• Title/Summary/Keyword: Energy Efficient Cognitive Radio

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An Energy-efficient MAC Protocol in Cognitive Radio Environment (Cognitive Radio 환경을 고려한 에너지 효율적인 MAC 프로토콜)

  • Kim, Byung-Boo;Rhee, Seung-Hyong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.7 no.2
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    • pp.81-91
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    • 2008
  • In mobile wireless communications, there is a new approach that uses the lacking spectrum efficiently. A cognitive radio is a device that can changes its transmitter parameters based on interaction with the environment in which it operates. At present, the wireless communication standard for wireless device contains power-saving modes or energy efficient mechanisms which cuts off the power of transmitter and receiver for power-saving. However, in cognitive radio environment, every device has the Quiet Period for searching channel and existing energy-saving method is not appropriate to be adjust to cognitive radio environment. In this paper, we propose an energy-efficient MAC protocol of mobile device in cognitive radio environment and prove the improvement of proposed method.

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An Approach to maximize throughput for Energy Efficient Cognitive Radio Networks

  • Ghosh, Jyotirmoy;Koo, Insoo
    • International Journal of Advanced Culture Technology
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    • v.1 no.2
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    • pp.18-23
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    • 2013
  • In this paper, we consider the problem of designing optimal sensing time and the minimization of energy consumption in the Cognitive radio Network. Trade-off between throughput and the sensing time are observed, and the equations are derived for the optimal choice of design variables. In this paper, we also look at the optimization problem involving all the design parameters together. The advantages of the proposed scheme for the spectrum sensing and access process are shown through simulation.

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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.

A Sensing Node Selection Scheme for Energy-Efficient Cooperative Spectrum Sensing in Cognitive Radio Sensor Networks (인지 무선 센서 네트워크에서 에너지 효율적인 협력 스펙트럼 센싱을 위한 센싱 노드 선택 기법)

  • Kong, Fanhua;Jin, Zilong;Cho, Jinsung
    • Journal of KIISE
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    • v.43 no.1
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    • pp.119-125
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    • 2016
  • Cognitive radio technology can allow secondary users (SUs) to access unused licensed spectrums in an opportunistic manner without interfering with primary users (PUs). Spectrum sensing is a key technology for cognitive radio (CR). However, few studies have examined energy-efficient spectrum sensing in cognitive radio sensor networks (CRSNs). In this paper, we propose an energy-efficient cooperative spectrum sensing nodes selection scheme for cluster-based cognitive radio sensor networks. In our proposed scheme, false alarm probability and energy consumption are considered to minimize the number of spectrum sensing nodes in a cluster. Simulation results show that by applying the proposed scheme, spectrum sensing efficiency is improved with a decreased number of spectrum sensing nodes. Furthermore, network energy efficiency is guaranteed and network lifetime is substantially prolonged.

Efficient Energy Detection Method in Poor Radio Environment for Cognitive Radio System (Cognitive Radio 시스템을 위한 열악한 통신 환경에서 효과적인 에너지 검출방법)

  • Hyun, Young-Ju;Kim, Kyung-Seok
    • The Journal of the Korea Contents Association
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    • v.7 no.7
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    • pp.60-67
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    • 2007
  • The spectrum sensing is important for decision of using frequency band. It checks the frequency band for cognitive radio system. In this paper, we apply autocorrelation function to the energy detection method. We use the autocorrelation function to improve the performance of spectrum sensing method based on the energy detection method. This method is different from cyclostationary process method where parameters such as the mean or the autocorrelation function are time-varying periodically. And we propose improved method that is robust in poor radio environment. If the proposed method applies for sensing in the cognitive radio system, it will have the structural simplicity and the fast computation of spectrum sensing.

Energy Efficient Architecture Using Hardware Acceleration for Software Defined Radio Components

  • Liu, Chen;Granados, Omar;Duarte, Rolando;Andrian, Jean
    • Journal of Information Processing Systems
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    • v.8 no.1
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    • pp.133-144
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    • 2012
  • In order to make cognitive radio systems a practical technology to be deployed in real-world scenarios, the core Software Defined Radio (SDR) systems must meet the stringent requirements of the target application, especially in terms of performance and energy consumption for mobile platforms. In this paper we present a feasibility study of hardware acceleration as an energy-efficient implementation for SDR. We identified the amplifier function from the Software Communication Architecture (SCA) for hardware acceleration since it is one of the functions called for most frequently and it requires intensive floating-point computation. Then, we used the Virtex5 Field-Programmable Gate Array (FPGA) to perform a comparison between compiler floating-point support and the on-chip floating-point support. By enabling the on-chip floating-point unit (FPU), we obtained as high as a 2X speedup and 50% of the overall energy reduction. We achieved this with an increase of the power consumption by no more than 0.68%. This demonstrates the feasibility of the proposed approach.

ENC-MAC: Energy-efficient Non-overlapping Channel MAC for Cognitive Radio enabled Sensor Networks

  • Kim, Bosung;Kim, Kwangsoo;Roh, Byeong-hee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.11
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    • pp.4367-4386
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    • 2015
  • The concept of Internet of Things (IoT) has shed new light on WSN technologies. MAC protocol issues improving the network performance are important in WSNs because of the increase in demand for various applications to secure spectrum resources. Cognitive radio (CR) technology is regarded as a solution to the problems in this future wireless network. In recent years, energy efficiency has become an issue in CR networks. However, few relevant studies have been conducted. In this paper, an energy-efficient non-overlapping channel MAC (ENC-MAC) for CR-enabled sensor networks (CRSNs) is proposed. Applying the dedicated control channel approach, ENC-MAC allows the SUs to utilize channels in a non-overlapping manner, and thus spectrum efficiency is improved. Moreover, the cooperative spectrum sensing that allows an SU to use only two minislots in the sensing phase is addressed to en-hance energy efficiency. In addition, an analytical model for evaluating the performance, such as saturation throughput, average packet delay, and network lifetime, is developed. It is shown in our results that ENC-MAC remarkably outperforms existing MAC protocols.

Energy-Efficient Power Allocation for Cognitive Radio Networks with Joint Overlay and Underlay Spectrum Access Mechanism

  • Zuo, Jiakuo;Zhao, Li;Bao, Yongqiang;Zou, Cairong
    • ETRI Journal
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    • v.37 no.3
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    • pp.471-479
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    • 2015
  • Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency-division multiple access-based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a "bit per Joule" metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy-efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.

Simple Energy Detection Algorithm for Spectrum Sensing in Cognitive Radio

  • Lee, So-Young;Kim, Eun-Cheol;Kim, Jin-Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.1
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    • pp.19-26
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    • 2010
  • In this paper, we propose an efficient decision rule in order to get better chance to detect the unused spectrum assigned to a licensed user and improve reliability of spectrum sensing performance. Each secondary user receives the signals from the licensed user. And the resulting signals input to an energy detector. Then, each sensing result is combined and used to make a decision whether the primary user is present at the licensed spectrum band or not. In order to make the reliable decision, we apply an efficient decision rule that is called as a majority rule in this paper. The simulation results show that spectrum sensing performance with the proposed decision rule is more reasonable and efficient than that with conventional decision rules.