• Title/Summary/Keyword: CRN(Cognitive Radio Network)

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Energy-Efficient Resource Allocation for Heterogeneous Cognitive Radio Network based on Two-Tier Crossover Genetic Algorithm

  • Jiao, Yan;Joe, Inwhee
    • Journal of Communications and Networks
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    • v.18 no.1
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    • pp.112-122
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    • 2016
  • Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

An Heuristic for Joint Assignments of Power and Subcarriers in Cognitive Radio Networks (인지라디오 네트워크에서 전력과 부반송파 할당을 위한 휴리스틱)

  • Paik, Chun-Hyun
    • Korean Management Science Review
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    • v.29 no.2
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    • pp.65-77
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    • 2012
  • With the explosivley increasing demand in wireless telecommunication service, the shortage of radio spectrum has been worsen. The traditional approach of the current fixed spectrum allocation leads to spectrum underutilization. Recently, CR (Cognitive Radio) technologies are proposed to enhance the spectrum utilization by allocating dynamically radio resources to CR Networks. In this study, we consider a radio resource(power, subcarrier) allocation problem for OFDMA-based CRN in which a base station supports a variety of CUs (CRN Users) while avoiding the radio interference to PRN (Primary Radio Network). The problem is mathematically formulated as a general 0-1 IP problem. The optimal solution method for the IP problem requires an unrealistic execution time due to its complexity. Therefore, we propose an heuristic that gives an approximate solution within a reasonable execution time.

Throughput Maximization for Cognitive Radio Users with Energy Constraints in an Underlay Paradigm

  • Vu, Van-Hiep;Koo, Insoo
    • Journal of information and communication convergence engineering
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    • v.15 no.2
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    • pp.79-84
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    • 2017
  • In a cognitive radio network (CRN), cognitive radio users (CUs) should be powered by a small battery for their operations. The operations of the CU often include spectrum sensing and data transmission. The spectrum sensing process may help the CU avoid a collision with the primary user (PU) and may save the energy that is wasted in transmitting data when the PU is present. However, in a time-slotted manner, the sensing process consumes energy and reduces the time for transmitting data, which degrades the achieved throughput of the CRN. Subsequently, the sensing process does not always offer an advantage in regards to throughput to the CRN. In this paper, we propose a scheme to find an optimal policy (i.e., perform spectrum sensing before transmitting data or transmit data without the sensing process) for maximizing the achieved throughput of the CRN. In the proposed scheme, the data collection period is considered as the main factor effecting on the optimal policy. Simulation results show the advantages of the optimal policy.

Improving Voice-Service Support in Cognitive Radio Networks

  • Homayounzadeh, Alireza;Mahdavi, Mehdi
    • ETRI Journal
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    • v.38 no.3
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    • pp.444-454
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    • 2016
  • Voice service is very demanding in cognitive radio networks (CRNs). The available spectrum in a CRN for CR users varies owing to the presence of licensed users. On the other hand, voice packets are delay sensitive and can tolerate a limited amount of delay. This makes the support of voice traffic in a CRN a complicated task that can be achieved by devising necessary considerations regarding the various network functionalities. In this paper, the support of secondary voice users in a CRN is investigated. First, a novel packet scheduling scheme that can provide the required quality of service (QoS) to voice users is proposed. The proposed scheme utilizes the maximum packet transmission rate for secondary voice users by assigning each secondary user the channel with the best level of quality. Furthermore, an analytical framework developed for a performance analysis of the system, is described in which the effect of erroneous spectrum sensing on the performance of secondary voice users is also taken into account. The QoS parameters of secondary voice users, which were obtained analytically, are also detailed. The analytical results were verified through the simulation, and will provide helpful insight in supporting voice services in a CRN.

Learning Automata Based Multipath Multicasting in Cognitive Radio Networks

  • Ali, Asad;Qadir, Junaid;Baig, Adeel
    • 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.

Delegation-based Authentication Protocol for Cognitive Radio Network (인지무선네트워크를 위한 위임기반 인증 프로토콜)

  • Kim, Hyunsung
    • 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.

Traffic Analysis of a Cognitive Radio Network Based on the Concept of Medium Access Probability

  • Khan, Risala T.;Islam, Md. Imdadul;Amin, M.R.
    • Journal of Information Processing Systems
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    • v.10 no.4
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    • pp.602-617
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    • 2014
  • The performance of a cognitive radio network (CRN) solely depends on how precisely the secondary users can sense the presence or absence of primary users. The incorporation of a spatial false alarm makes deriving the probability of a correct decision a cumbersome task. Previous literature performed this task for the case of a received signal under a Normal probability density function case. In this paper we enhance the previous work, including the impact of carrier frequency, the gain of antennas on both sides, and antenna heights so as to observe the robustness against noise and interference and to make the correct decision of detection. Three small scale fading channels: Rayleigh, Normal, and Weibull were considered to get the real scenario of a CRN in an urban area. The incorporation of a maximal-ratio combining and selection combing with a variation of the number of received antennas have also been studied in order to achieve the correct decision of spectral sensing, so as to serve the cognitive users. Finally, we applied the above concept to a traffic model of the CRN, which we based on a two-dimensional state transition chain.

Cooperative Sensing Clustering Game for Efficient Channel Exploitation in Cognitive Radio Network (인지무선 네트워크에서 효율적인 채널 사용을 위한 협력센싱 클러스터링 게임)

  • Jang, Sungjeen;Yun, Heesuk;Bae, Insan;Kim, JaeMoung
    • Journal of Satellite, Information and Communications
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    • v.10 no.1
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    • pp.49-55
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    • 2015
  • In cognitive radio network (CRN), spectrum sensing is an elementary level of technology for non-interfering to licensed user. Required sample number for spectrum sensing is directly related to the throughput of secondary user and makes the tradeoff between the throughput of secondary user and interference to primary user. Required spectrum sensing sample is derived from required false alarm, detection probability and minimum required SNR of primary user (PU). If we make clustering and minimize the required transmission boundary of secondary user (SU), we can relax the required PU SNR for spectrum sensing because the required SNR for PU signal sensing is related to transmission range of SU. Therefore we can achieve efficient throughput of CRN by minimizing spectrum sensing sample. For this, we design the tradeoff between gain and loss could be obtained from clustering, according to the size of cluster members through game theory and simulation results confirm the effectiveness of the proposed method.

On Cyclic Delay Diversity with Single Carrier OFDM Based Communication Network

  • A. Sathi Babu;M. Muni Chandrika;P. Sravani;M. Sindhu sowjanyarani;M. Dimpu Krishna
    • International Journal of Computer Science & Network Security
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    • v.24 no.2
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    • pp.95-100
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    • 2024
  • Cyclic Delay Diversity (CDD) is a diversity scheme used in OFDM-based telecommunication systems, transforming spatial diversity into frequency diversity and thus avoiding intersymbol interference without entailing the receiver to be aware of the transmission strategy making the signal more reliable achieving full diversity gain in cooperative systems. Here the analyzation of the influence of CDD-SC scheme in Cognitive Radio Network (CRN) is done with the challenge of overcoming the complication called channel estimation along with overhead in CNR. More specifically, the closed-form expressions for outage probability and symbol error rate are divided under different frequencies among independent and identically distributed (i.i.d.) frequency selective fading channel model i.e., the signal is divided into different frequencies and transmitted among several narrow band channels of different characteristics. It is useful in the reduction of interference and crosstalk. The results reveal the diversity order of the proposed system to be mainly affected by the number of multipath components that are available in the CNR.

Artificial Neural Network with Firefly Algorithm-Based Collaborative Spectrum Sensing in Cognitive Radio Networks

  • Velmurugan., S;P. Ezhumalai;E.A. Mary Anita
    • 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.