 이를 통해 재전송 타이머와 혼잡 윈도우를 고정시키고, 패킷 전송을 중단하도록 한다. 또, 하위계층이 가용 채널을 감지하게 되면, 재차 TCP에게 시그널링을 함으로써, 전송이 신속하게 재개되도록 한다. 제안하는 방법은 실제 USRP(Universal Software Radio Peripheral)에 구현하여 성능의 향상을 검증한다.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.129-136
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• 2014

One of the fundamental issues in the design of dynamic spectrum access policy is the modeling of the dynamic behavior of channel occupancy by primary users. Under a Markovian modeling of channel occupancy, a periodic sensing and greedy access policy is known as one of the simple and practical dynamic spectrum access policies in cognitive radio networks. In this paper, the primary occupancy of each channel is modeled as a discrete-time alternating renewal process with generally distributed on- and off-periods. A periodic sensing and greedy access policy is constructed based on the general channel occupancy model. Simulation results show that the proposed policy has better throughput than the policies using channel models with exponentially distributed on- or off-periods.