Spectrum Sensing

"James Joyce, as a postcolonial Irishman, understands the connection between Ireland and the Orient . In his texts, his characters often contemplate the Orient while numbly living out their routines in Ireland, but Joyce’s Irish Oriental aesthetic goes far beyond his characters’ small mindedness and paralysis. My intent in this paper is to discover how Joyce interacts with the commonly understood category of Irish Orientalism through his texts, characters, and styles of writing. I begin my argument by defining Irish Orientalism in the context of Orientalism and history. Next, I analyze select elements of “Araby” from Dubliners and “Lotus Eaters” from Ulysses, demonstrating how they either confirm or subvert traditional conceptions of Irish Orientalism. I conclude my essay with a contemplation of other critics’ views on Joyce’s Irish Oriental aesthetic and establish my own argument in light of my close readings of the texts “Araby” and “Lotus Eaters.” I propose that Joyce neither fully confirms nor subverts the concept of Irish Orientalism; ultimately, I argue that Joyce’s works promote a new vision of Irish Orientalism that is organic and transformative and that demonstrates bravely how a postcolonial entity like Ireland (or the Orient) can begin to recreate its own identity separate from imperialism."

This report focuses on the Access network implementation of a 5G small-cell communication system using Cognitive Radio. 5G systems are the next major wireless communications standard and Cognitive Radio is being heralded as a valid implementation method when the wireless communications industry finally concludes on a fifth generation standard. The project is concerned with implementing a Beyond-Next-Generation (5G) communications network based on Cognitive Radio. A functioning model is developed in matlab, the purpose of which is to show that Cognitive Radio based 5G systems will give acceptable Quality-of-Service and energy efficiency levels.
The Access network implementation of the system involves channel assignment for the access links which provide network access to mobile subscribers. Suitable channels to service call requests are determined based on cognition.
The system performance is evaluated by estimating the system blocking and dropping probabilities and the percentage of energy saved.

The increasing demand of wireless applications has put a lot of limitations on the use of available radio spectrum is limited and precious resource. Many survey of spectrum utilization shows that entire spectrum is not used at all the times, so many of the radio spectrum is underutilized. Some of the frequency bands in the spectrum are unoccupied, some of the frequency bands less occupied and few bands are over utilized. Cognitive radio system is a technique which overcomes that spectrum underutilization. Cognitive radio is a technique where secondary user looks for a free band to use when primary user is not in use of its licensed band. A function of cognitive radio is called Spectrum sensing which enables to search for the free bands and it helps to detect the spectrum hole (frequency band which is free enough to be used) which can be utilized by secondary user with high spectral resolution capability. The idea of simulation and analysis of Cognitive Radio System to reuse unused spectrum to increase the total system capacity was brought in this paper and this work digs into the practical implementation of a Cognitive radio system. MATLAB R2007b (version7.5) has been used to test the performance of Cognitive radio dynamically

The localization algorithm based on the doublethresholding (LAD) method was originally proposed for detecting and localizing narrowband (NB) signals with respect to the search bandwidth. Its weakness is that the localized signal is often split into several parts, especially when the signal-to-noise ratio (SNR) is low. This may lead to the illusion of unoccupied frequencies in the middle of the signals. In this paper, an extension of the LAD method, namely the two-dimensional LAD (2-D LAD), is proposed to solve that problem. In addition to offering low computational complexity, the proposed method is able to operate at lower SNR values than the original 1-D LAD method.

Cognitive Radio plays a major part in communication technology by resolving the shortage of the spectrum through usage of dynamic spectrum access and artificial intelligence characteristics. The element of spectrum sharing in cognitive radio is a fundamental approach in utilising free channels. Cooperatively communicating cognitive radio devices use the common control channel of the cognitive radio medium access control to achieve spectrum sharing. Thus, the common control channel and consequently spectrum sharing security are vital to ensuring security in the subsequent data communication among cognitive radio nodes. In addition to well known security problems in wireless networks, cognitive radio networks introduce new classes of security threats and challenges, such as licensed user emulation attacks in spectrum sensing and misbehaviours in the common control channel transactions, which degrade the overall network operation and performance. This review paper briefly presents the known threats and attacks in wireless networks before it looks into the concept of cognitive radio and its main functionality. The paper then mainly focuses on spectrum sharing security and its related challenges. Since spectrum sharing is enabled through usage of the common control channel, more attention is paid to the security of the common control channel by looking into its security threats as well as protection and detection mechanisms. Finally, the pros and cons as well as the comparisons of different CR-specific security mechanisms are presented with some open research issues and challenges.

The IEEE is developing a standard for cognitive wireless regional area networks operating in unused television channels. One of the cognitive features of this standard is spectrum sensing, which is used to identify unused television channels. This paper describes the requirements for spectrum sensing and the spectrum sensing framework. A description is given of the method used for evaluating specific spectrum sensing techniques. Finally, the paper provides a survey of the spectrum sensing techniques that are included in the draft standard.

Recent years have shown a growing interest in the concept of Cognitive Radios (CRs), able to access portions of the electromagnetic spectrum in an opportunistic operating way. Such systems require efficient detectors able to work in low Signal-to-Noise Ratio (SNR) environments, with little or no information about the signals they are trying to detect. Energy detectors are widely used to perform such blind detection tasks, but quickly reach the so-called SNR wall below which detection becomes impossible Tandra (2005). Cyclostationarity detectors are an interesting alternative to energy detectors, as they exploit hidden periodicities present in man-made signals, but absent in noise. Such detectors use quadratic transformations of the signals to extract the hidden sinewaves. While most of the literature focuses on the second-order transformations of the signals, we investigate the potential of higher-order transformations of the signals. Using the theory of Higher-Order Cyclostationarity (HOCS), we derive a fourthorder detector that performs similarly to the second-order ones to detect linearly modulated signals, at SNR around 0 dB, which may be used if the signals of interest do not exhibit second-order cyclostationarity. More generally this paper reviews the relevant aspects of the cyclostationary and HOCS theory, and shows their potential for spectrum sensing.

Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum's utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the stateof-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and reporting, user selection, and knowledge base. Moreover, the impacting factors of achievable cooperative gain and incurred cooperation overhead are presented. The factors under consideration include sensing time and delay, channel impairments, energy efficiency, cooperation efficiency, mobility, security, and wideband sensing issues. The open research challenges related to each issue in cooperative sensing are also discussed.

TVWS represent an alternative to various problems, such as spectrum scarcity; The challenge of connecting to remote locations or even the deployment of community networks through the use of portions of unused spectrum. TVWS are spaces that have been left unoccupied by the transition from analogue to digital television or simply because in some regions television operators do not see a return on investment and as a consequence these frequencies are available for use; However in order to declare them as underutilized space, a technical verification of the spectrum must be carried out. I made a census of the electromagnetic spectrum of 300 MHz to 900 MHz, belonging to the band Ultra High Frequency (UHF), that was realized with low cost measurement devices so that these measurements are replicable, in developing countries, which lack of the costly technology generally required to perform such censuses. A measurement framework based on this experience and previous experiences is constructed, taking a census of the spectrum with different low cost devices that show that it is possible to carry out an organized and structured census of a portion of the spectrum that serves as a valid source of the state of the art, and therefore a valid source for the justification of the use of these frequencies in function of the deployment of community networks or cognitive radio.

The increasing demand of wireless applications has put a lot of limitations on the use of available radio spectrum is limited and precious resource. Many survey of spectrum utilization shows that entire spectrum is not used at all the times, so many of the radio spectrum is underutilized. Some of the frequency bands in the spectrum are unoccupied, some of the frequency bands less occupied and few bands are over utilized. Cognitive radio system is a technique which overcomes that spectrum underutilization. Cognitive radio is a technique where secondary user looks for a free band to use when primary user is not in use of its licensed band. A function of cognitive radio is called Spectrum sensing which enables to search for the free bands and it helps to detect the spectrum hole (frequency band which is free enough to be used) which can be utilized by secondary user with high spectral resolution capability. The idea of simulation and analysis of Cognitive Radio System to reuse unused spectrum to increase the total system capacity was brought in this paper and this work  digs into the practical implementation of a Cognitive radio system.MATLAB R20 07b (version7.5) has been used to test the performance of Cognitive radio dynamically

Cognitive radio wireless networks are an emerging communication paradigm to effectively address spectrum scarcity challenge. Spectrum sensing plays a paramount role in cognitive radio, which is widely agreed to be the most promising method for alleviating the symptom of RF spectral scarcity. Dynamic access of unused spectrum via a cognitive radio asks for flexible radio circuits that can work at an arbitrary radio frequency. In this paper, we analyze the performance of spectrum sensing on GNU Radio system with USRP. We investigating spectrum scarcity and proposed the algorithm that performed and measuring the energy of Rx signal in a fixed bandwidth, W, over an observation time window, T. The results presented that it can detected of primary user signal over the fixed bandwidth which occupied the spectrum.

The cognitive radio system is proposed as an optimal way to improve the frequency underutilization. Spectrum sensing is the first and the essential function in this approach. A cognitive user must sense his environment to detect the unused channels, and then he can use the free channel without causing any interference to the primary user. In this article, an innovative technique is proposed for spectrum sensing based on principal component analysis and neural networks in frequency domain. The designed blocks are described using VHSIC Hardware Description Language (VHDL). The suggested application consists of extracting features from the captured signals by PCA; the classification is done by a Multi-Layer Perceptron (MLP). Neural network training part and principal components are done on MATLAB environment; while the hardware implementations are created on an FPGA DE2-70board.

In emerging cognitive radio (CR) networks, the first cognitive task preceding any dynamic spectrum management is the sensing and identification of spectrum holes in wireless environments. This paper develops a distributed compressed spectrum sensing approach for (ultra-)wideband CR networks. First, compressive sampling is performed at local CRs to scan the very wide spectrum at practical signal-acquisition complexity. Then, measurements or states from multiple CR detectors are fused to collect spatial diversity gain, which improves the detection quality especially under fading channels. Distributed fusion algorithms are derived to effect collaborative fusion at low communication and computation load scalable to the network size. Multiple performance metrics are identified to evaluate the proposed spectrum sensing techniques, as well as to assess those performance-determining factors in system design. Computer simulations corroborate the effectiveness of the proposed techniques in id...

Spectrum sensing is a fundamental component is a cognitive radio. In this paper, we propose new sensing methods based on the eigenvalues of the covariance matrix of signals received at the secondary users. In particular, two sensing algorithms are suggested, one is based on the ratio of the maximum eigenvalue to minimum eigenvalue; the other is based on the ratio of the average eigenvalue to minimum eigenvalue. Using some latest random matrix theories (RMT), we quantify the distributions of these ratios and derive the probabilities of false alarm and probabilities of detection for the proposed algorithms. We also find the thresholds of the methods for a given probability of false alarm. The proposed methods overcome the noise uncertainty problem, and can even perform better than the ideal energy detection when the signals to be detected are highly correlated. The methods can be used for various signal detection applications without requiring the knowledge of signal, channel and noise power. Simulations based on randomly generated signals, wireless microphone signals and captured ATSC DTV signals are presented to verify the effectiveness of the proposed methods.

Los espacios en blanco de televisión representan una alternativa a diversos problemas, tales como, la escasez de espectro; el reto de llevar conexión a lugares remotos y la potencial saturación de los operadores de telefonía móvil impulsa a utilizar estos espacios para aliviar cada uno de estos problemas. Los espacios en blanco de televisión son espacios que han quedado desocupados debido a la transición de la televisión analógica a la digital o simplemente porque en ciertas regiones los operadores de televisión no ven un retorno de inversión y en consecuencia estas frecuencias están disponibles para su uso.
En este trabajo de grado se realizó un censo del espectro electromagnético de 300 MHz a 900 MHz, pertenecientes a la banda Ultra High Frequency (UHF), con dispositivos de medición de bajo costo de manera que estas mediciones sean replicables, en países en vías de desarrollo, que carecen de la costosa tecnología generalmente requerida para realizar dichos censos. De igual manera, se construye un marco de medición basado en esta experiencia y experiencias previas. Se obtiene entonces un censo del espectro con diferentes dispositivos de bajo costo que demuestran que es posible realizar un censado organizado y estructurado de una porción del espectro que sirva como una fuente valida del estado del mismo.

Fruit peel coloring is one of the most important measures of commercial values in various citrus fruits. It is well documented that a gaseous plant hormone, ethylene, regulates the peel color changes associated with fruit ripening. To handle the peel color quality, it is necessary to develop a universal measure of ethylene-directed color changes. Here, we proposed a novel colorimetric formula: y* = [ (L* n • max-L* t) 2 + (a* n • max-a* t) 2 + (b* n • max-b* t) 2 ] 1/2 (y* > 0), based the CIE 1976 L*a*b* colour space units, which reflect the wholistic changes in fruit color. Since all known colorimetric values are specialized for estimation of the changes in certain single pigment, our formula may be useful for assessing the total fruit color development in a controlled atmosphere.

In this paper, we consider the problem of spectrum sensing in cognitive radio, where unlicensed (secondary) users are allowed to share the vacant frequency bands from the licensed (primary) users. We propose two cooperation protocols to improve the detection probability compared to an existing protocol. In the first protocol, secondary users with higher detection probability constantly act as relays to help those with lower detection probability, while in the second protocol, the help-oriented users choose to relay signals according to the decision made during the first time slot. Analytical studies are provided to demonstrate the enhanced performance of our proposed protocols. Finally, simulation examples are presented to corroborate our analytical results.

Cognitive radio is an enabling technology that allows opportunistic users to reuse licensed spectrum in order to overcome the artificial spectrum scarcity. In cognitive radio networks, opportunistic users collaboratively perform spectrum sensing to detect the presence of incumbent users. Collaborative Spectrum Sensing (CSS) performance suffers due to the presence of malicious users. We propose a robust malicious user detection algorithm which exploits inherent statistical moments of the sensing observations from collaborating users to identify malicious users among them. In this way, CSS performance is improved by detecting and marginalizing the effects of malicious users.

| Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum. Such revolutionary and transforming technology represents a paradigm shift in the design of wireless systems, as it will allow the agile and efficient utilization of the radio spectrum by offering distributed terminals or radio cells the ability of radio sensing, self-adaptation, and dynamic spectrum sharing. Cooperative communications and networking is another new communication technology paradigm that allows distributed terminals in a wireless network to collaborate through some distributed transmission or signal processing so as to realize a new form of space diversity to combat the detrimental effects of fading channels. In this paper, we consider the application of these technologies to spectrum sensing and spectrum sharing. One of the most important challenges for cognitive radio systems is to identify the presence of primary (licensed) users over a wide range of spectrum at a particular time and specific geographic location. We consider the use of cooperative spectrum sensing in cognitive radio systems to enhance the reliability of detecting primary users. We shall describe spectrum sensing for cognitive radios and propose robust cooperative spectrum sensing techniques for a practical framework employing cognitive radios. We also investigate cooperative communications for spectrum sharing in a cognitive wireless relay network. To exploit the maximum spectrum opportunities, we present a cognitive space-time-frequency coding technique that can opportunistically adjust its coding structure by adapting itself to the dynamic spectrum environment.

For the purpose of enhancing the spectrum efficiency, cognitive radio (CR) technology has been recently proposed as a promising dynamic spectrum allocation paradigm. In CR, spectrum sensing is the key capability of secondary users in a cognitive radio network that aims for reducing the probability of harmful interference with primary users. However, the individual CRs might not be able to carry out reliable detection of the presence of a primary radio due to the impact of channel fading or shadowing. This paper studies the cooperative spectrum sensing scheme as means of optimizing the sensing performance in AWGN and Rayleigh channels. Results generated from simulation provide evidence of the impact of channel condition on the complementary receiver operating characteristic (ROC). Based on the results, it was found that with constant local SNRs at the secondary users, the probability of missed detection (P m ) of cooperative spectrum sensing in a cognitive radio network, calculated using a closed form expression, can be significantly minimized. Thus, the paper illustrates that improvement of the detection performance of the CR network can be achieved by establishing a centralized cooperation among neighboring cognitive radio users. Finally, verification of the validity of the fusion schemes utilized for combining the individual CR decisions is provided.

    In this paper, signal detection methods for spectrum sensing in IEEE 802.22 wireless RAN systems are discussed. As most of the manmade signals can be treated as cyclostationary random process, the spectral correlation function is effective for detecting of these signals. In WRAN systems, due to the specific detection environment, the computational complexity of the spectral correlation based method is significantly reduced. Peak detection in the high SNR environment together with contour figure based unique patterns search method in the low SNR environment are proposed for the primary user signal detection.

Spectrum sensing for cognitive radio is challenging. In this letter, a spectrum sensing method based on quintiles of Order-Statistics is proposed. We derive the test statistic and evaluate the performance of the proposed method by Monte Carlo simulations. Simulation results show that order statistics based sensing considerably outperforms both energy detection and anderson darling based sensing in an Additive White Gaussian Noise (AWGN) channel; especially in a lower signal to noise ratio region.

Despite its practical performance limitations, energy detection has gained popularity during the last years as a spectrum sensing technique for dynamic spectrum access in cognitive radio networks. The main advantages of energy detectionbased spectrum sensing are its simplicity, low computational and implementation costs as well as its ability to work irrespective of the actual signal to be detected. Since no prior knowledge is required, energy detection can be employed when the secondary receiver cannot gather sufficient information about the primary user signal. Due to the generality of its operating principle, the energy detector performance would not be expected to depend on the type of primary signal being detected. In this context, this paper evaluates the performance of energy detectionbased spectrum sensing for several real-world primary signals of various radio technologies. The obtained results indicate that the detection performances may vary notably with the considered primary signal but converge under certain conditions. The practical consequences of the different observed performances for several primary radio technologies are illustrated and discussed.

Limited spectrum resources and dramatic growth of high data rate applications have motivated opportunistic spectrum access utilizing the promising concept of cognitive networks. Although this concept has emerged primarily to enhance spectrum utilization and to allow the coexistence of heterogeneous network technologies, the importance of energy consumption imposes additional challenges, because energy consumption and communication performance can be at odds. In this paper, the approaches for energy efficient spectrum sensing and spectrum handoff, fundamental building blocks of cognitive networks is investigated. The tradeoff between energy consumption and throughput, under local as well as under cooperative sensing are characterized, and what further aspects need to be investigated to achieve energy efficient cognitive operation under various application requirements are discussed.

Ultrawideband and cognitive radio are two of the most important approaches that are shaping the future of wireless communication systems. At a first glance, the aims of UWB and cognitive radio do not seem to be overlapping significantly, however, there is a strong synergy between the capabilities of UWB and the goals of cognitive radio. One of the objectives of

Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum's utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the stateof-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and reporting, user selection, and knowledge base. Moreover, the impacting factors of achievable cooperative gain and incurred cooperation overhead are presented. The factors under consideration include sensing time and delay, channel impairments, energy efficiency, cooperation efficiency, mobility, security, and wideband sensing issues. The open research challenges related to each issue in cooperative sensing are also discussed.

This report reviews Cognitive Radio technology starting from when the term Cognitive Radio was coined by Dr Joseph Mitola in the late 90s. Basic concepts about CR technology as well as different features of CR alongside principles behind CR more importantly from the cognitive cycle perspective were discussed in this report. Certain applications and test-beds across the United States and Europe like CORNET and ORBIT were identified. Several emerging research topics which could lead to major innovative CR approach were also discussed before giving a personal opinion on when CR technology is likely to be widely used.

Wireless technology is expanding its domain and with it is growing the need for more frequencies for communication. Cognitive radio offers a solution to this problem by using the concept of Dynamic spectrum access instead of fixed spectrum allocation. Such radios are capable of sensing the RF spectrum for identifying idle frequency bands. It then transmits opportunistically so as to avoid interference with primary user over same band. In cognitive radio, intelligent spectrum sensing forms the major and most important part. Out of the various sensing techniques, we will give an overview of some of the prominent non-cooperative techniques. The paper deals with comparative study of these methods.

The need for Digital Transmission has been on the increase over the years. Spectrums are basically a range of electromagnetic waves for digital transmission. Digital Transmission has poised great economic benefits to Networks Transmission Industries. However, with the wide spread demand for networks transmission, appropriate supervision of utilization and management is adequately required. A key component of the study is based on the input from the operational regions, industry stakeholders and Government Commissions. The study observed that, digital transmission has helped in managing the rate at which available spectrums are been utilized. Indeed, it takes 8MHz (Eight Mega Hertz) of Spectrum to carry a single Analogue Transmission, but with, Digital Transmission, it take the same 8MHz (Eight Mega Hertz) of Spectrum to carry as much as 20 (twenty) Digital Transmissions. This research work focused on providing solution to the need for a proper Analysis of Digital Spectrum Utilization. The concept of a Fuzzy Set, and a robust analytic tool (MATLAB) was used as the analytic system model for a more scientific and feasible solution to sensitivity analysis and spectrum utilization. The system was developed and evaluated using a scientific field data obtained from Nigerian Television Authority (NTA) Jos, for analysis purpose. Results obtained from the analysis shows that the use of Spectrum for Digital Transmission in Nigeria (Jos) has periodically increased, however not up to 50% (fifty per cent) were in use as at the end of December 2016. Recent concerns for conversion of Analogue Transmission to Digital are expected to bring about significant increase to Spectrum Utilization in Nigeria.

Spectrum sensing is a key function of cognitive radio to prevent the harmful interference with licensed users and identify the available spectrum for improving the spectrum's utilization. However, detection performance in practice is often compromised with multipath fading, shadowing and receiver uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. While cooperative gain such as improved detection performance and relaxed sensitivity requirement can be obtained, cooperative sensing can incur cooperation overhead. The overhead refers to any extra sensing time, delay, energy, and operations devoted to cooperative sensing and any performance degradation caused by cooperative sensing. In this paper, the stateof-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead. Specifically, the cooperation method is analyzed by the fundamental components called the elements of cooperative sensing, including cooperation models, sensing techniques, hypothesis testing, data fusion, control channel and reporting, user selection, and knowledge base. Moreover, the impacting factors of achievable cooperative gain and incurred cooperation overhead are presented. The factors under consideration include sensing time and delay, channel impairments, energy efficiency, cooperation efficiency, mobility, security, and wideband sensing issues. The open research challenges related to each issue in cooperative sensing are also discussed.

The assignment policy of frequency spectrum which is limited, is implemented as a constant in today's wireless communications. Increasing number of users with the rapidly developing wireless technologies also increases the frequency spectrum demand. Therefore, allocation of frequency bands in the spectrum to the users as fixed causes inefficient use of the frequency spectrum. To overcome this problem, cognitive radio concept is emerged. This concept described as intelligent radio enables the current spectrum band to be used efficiently and actively. Cognitive radio detects whether or not there is any licensed (primary) users around, by sensing the full spectrum band continuously. It assigns the spectrum bands unused by primary users to unlicensed (secondary) users. To prevent interference, it empties that spectrum when the primary users start to use their own spectrum bands, or it reduces transmission power to a level that cannot communicate. Spectrum sensing which is one of the major components used to improve cognitive radio spectrum efficiency scans all licensed users and unused frequency spectrum continuously. In this study, spectrum availability is determined according to the detected energy level using Energy Detection Based Spectrum Sensing which is one of the spectrum sensing techniques. The effects of Probability of detection (Pd), Probability of false alarm (Pf), Probability of missed detection (Pm) and Signal to Noise Ratio (SNR) value to each other are analyzed. Simulation results shows that the probability of detection increases significantly when signal to noise ratio increases.

In this paper we present a time divisional and a time-frequency divisional cooperative spectrum sensing technique suitable for cognitive radio (CR) networks. The two methods are well suited for very high bandwidth CR networks, such as UWB networks, where the individual nodes need to scan a wide range of spectrum which is a time consuming process. With the time divisional and the time-frequency divisional cooperative spectrum sensing approaches the nodes share the spectrum sensing functions cooperatively, coordinating in time and frequency, covering the total frequency band and also in near-continuous time. In this paper we present the corresponding algorithms and techniques for the two cooperative spectrum sensing approaches, analyze their performances, and compare the advantages and disadvantages with each other. We also present simulation results to verify the performance improvements in terms of probability of miss detection and the probability of false alarm for detecting the PU. Results show that the the proposed methods are best suited for detecting the PUs having low spectral occupancy statistics who occupy the spectrum very seldom.

Frequency spectrum is the scarcest resource for wireless communication. The FCC has stated that there are some frequency bands that are underutilized. Hence the frequency spectrum is not scarce but it is underutilized. An efficient way to utilize the spectrum is cognitive radio. An important point for designing future systems is to gain knowledge about the occupation of the frequency bands which may be used by the cognitive radio. This includes the general characterization of the traffic density at the frequency bands as well as a detailed analysis of the temporal frequency allocation. In this paper, measurements are taken in FM band and the spectrum occupation analysis is done using USRP. Short-term and real-time measurements to enable the radio to predict occupancy is carried out based on the spectrum monitoring performed at various timings of the day.

In the last few years Compressed Sampling (CS) has been well used in the area of signal processing and image compression. Recently, CS has been earning a great interest in the area of wireless communication networks. CS exploits the sparsity of the signal processed for digital acquisition to reduce the number of measurement, which leads to reductions in the size, power consumption, processing time and processing cost. This article presents application of CS for the spectrum sensing and channel estimation in Cognitive Radio (CR) networks. Basic approach of CS is introduced first, and then scheme for spectrum sensing and channel estimation for CR is discussed. First, fast and efficient compressed spectrum sensing (CSS) scheme is proposed to detect wideband spectrum, where samples are taken at sub-Nyquist rate and signal acquisition is terminated automatically once the samples are sufficient for the best spectral recovery and then, after the spectrum sensing, in the second phase notion of multipath sparsity is formalized and a novel approach based on Orthogonal Matching Pursuit (OMP) is discussed to estimate sparse multipath channels for CR networks. The effectiveness of the proposed scheme is demonstrated through comparisons with the existing conventional spectrum sensing and channel estimation methods.

A scenario is presented in spectrum sensing for Cognitive Radio Networks based on energy detectors. Results are presented for the performance of the energy detector based on Welch periodogram. The effect of the number of signal samples and the time domain window function are demonstrated for low Signal-to-Noise Ratio values. Furthermore, the detector performance is linked to a general probabilistic scheme for sensing algorithms. Important system issues such as receiver feedback and cooperative spectrum sensing are included in this framework. Parametric computations of the probability of correct decision are presented to show the detrimental effect of the hidden node problem in a simple collaborative spectrum sensing scheme.

This is a fascinating and satisfying book. It is a hefty tome incorporating some 140 illustrations (four of them colour plates), copious footnotes and a leisurely, multi-threaded analysis dominated by abundant historical examples. Its subject is spectrum analysis, and especially the representation of spectra through the nineteenth and early twentieth centuries.

Natural frequency spectrum is scared resource; the efficient use of it can only accommodate the need of future computing world. But efficient use of it is not possible within the existing system, where the allocation of spectrum is done based on fixed spectrum access (FSA) policy. Many surveys show that it leads to inefficient use of spectrum. For efficient utilization of spectrum innovative techniques is needed. Using Dynamic spectrum access (DSA) policy, available spectrum can be exploited. For given purpose Cognitive radio arises to be a tempting solution which introduces opportunistic usage of the frequency bands that are not heavily occupied by licensed users. This paper presents the study of different spectrum sensing techniques of cognitive radio networks. As matter of fact Cognitive radio is a form of wireless communication where radio transceiver intelligently detects which spectrums are free which are not. After this it occupies the vacant one while avoiding busy one. Cognitive radios promote open spectrum allocation which is a clear departure from traditional command and control allocation schemes for radio spectrum usage. In short, it allows the formation of "infrastructure-less" collaborative network clusters which is called Cognitive Radio Networks (CRN). However spectrum sensing techniques are needed to detect free spectrum. In this paper, different spectrum sensing techniques are analyzed with their respective pros and corns

Today's wireless communication systems follow fixed spectrum assignment policies which leads to overall inefficient spectrum use. Further, spectrum scarcity is an issue for operators with emerging mobile services and large number of users with even higher capacity requirements. This inefficiency and scarcity in spectrum usage necessitates a new paradigm for communications such as utilising available spectrum opportunistically. Cognitive radio (CR) is an enabling technology having potential to increase spectrum utilisation and provide desired interference protection to licenced users. This can be done by detection of spectrum opportunities by secondary users. Due to channel fading and shadowing a single user can not make a reliable decision and collaboration of and among users is required. In this paper, it has been demonstrated that for improved detection performance decision fusion algorithm for collaborative spectrum sensing must have information about channel and the mean SNR of all secondary users. Using Monte Carlo simulations it is concluded that for optimum performance it is not necessary that all users collaborate with each other.

This work presents a spectrum sensing technique based on the entropy of frequency domain autocorrelation of receiving signal at different cyclic frequencies. The performance of the proposed sensing technique is compared with other sensing techniques such as energy detection using Bayesian and Neyman-Pearson criteria, entropy estimation under frequency domain, cyclostationary feature detection. The performance of sensing algorithms is also analyzed for single node and multinode/cooperative environment under most probable channel effects such as fading, shadowing, receiver's uncertainty and free space path loss using Monte-Carlo methods. Simulation results reveal that the proposed sensing technique is able to detect signals of signal-to-noise ratio up to À24 dB with five nodes in cooperation while maintaining a false alarm probability of 0.1 and a detection probability of 0.9. The proposed sensing algorithm is also implemented in Virtex-4 Field Programmable Gate Arrays.

Cognitive radio is emerging as a promising technique to improve the utilization of radio frequency spectrum. In this paper, we consider the problem of spectrum sharing among primary (or "licensed") and secondary (or "unlicensed") users. We formulate the problem based on bandwidth auction in which each secondary user makes a bid for the amount of spectrum and each primary user may assign the spectrum among secondary users by itself according to the information from secondary users without degrading its own performance. We show that the auction is a non-cooperative game and Nash equilibrium can be its solution. We first consider a single-primary-user network to investigate the existence and uniqueness of Nash equilibrium, and further discuss the fairness among secondary users under given conditions. Then, we present a dynamic updating algorithm in which each secondary user achieves Nash equilibrium in a distributed manner. The stability condition of the dynamic behavior for this spectrum sharing scheme is studied. The discussion is generalized to the case in which there are multiple primary users in the network, where the properties of Nash equilibrium are shown under appropriate conditions. Simulations were used to evaluate the system performance and verify the effectiveness of the proposed algorithm.

Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as NeXt Generation (xG) Networks as well as Dynamic Spectrum Access (DSA) and cognitive radio networks. The term xG networks is used throughout the paper. The novel functionalities and current research challenges of the xG networks are explained in detail. More specifically, a brief overview of the cognitive radio technology is provided and the xG network architecture is introduced. Moreover, the xG network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated and open research issues in these areas are also outlined. Finally, the cross-layer design challenges in xG networks are discussed.

The tremendous growth in wireless communication has increased the spectrum usage, thereby raised the spectrum scarcity and security issues. The real problem is the inefficient spectrum allocation and its usage. Cognitive Radio is considered to be the key enabling technology for such problems. Spectrum sensing is the main aspect of cognitive radios. In this paper, a survey of Interference mitigation techniques by using Spatial Modulation in cognitive radio is studied. To protect both the primary as well as secondary user transmission, beam forming techniques is used. Such a scheme can be employed in the 5G technologies by the deployment of GFDM. Also, a comparative study on other 5G multicarrier transmission schemes such as FBMC and UFMC is done.