• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3860-3875
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• 2014

Cognitive radio networks (CRNs) are composed of mobile users who can use multiple spectrum bands for communication. CRNs allow unlicensed users (called cognitive users) to efficiently utilize unused licensed spectrums without interfering with communications of licensed users (called primary users). The main goals of CRNs are to mitigate spectrum saturation and to improve spectrum utilization. This paper introduces state-of-the-art routing protocols for CRNs and addresses some limitations of these protocols. To resolve the limitations, we suggest a new research direction for routing protocols in CRNs. We implement our protocol to compare with the existing routing protocols for multi-hop CRNs. Our protocol shows good performance compared to the existing routing protocols in terms of network performance and PU protection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3711-3730
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• 2014

Cognitive radio networks (CRNs) have emerged as a promising solution to enhance spectrum utilization by using unused or less used spectrum in radio environments. The basic idea of CRNs is to allow secondary users (SUs) access to licensed spectrum, under the condition that the interference perceived by the primary users (PUs) is minimal. In CRNs, the channel availability is uncertainty due to the existence of PUs, resulting in intermittent communication. Transmission control protocol (TCP) performance may significantly degrade in such conditions. To address the challenges, some transport protocols have been proposed for reliable transmission in CRNs. In this paper we survey the state-of-the-art transport protocols for CRNs. We firstly highlight the unique aspects of CRNs, and describe the challenges of transport protocols in terms of PU behavior, spectrum sensing, spectrum changing and TCP mechanism itself over CRNs. Then, we provide a summary and comparison of existing transport protocols for CRNs. Finally, we discuss several open issues and research challenges. To the best of our knowledge, our work is the first survey on transport protocols for CRNs.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.130-139
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• 2014

Due to the unpredictable nature of channel availability, carrying delay-sensitive traffic in cognitive radio networks (CRNs) is very challenging. Spectrum leasing of radio resources has been proposed in the so called coordinated CRNs to improve the quality of service (QoS) experienced by secondary users (SUs). In this paper, the performance of coordinated CRNs under fixed-rate with hard-delay-constraints traffic is analyzed. For the adequate and fair performance comparison, call admission control strategies with fractional channel reservation to prioritize ongoing secondary calls over new ones are considered. Maximum Erlang capacity is obtained by optimizing the number of reserved channels. Numerical results reveal that system performance strongly depends on the value of the mean secondary service time relative to the mean primary service time. Additionally, numerical results show that, in CRNs without spectrum leasing, there exists a critical utilization factor of the primary resources from which it is not longer possible to guarantee the required QoS of SUs and, therefore, services with hard delay constraints cannot be even supported in CRNs. Thus, spectrum leasing can be essential for CRN operators to provide the QoS demanded by fixed-rate applications with hard delay constraints. Finally, the cost per capacity Erlang as function of both the utilization factor of the primary resources and the maximum allowed number of simultaneously rented channels is evaluated.

• 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.

• 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.

• 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.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.406-418
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• 2015

Cognitive radio networks (CRNs) have emerged as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows a secondary network comprising of secondary users (SUs) to coexist with a primary network comprising of licensed primary users (PUs) subject to the condition that SUs do not cause any interference to the primary network. Since it is necessary for SUs to avoid any interference to the primary network, PU activity precludes attempts of SUs to access the licensed spectrum and forces frequent channel switching for SUs. This dynamic nature of CRNs, coupled with the possibility that an SU may not share a common channel with all its neighbors, makes the task of multicast routing especially challenging. In this work, we have proposed a novel multipath on-demand multicast routing protocol for CRNs. The approach of multipath routing, although commonly used in unicast routing, has not been explored for multicasting earlier. Motivated by the fact that CRNs have highly dynamic conditions, whose parameters are often unknown, the multicast routing problem is modeled in the reinforcement learning based framework of learning automata. Simulation results demonstrate that the approach of multipath multicasting is feasible, with our proposed protocol showing a superior performance to a baseline state-of-the-art CRN multicasting protocol.

• ETRI Journal
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• v.40 no.5
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• pp.613-623
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• 2018

The instability of operational channels on cognitive radio networks (CRNs), which is due to the stochastic behavior of primary users (PUs), has increased the complexity of the design of the optimal routing criterion (ORC) in CRNs. The exploitation of available opportunities in CRNs, such as the channel diversity, as well as alternative routes provided by the intermediate nodes belonging to routes (internal backup routes) in the route-cost (or weight) determination, complicate the ORC design. In this paper, to cover the channel diversity, the CRN is modeled as a multigraph in which the weight of each edge is determined according to the behavior of PU senders and the protection of PU receivers. Then, an ORC for CRNs, which is referred to as the stability probability of communication between the source node and the destination node (SPC_SD), is proposed. SPC_SD, which is based on the obtained model, internal backup routes, and probability theory, calculates the precise probability of communication stability between the source and destination. The performance evaluation is conducted using simulations, and the results show that the end-to-end performance improved significantly.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.79-86
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• 2015

Cognitive radio networks (CRNs) offer the promise of intelligent radios that can learn from and adapt to their environment. CRN permits unlicensed users to utilize the idle spectrum as long as it does not introduce interference to the primary users due to the Federal Communications Commission's recent regulatory policies. Thereby, the security aspects in CRNs should be different with the other networks. The purpose of this paper is to devise a new delegation-based authentication protocol (NDAP) by extracting out the security aspects for unlicensed user authentication over CRNs from Tsai et al's delegation-based authentication protocol (TDAP). First of all, we will provide security analyses on the TDAP and set design goal for unlicensed user authentication. Then, we will propose a NDAP as a remedy mechanism for the TDAP and a new protocol for CRNs. The NDAP could be used as a security building block for the CRNs and various convergence applications.

• 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.