• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3751-3774
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• 2014

With the rapid development of wireless communication, the confliction between the scarce frequency resources and the low spectral efficiency caused by the stationary spectrum sharing strategies seriously restricts the evolution of the future mobile communication. For this purpose, cognitive radio (CR) emerges as one of the most promising inventions which can overcome the spectrum shortage. As the key technology and main objective of CR, spectrum sharing can make full use of the limited spectrum, alleviate the scarcity of frequency resources and improve the system utilities, playing thereby an important role in improving the system performance of cognitive radio networks (CRNs). In this survey, the spectrum sharing in CRNs is discussed in terms of the sharing process, mainstream sharing technologies and spectrum sharing models. In particular, comparisons of different spectrum sharing strategies are concluded, as well as that of different spectrum sensing schemes in sharing procedure. Moreover, some application examples of the spectrum sharing in CRNs, such as smart grid, public safety, cellular network and medical body area networks are also introduced. In addition, our previous related works are presented and the open research issues in the field of spectrum sharing are stated as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4446-4462
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• 2019

In this paper, we focus on interference cancellation for three-hop cognitive radio networks (CRNs) over Rayleigh fading channels. In CRNs, secondary users (SUs) are allowed to opportunistically utilize the licensed spectrum during the idle time of primary users (PUs) to achieve spectrum sharing. However, the SUs maybe power constrained to avoid interference and cover a very short transmission range. We here propose an interference cancellation scheme (ICS) for three-hop CRNs to prolong the transmission range of SUs and improve their transmission efficiency. In the proposed scheme, a flexible transmission protocol is adopted to cancel the interference at both secondary relays and destinations at the same time. And a closed-form expression for the secondary outage probability over Rayleigh fading channels is derived to measure the system performance. Simulation results show that the proposed scheme can significantly reduce the secondary outage probability and increase the secondary diversity in comparison with the traditional cases.

• ETRI Journal
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• v.44 no.3
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• pp.400-412
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• 2022

In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.300-302
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• 2012

In this paper, we investigate the performance of multi-channel cognitive radio networks (CRNs) by taking into consideration the problem of channel assignment and link scheduling. We assume that secondary nodes are equipped with multiple radios and can switch among multiple channels. How to allocate channels to links and how much power used on each channel to avoid mutual interference among secondary links are the key problem for such CRNs. We formulate the problem of channel assignment and link scheduling as a combinatorial optimization problem. Then, we propose a the optimal solution and show that it converges to maximum optimum in some iterations by using numerical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.52-68
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• 2019

Aiming at the optimal placement of communication relay nodes (OPCRN) problem in manned/unmanned aerial vehicle cooperative engagement system, this paper designed a kind of fully connected broadband backbone communication topology. Firstly, problem description of OPCRN was given. Secondly, based on problem analysis, the element attributes and decision variables were defined, and a bi-level programming model including physical layer and logical layer was established. Thirdly, a hierarchical artificial bee colony (HABC) algorithm was adopted to solve the model. Finally, multiple sets of simulation experiments were carried out to prove the effectiveness and superiority of the algorithm.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.2957-2986
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• 2013

The traditional approach of fixed spectrum allocation to licensed networks has resulted in spectrum underutilisation. Cognitive radio technology is envisioned as a promising solution that can be used to resolve the ineffectiveness of the fixed spectrum allocation policy by accessing the underutilised spectrum of existing technologies opportunistically. The implementation of cognitive radio networks (CRNs) faces distinct challenges due to the fact that two systems (i.e., cognitive radio (CR) and primary users (PUs)) with conflicting interests interact with each other. Specially, in self-organised systems such as ad-hoc CRNs (AHCRNs), the coordination of spectrum access introduces challenges to researchers due to rapid utilisation changes in the available spectrum, as well as the multi-hop nature of ad-hoc networks, which creates additional challenges in the analysis of resource allocation (e.g., power control, channel and rate allocation). Instead, game theory has been adopted as a powerful mathematical tool in analysing and modelling the interaction processes of AHCRNs. In this survey, we first review the most fundamental concepts and architectures of CRNs and AHCRNs. We then introduce the concepts of game theory, utility function, Nash equilibrium and pricing techniques. Finally, we survey the recent literature on the game theoretic analysis of AHCRNs, highlighting its applicability to the physical layer PHY, the MAC layer and the network layer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.106-114
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• 2021

The needs in terms of wireless communications are growing up both for civil and military applications. Therefore a constant improvement of this technology is required to meet customer wishes. One of its main shortcomings is the inefficient use of the spectrum in which a large part of the allocated bands of frequencies is unused. Since communication is crucial, spectrum shortage problems can lead a multi-national and coalition operation to failure. Cognitive Radio Networks (CRNs) are a promising technology which continuously analyses the spectrum searching for available frequencies. It can solve this spectrum issue by avoiding interferences, improving system-wide spectral efficiency, robustness to dynamic conditions and allowing more spectrum flexibility This paper specifically analyzed and presented the application of the CRNs in the military operational environment, and presented the appropriate method applicable to each actual operational situation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1489-1503
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• 2018

Spectrum reuse has attracted much concern of researchers and scientists, however, the dynamic spectrum access is challenging, since an individual secondary user usually just has limited sensing abilities. One key insight is that spectrum usage forecasting among secondary users, this inspiration enables users to obtain more informed spectrum opportunities. Therefore, spectrum usage forecasting is vital to cognitive radio networks (CRNs). With this insight, a spectrum usage forecasting model for the occurrence of primary users prediction is derived in this paper. The proposed model is based on auto regressive enhanced primary user emergence reasoning (AR-PUER), which combines linear prediction and primary user emergence reasoning. Historical samples are selected to train the spectrum usage forecasting model in order to capture the current distinction pattern of primary users. The proposed scheme does not require the knowledge of signal or of noise power. To verify the performance of proposed spectrum usage forecasting model, we apply it to the data during the past two months, and then compare it with some other sensing techniques. The simulation results demonstrate that the spectrum usage forecasting model is effective and generates the most accurate prediction of primary users occasion in several cases.