Relevant bibliographies by topics / OFDM-based cognitive radio

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'OFDM-based cognitive radio'

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Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "OFDM-based cognitive radio"

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Wang, Yonghua, Yuehong Li, Yiquan Zheng, Ting Liang, and Yuli Fu. "A Linear Weighted Sum Multi-objective Optimization Algorithm Based on PSO for Wideband Spectrum Sensing." International Journal of Online Engineering (iJOE) 11, no. 9 (2015): 9. http://dx.doi.org/10.3991/ijoe.v11i9.5058.

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In order to maximize throughput and minimize interference of the wideband spectrum sensing problem in OFDM cognitive radio sensor networks, a linear weighted sum multi-objective algorithm based on the Particle Swarm Optimization is proposed. The multi-objective optimization advantages of Particle Swarm Optimization are utilized to solve the optimal threshold vector of the spectrum sensing problem in OFDM cognitive radio sensor networks. So the network can get a larger throughput under the condition of small interference. The simulation results show that the proposed algorithm can make larger throughput while keeping the interference is smaller in OFDM cognitive radio sensor networks. Thus the spectrum resources are used more effectively.
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Saoucha, Naziha Ali, and Badr Benmammar. "Bio-inspired approaches for OFDM-based cognitive radio." International Journal of Internet Protocol Technology 12, no. 2 (2019): 61. http://dx.doi.org/10.1504/ijipt.2019.099680.

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Benmammar, Badr, and Naziha Ali Saoucha. "Bio-inspired Approaches for OFDM Based Cognitive Radio." International Journal of Internet Protocol Technology 12, no. 2 (2019): 1. http://dx.doi.org/10.1504/ijipt.2019.10019368.

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Toroujeni, Seyed Mahdi Mousavi, Seyed Mohammad-Sajad Sadough, and Seyed Ali Ghorashi. "Spectrum Leasing for OFDM-Based Cognitive Radio Networks." IEEE Transactions on Vehicular Technology 62, no. 5 (2013): 2131–39. http://dx.doi.org/10.1109/tvt.2012.2231102.

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Sakran, Hefdhallah, Omar Nasr, and Mona Shokair. "An Efficient Adaptive Technique with Low Complexity for Reducing PAPR in OFDM-Based Cognitive Radio." ISRN Signal Processing 2012 (June 28, 2012): 1–7. http://dx.doi.org/10.5402/2012/584941.

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Cognitive radio (CR) is considered nowadays as a strong candidate solution for the spectrum scarcity problem. On standards level, many cognitive radio standards have chosen Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) as their modulation scheme. Similar to OFDM, NC-OFDM suffers from the problem of having a high Peak to Average Power Ratio (PAPR). If not solved, either the transmitted signal will be distorted, which will cause interference to primary (licensed) users, or the effeciency of the power amplifier will be seriously degraded. The effect of the PAPR problem in NC-OFDM based cognitive radio networks is worse than normal OFDM systems. In this paper, we propose enhanced techniques to reduce the PAPR in NC-OFDM systems. We start by showing that combining two standard PAPR reduction techniques (interleaver-based and selective mapping) results in a lower PAPR than using them individually. Then, an “adaptive number of interleavers” will be proposed that achieves the same performance of conventional interleaver-based PAPR reduction while reducing the CPU time by 41.3%. Finally, adaptive joint interleaver with selective mapping is presented, and we show that it gives the same performance as conventional interleaver-based technique, with reduction in CPU time by a factor of 50.1%.
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Ekin, Sabit, Mohamed M. Abdallah, Khalid A. Qaraqe, and Erchin Serpedin. "Random subcarrier allocation in OFDM-based cognitive radio networks." Qatar Foundation Annual Research Forum Proceedings, no. 2012 (October 2012): CSPS1. http://dx.doi.org/10.5339/qfarf.2012.csps1.

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Zhou, Xiangwei, Geoffrey Ye Li, and Guolin Sun. "Multiuser Spectral Precoding for OFDM-Based Cognitive Radio Systems." IEEE Journal on Selected Areas in Communications 31, no. 3 (2013): 345–52. http://dx.doi.org/10.1109/jsac.2013.130302.

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Ekin, Sabit, Mohamed M. Abdallah, Khalid A. Qaraqe, and Erchin Serpedin. "Random Subcarrier Allocation in OFDM-Based Cognitive Radio Networks." IEEE Transactions on Signal Processing 60, no. 9 (2012): 4758–74. http://dx.doi.org/10.1109/tsp.2012.2203126.

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Razmi, Shirin, and Naser Parhizgar. "Adaptive resources assignment in OFDM-based cognitive radio systems." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (2019): 1935. http://dx.doi.org/10.11591/ijece.v9i3.pp1935-1943.

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Spectrum efficiency of orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems can be improved by adaptive resources allocation. In resources allocation, transmission resources such as modulation level and transmission power are adaptively assigned based on channel variations. The goal of this paper is maximize the total transmission rate of secondary user (SU). Hence, we investigate adaptive power and modulation allocation to achieve this purpose. For power allocation, we investigate optimal and conventional methods and then introduce a novel suboptimal algorithm to calculate the transmission power of each subcarrier. In addition, for adaptive modulation, we consider two kinds of modulations including multi-quadrature amplitude modulation (MQAM) and multi-phase-shift keying (MPSK). Also, simulation results are indicated the performance of our algorithm.
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Bokharaiee, Simin, Ha H. Nguyen, and Ed Shwedyk. "Blind Spectrum Sensing for OFDM-Based Cognitive Radio Systems." IEEE Transactions on Vehicular Technology 60, no. 3 (2011): 858–71. http://dx.doi.org/10.1109/tvt.2010.2103095.

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Dissertations / Theses on the topic "OFDM-based cognitive radio"

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Zhang, Yonghong. "Resource allocation for OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2828.

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Cognitive radio (CR) is a novel wireless communication approach that may alleviate the looming spectrum-shortage crisis. Orthogonal frequency division multiplexing (OFDM) is an attractive modulation candidate for CR systems. In this thesis, we study resource allocation (RA) for OFDM-based CR systems using both aggressive and protective sharing. In aggressive sharing, cognitive radio users (CRUs) can share both non-active and active primary user (PU) bands. We develop a model that describes aggressive sharing, and formulate a corresponding multidimensional knapsack problem (MDKP). Low-complexity suboptimal RA algorithms are proposed for both single and multiple CRU systems. A simplified model is proposed which provides a faster suboptimal solution. Simulation results show that the proposed suboptimal solutions are close to optimal, and that aggressive sharing of the whole band can provide a substantial performance improvement over protective sharing, which makes use of only the non-active PU bands. Although aggressive sharing generally yields a higher spectrum-utilization efficiency than protective sharing, aggressive sharing may not be feasible in some situations. In such cases, sharing only non-active PU bands is more appropriate. When there are no fairness or quality of service (QoS) considerations among CRUs, both theoretical analysis and simulation results show that plain equal power allocation (PEPA) yields similar performance as optimal power allocation in a multiuser OFDM-based CR system. We propose a low-complexity discrete bit PEPA algorithm. To improve spectrum-utilization efficiency, while considering the time-varying nature of the available spectrum as well as the fading characteristics of wireless communication channels and providing QoS provisioning and fairness among users, this thesis introduces the following novel algorithms: (1) a distributed RA algorithm that provides both fairness and efficient spectrum usage for ad hoc systems; (2) a RA algorithm for non-real-time (NRT) services that maintains average user rates proportionally on the downlink of multiuser OFDM-based CR systems; and (3) cross-layer RA algorithms for the downlink of multiuser OFDM-based CR systems for both real-time (RT) services and mixed (RT and NRT) services. Simulation results show that the proposed algorithms provide satisfactory QoS to all supported services and perform better than existing algorithms designed for multiuser OFDM systems.
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Bansal, Gaurav. "Dynamic resource allocation for OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/33275.

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Cognitive radio (CR) is an emerging technology that would improve spectrum utilization by exploiting unused spectrum in dynamically changing environments. We investigate the design of link adaptation algorithms (e.g., adaptive power and bit loading) for orthogonal frequency division multiplexing (OFDM)-based CR systems. Different power and bit loading schemes can be designed for CR users which exploits the time varying nature of fading gains across the OFDM subcarriers. However, one of the challenges here is to ensure that the interference caused to the primary users (PUs) remains below the target interference threshold. Therefore, not only do we need to consider the fading gains, but also the spectral distance of the subcarriers from the PU's band. In this thesis, we propose an optimal power loading algorithm, assuming that the rate can be varied continuously, for an OFDM-based CR system. The downlink transmission capacity of the CR user is thereby maximized, while the interference introduced to the PU remains within a tolerable range. We investigate the case of discrete (or integer) rate adaptation. A sub-optimal scheme for integer bit loading is presented which approximates the optimal continuous rate value to a nearest integer. Next, we propose schemes that maximize the capacity of CR users when only imperfect channel state information (CSI) is available at the CR transmitter while guaranteeing the statistical interference constraint. Further, we propose resource allocation schemes for a multiuser scenario where power is loaded for CR users not only in the subcarriers where PU is not present (overlay fashion) but also in the subcarriers where PU is present (underlay fashion). Finally, for the scenarios where the link between CR source and destination might be weak and not reliable for communication, we employ relays and propose relay and power allocation schemes. Numerical results have been presented for all the proposed algorithms.
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Qin, Tao. "Adaptive resource allocation for multiuser OFDM-based cognitive radio systems." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32229.

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Major challenges in the design of next generation wireless communication systems include harsh propagation environments and scarce resources such as power and spectrum. Cognitive radio (CR) is a promising concept for improving the utilization of scarce radio spectrum resources. Orthogonal frequency division multiplexing (OFDM) is regarded as a technology which is well-matched for CR systems. Dynamic resource allocation is an important task in such systems. In this thesis, a novel fair multiuser resource allocation algorithm for OFDM CR systems is presented. Although not optimal, the algorithm has low computational complexity. The algorithm attempts to maximize the total transmit bit rate (system throughput) of a group of secondary (unlicensed or CR) users subject to (1) a total transmit power constraint for secondary users, (2) a maximum tolerable interference level which can be tolerated by primary (licensed) users. The algorithm is fair in the sense that it tries whenever possible to allocate bits to users who have not received their fair share of service. Simulation results show that the proposed algorithm achieves a performance close to optimal. The effect on system throughput of changing various system parameter values is also examined. A novel cost minimization algorithm for multiuser OFDM cognitive radio systems is also proposed. The objective is to minimize a cost function which takes into account the interference power experienced by the primary user as well as the base station transmit power for secondary users given minimum bit rate requirements for each secondary user. It is found that the proposed algorithm provides a performance which is fairly close to optimal. The influence of a relative weight parameter on the base station (BS) transmit power for secondary users and the primary user interference power is also discussed.<br>Applied Science, Faculty of<br>Electrical and Computer Engineering, Department of<br>Graduate
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Yücek, Tevfik. "Channel, spectrum, and waveform awareness in OFDM-based cognitive radio systems." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002160.

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Yücek, Tevfik. "Channel, spectrum, and waveform awareness in OFDM-based cognitive radio systems." Scholar Commons, 2007. http://scholarcommons.usf.edu/etd/2425.

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The radio spectrum is becoming increasingly congested everyday with emerging technologies and with the increasing number of wireless devices. Considering the limited bandwidth availability, accommodating the demand for higher capacity and data rates is a challenging task, requiring innovative technologies that can offer new ways of exploiting the available radio spectrum. Cognitive radio arises to be a tempting solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Because of its attractive features, orthogonal frequency division multiplexing (OFDM) has been successfully used in numerous wireless standards and technologies. We believe that OFDM will play an important role in realizing the cognitive radio concept as well by providing a proven, scalable, and adaptive technology for air interface. The goal of this dissertation is to identify and address some of the challenges that arise from the introduction of cognitive radio. Specifically, we propose methods for obtaining awareness about channel, spectrum, and waveform in OFDM-based cognitive radio systems in this dissertation. Parameter estimation for enabling adaptation, spectrum sensing, and OFDM system identification are the three main topics discussed. OFDM technique is investigated as a candidate for cognitive radio systems. Cognitive radio features and requirements are discussed in detail, and OFDM's ability to satisfy these requirements is explained. In addition, we identify the challenges that arise from employing OFDM technology in cognitive radio. Algorithms for estimating various channel related parameters are presented. These parameters are vital for enabling adaptive system design, which is a key requirement for cognitive radio. We develop methods for estimating root-mean-square (RMS) delay spread, Doppler spread, and noise variance. The spectrum opportunity and spectrum sensing concepts are re-evaluated by considering different dimensions of the spectrum which is known as multi-dimensional spectrum space. Spectrum sensing problem in a multi-dimensional space is addressed by developing a new sensing algorithm termed as partial match filtering (PMF). Cognitive radios are expected to recognize different wireless networks and have capability of communicating with them. Algorithms for identification of multi-carrier transmissions are developed. Within the same work, methods for blindly detecting transmission parameters of an OFDM based system are developed. Blind detection is also very helpful in reducing system signaling overhead in the case of adaptive transmission where transmission parameters are changed depending on the environmental characteristics or spectrum availability.
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Sohail, Ahmed. "Power allocation in OFDM based cognitive radio systems with arbitrary input distributions." Thesis, University of Surrey, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616476.

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Future demands for higher data-rate services is putting pressure on the current fixed radio spectrum assignment scheme adopted by regulators. The Cognitive Radio (CR) approach is one possible solution to these issues by dynamically assigning spectrum between a Primary User (PU) and Secondary User (SU) and thus sharing spectrum and using it more efficiently. In this thesis we consider various forms of CR (interweave, underlay and joint interweave/underlay) applied to OFDM based radio systems. As conventionally used power allocation of the OFDM modulated SU aims to dynamically control the transmit power on each subcarrier in order to maximize the achievable data rate while protecting the PU from the interference caused by the SUo However, assumptions currently made do not account for practical system considerations e.g., Gaussian input and an interference model that assumes an FDM modulated PU with perfect synchronization with the SU plus a static traffic model. This results in higher optimized power levels and lower SU achievable data rates and thus underestimates usefulness of the system. The thesis addresses these issues by deriving a more general interference model which takes into consideration the more realistic waveforms and imperfect synchronization as well as real traffic models. Based on the interference model, the power optimization problem is formulated under the condition of real (Finite Symbol Alphabet) input as used in practical systems, and evaluates, for the interweave and joint schemes, using single and multiple terminal antennas (SISO and MIMO). The more generalised model shows a saving of transmit power and achieves higher data rates compared to the previous Gaussian approximation. Motivated by the power saving results, a theoretical framework is further established for all cases by evaluating average allocated power for the Gaussian and real waveform model. This theoretical analysis provides guidance for the system design and gives a deeper insight into the choice of parameters affecting power saving and rate improvement. In addition, for given channel statistics, the theoretical analysis can be used to estimate the power saving without running timeconsuming Monte Carlo simulations. Finally, by taking into account more practical scenarios, optimal power and achievable data rate is also evaluated for the case of the dynamic (considering probability of PU arrival and departure) joint scheme. In comparison to the static scheme, the joint scheme protects the PU in case of PU arrivals and yields improved utilization of spectrum when the PU departures are considered.
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Tom, Anas. "Physical Layer Algorithms for Interference Reduction in OFDM-Based Cognitive Radio Systems." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5872.

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Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier transmission scheme used in most of the existing wireless standards such as LTE, WiFi and WiMAX. The popularity of OFDM stems from the multitude of benefits it offers in terms of providing high data rate transmission, robustness against multipath fading and ease of implementation. Additionally, OFDM signals are agile in the sense that any subcarrier can be switched on or off to fit the available transmission bandwidth, which makes it well suited for systems with dynamic spectrum access such as cognitive radio systems. Nonetheless, and despite all the aforementioned advantages, OFDM signals have high spectral sidelobes outside the designated band of transmission, that can create severe interference to users in adjacent transmission bands, particularly when there is no synchronization between users. The focus of this dissertation is to propose baseband solutions at the Physical Layer (PHY) of the communications system to address the interference resulting from the high out-of-band (OOB) emissions of OFDM. In the first part of this dissertation, we propose a precoder capable of generating mask compliant OFDM signals with low OOB emissions that are always contained under a given spectrum emission mask (SEM) specified by the OFDM standard. The proposed precoder generates transmitted signals with bit error rate (BER) performance similar to that of classical OFDM and does not reduce the spectral efficiency of the system. In the second part of this dissertation, we introduce a novel and elegant approach, called suppressing alignment (SA), to jointly reduce the OOB interference and peak-to-average power ratio (PAPR) of OFDM systems. SA exploits the unavoidable redundancy provided by the CP as well as the wireless communications channel to generate an OOB/PAPR suppressing signal at the OFDM transmitter. Furthermore, after passing through the wireless channel, the suppressing signal is aligned with the CP duration at the OFDM receiver, essentially causing no interference to the data portion of the OFDM symbol. The proposed approach improves the PAPR of the transmitted OFDM signal and reduces the OOB interference by tens of decibels. Additionally, the proposed approach maintains an error performance similar to that of plain OFDM without requiring any change in the receiver structure of legacy OFDM. In order to reduce the spectral emissions of OFDM, additional blocks, such as linear precoders, are usually introduced in the transmitter leading to a transmitted signal that is drastically different than that of a classical OFDM signal. This distortion is typically quantified by the error vector magnitude (EVM), a widely used metric specified by the wireless standard and is directly related to the BER performance of the system. The receiver can usually decode the information data with acceptable error probabilities if the distortion introduced to the transmitted signal is below the EVM values specified in the OFDM standard. Linear precoders, while capable of achieving significant reduction in the OOB interference, they typically introduce large distortion to the transmitted signal. As such, the receiver needs to know the precoding done at the transmitter to be able to recover the data which usually entails sending large amount of side information that can greatly reduce the spectral efficiency of the system. In the last part of this dissertation, we target the design of precoders for the purpose reducing the OOB interference, in a transparent manner where the receiver does not need to know the changes introduced in the transmitter. We present two precoders capable of significantly reducing the OOB emissions while producing transmitted signals with EVM values below those specified by the wireless standard, thereby guaranteeing acceptable error performance.
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Zhong, Bo. "Cross-layer QoE improvement with dynamic spectrum allocation in OFDM-based cognitive radio." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/9103.

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Rapid development of devices and applications results in dramatic growth of wireless traffic, which leads to increasing demand on wireless spectrum resources. Current spectrum resource allocation policy causes low efficiency in licensed spectrum bands. Cognitive Radio techniques are a promising solution to the problem of spectrum scarcity and low spectrum utilisation. Especially, OFDM based Cognitive Radio has received much research interest due to its flexibility in enabling dynamic resource allocation. Extensive research has shown how to optimise Cognitive Radio networks in many ways, but there has been little consideration of the real-time packet level performance of the network. In such a situation, the Quality of Service metrics of the Secondary Network are difficult to guarantee due to fluctuating resource availability; nevertheless QoS metric evaluation is actually a very important factor for the success of Cognitive Radio. Quality of Experience is also gaining interest due to its focus on the users' perceived quality, and this opens up a new perspective on evaluating and improving wireless networks performance. The main contributions of this thesis include: it focuses on the real-time packet level QoS (packet delay and loss) performance of Cognitive Radio networks, and evaluates the effects on QoS of several typical non-configurable factors including secondary user service types, primary user activity patterns and user distance from base station. Furthermore, the evaluation results are unified and represented using QoE through existing mapping techniques. Based on the QoE evaluation, a novel cross layer RA scheme is proposed to dynamically compensate user experience, and this is shown to significantly improve QoE in scenarios where traditional RA schemes fail to provide good user experience.
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Yuan, Zhou. "Sidelobe suppression and agile transmission techniques for multicarrier-based cognitive radio systems." Worcester, Mass. : Worcester Polytechnic Institute, 2009. http://www.wpi.edu/Pubs/ETD/Available/etd-050309-163215/.

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Zhang, Haijian. "Filter Bank based MultiCarrier (FBMC) for Cognitive Radio Systems." Thesis, Paris, CNAM, 2010. http://www.theses.fr/2010CNAM0763/document.

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La radio cognitive (CR) est une radio entièrement reconfigurable qui permet de changer intelligemment ses paramètres de communication en réponse à l’activité des autres réseaux radios et demandes d’utilisateur. L’objectif ultime de la CR est de permettre à l’utilisateur secondaire (SU) d’utiliser la ressource de spectre disponible sans interférer sur l’utilisateur primaire (PU) en utilisant des trous de spectre. Par conséquent, la détection du PU est l’un des défis principaux dans le développement de la CR. Par rapport aux systèmes conventionnels de communication sans fil, le système CR introduit de nouveaux problèmes d’allocation de ressource (RA) en raison de l’interférence des canaux adjacents utilisés par le SU et le PU. Dans le contexte de la CR, la plupart des efforts ont été menés sur les systèmes de CR basés sur le multiplexage par division de fréquences orthogonales (OFDM). Toutefois, la technique de l’OFDM montre quelques points faibles dans l’application à cause des remontées significatives du spectre. Les modulations multiporteuses à base de bancs de filtre (FBMC) ont été récemment proposées pour des applications de CR. Dans cette thèse, trois points importants pour le développement d’un système de CR basé sur le FBMC sont discutés.Les trois points principaux peuvent être résumés ainsi: nous examinons premièrement les problèmes de détection de spectre des signaux OFDM et FBMC en employant le détecteur de signature de cyclostationnarité (CS). En outre, nous proposons une architecture de détection multi-bande basée sur le banc de filtre polyphasé (PFB), et montrons son avantage; deuxièmement, la comparaison entre l’OFDM et le FBMC du point de vue de l’efficacité spectrale est discutée; et enfin, nous proposons un algorithme stratégique d’allocation de ressource pour les systèmes cognitifs multi-cellulaires et multi-utilisateurs.Les algorithmes proposés dans cette thèse ont été testés par simulation. Les résultats numériques prouvent que le FBMC, par opposition à l’OFDM, pourrait réaliser une efficacité spectrale plus élevée et offre un avantage attrayant dans la détection de spectre. Les contributions de cette thèse ont accru l’intérêt d’appliquer FBMC dans les systèmes de CR à l’avenir<br>Cognitive Radio (CR) is a fully reconfigurable radio that can intelligently change its communicationvariables in response to network and user demands. The ultimate goal of CR is to allowthe Secondary User (SU) to utilize the available spectrum resource on a non-interfering basis to thePrimary User (PU) by sensing the existence of spectrum holes. Therefore, the detection of PU isone of the main challenges in the development of the CR technology. Moreover, compared to conventionalwireless communication systems, CR system poses new challenges to Resource Allocation(RA) problems because of the Cross-Channel Interference (CCI) from the adjacent channels used bySU to PU. In the CR context, most past efforts have been spent on Orthogonal Frequency DivisionMultiplexing (OFDM) based CR systems. However, OFDM technique exhibits some shortcomingsin application due to its significant spectrum leakage. Filter Bank based Multi-Carrier (FBMC), asanother promising Multi-Carrier Modulation (MCM) candidate, has been recently proposed for CRapplications. In this dissertation, three important issues in developing a FBMC based CR system arediscussed.The three prime issues can be summarized: we firstly survey the spectrum sensing problemsof OFDM and FBMC signals by using Cyclostationary Signature (CS) detector. Furthermore, wepropose a Polyphase Filter Bank (PFB) based multi-band sensing architecture, and argue for its advantage;secondly, the comparison of OFDM and FBMC from the spectral efficiency point of viewis discussed; and lastly, our emphasis is placed on the strategic resource allocation algorithms fornon-cooperative multi-cell CR systems.The overall proposed algorithms have been verified by simulation. Numerical results show thatFBMC, as opposed to OFDM, could achieve higher spectrum efficiency and attractive benefit inspectrum sensing. The contributions of this dissertation have heighten the interest in applying FBMCin the future CR systems
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Books on the topic "OFDM-based cognitive radio"

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RF analog impairments modeling for communication systems simulation: Application to OFDM-based transceivers. Wiley, 2012.

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Book chapters on the topic "OFDM-based cognitive radio"

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Shamani, Farid, Tapani Ahonen, and Jari Nurmi. "Synchronization in NC-OFDM-Based Cognitive Radio Platforms." In Computing Platforms for Software-Defined Radio. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49679-5_10.

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Maherin, Ishrat, and Qilian Liang. "Power Allocation in OFDM Based Cognitive Radio System." In Lecture Notes in Electrical Engineering. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5803-6_14.

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Deepa, R., and K. Baskaran. "MIMO-OFDM Based Cognitive Radio for Modulation Recognition." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17878-8_35.

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Fernando, Xavier, Ajmery Sultana, Sattar Hussain, and Lian Zhao. "Resource Allocation in OFDM-Based Cognitive Radio Systems." In SpringerBriefs in Electrical and Computer Engineering. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73957-1_4.

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Yun, Liu, Qicong Peng, Fuchun Sun, Huaizong Shao, Xingfeng Chen, and Ling Wang. "A Novel Spectrum Sensing Algorithm in Cognitive Radio System Based on OFDM." In Advances in Intelligent Systems and Computing. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37835-5_12.

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Jia, Min, Hao Yang, and Xuemai Gu. "Improved Energy Detection Spectrum Sensing Method for OFDM-Based Cognitive Radio System." In Lecture Notes in Electrical Engineering. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5803-6_13.

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Vijayakumar, P., Jeswin George, S. Malarvizhi, and A. Sriram. "Analysis and Implementation of Reliable Spectrum Sensing in OFDM Based Cognitive Radio." In Smart Computing and Informatics. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5544-7_55.

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Krishnan, Kishore V., A. Bagubali, and Sibaram Khara. "Dynamic Resource Allocation in OFDM-Based Cognitive Radio System Based on Estimated Channel Information." In Proceedings of the International Conference on Soft Computing Systems. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2671-0_90.

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Savaux, Vincent, and Yves Louët. "Application of the Algorithm as a Detector for Cognitive Radio Systems." In MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119005087.ch3.

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Yan, Shuangcheng, Pinyi Ren, and Yu Hong. "Joint Subcarrier and Power Allocation Considering Fairness in OFDM-Based Cognitive Radio Systems." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30493-4_5.

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Conference papers on the topic "OFDM-based cognitive radio"

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Bokharaiee, Simin, Ha H. Nguyen, and Ed Shwedyk. "Spectrum Sensing for OFDM-Based Cognitive Radio." In 2010 IEEE Vehicular Technology Conference (VTC 2010-Fall). IEEE, 2010. http://dx.doi.org/10.1109/vetecf.2010.5594273.

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Xu, Yihu, DaeHwan Kim, SangHak Lee, and Myong-Seob Lim. "Split-radix FFT pruning for OFDM based Cognitive Radio system." In 2009 9th International Symposium on Communications and Information Technology (ISCIT). IEEE, 2009. http://dx.doi.org/10.1109/iscit.2009.5341214.

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Mahmoud, Hisham A., and Huseyin Arslan. "Spectrum shaping of OFDM-based cognitive radio signals." In 2008 IEEE Radio and Wireless Symposium. IEEE, 2008. http://dx.doi.org/10.1109/rws.2008.4463441.

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Sokhandan, Negin, and Seyed Mostafa Safavi. "Sidelobe Suppression in OFDM-based cognitive radio systems." In 2010 10th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA). IEEE, 2010. http://dx.doi.org/10.1109/isspa.2010.5605455.

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Kyryk, Maryan, and Volodymyr Yanyshyn. "OFDM-based cognitive radio system capacity evaluation model." In 2015 13th International Conference on the Experience of Designing and Application of CAD Systems in Microelectronics (CADSM). IEEE, 2015. http://dx.doi.org/10.1109/cadsm.2015.7230818.

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Wang, Peng, Ming Zhao, Limin Xiao, Shidong Zhou, and Jing Wang. "Power Allocation in OFDM-Based Cognitive Radio Systems." In IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference. IEEE, 2007. http://dx.doi.org/10.1109/glocom.2007.772.

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Parekh, Pratik R., and Mehul B. Shah. "Spectrum sensing in wideband OFDM based Cognitive Radio." In 2014 International Conference on Communications and Signal Processing (ICCSP). IEEE, 2014. http://dx.doi.org/10.1109/iccsp.2014.6950094.

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Marutham M and L. Nandita. "Performance improvement of OFDM-based Cognitive Radio system." In 2015 International Conference on Communications and Signal Processing (ICCSP). IEEE, 2015. http://dx.doi.org/10.1109/iccsp.2015.7322793.

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Alnwaimi, Ghassan, Kamran Arshad, and Klaus Moessner. "Collaborative spectrum sensing in OFDM-based Cognitive Radio." In 2009 First UK-India International Workshop on Cognitive Wireless Systems (UKIWCWS 2009). IEEE, 2009. http://dx.doi.org/10.1109/ukiwcws.2009.5749395.

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Fu, Xiao, Jun Wang, and Shao Qian Li. "Sidelobe suppression for OFDM based cognitive radio systems." In 2009 Fourth International Conference on Communications and Networking in China (CHINACOM). IEEE, 2009. http://dx.doi.org/10.1109/chinacom.2009.5339744.

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