Cognitive Radio Networks

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Application of Stochastic Resonance of the Single-mode Nonlinear Optical System in Spectrum Sensing of Cognitive Radio Networks

Application of Stochastic Resonance of the Single-mode Nonlinear Optical System in Spectrum Sensing of Cognitive Radio Networks

The cognitive radio technology can improve the efficiency of spectrum utilization byproviding dynamic spectrum access to unoccupied frequency bands. Spectrum sensing is one of the key technologies of cognitive radio networks. The spectrum sensing performance of cognitive radio networks will be greatly reduced in the low SNR environment, especially when using energy detection. Because the stochastic resonance system can improve the energy detection system output SNR .To improve the spectrum sensing performance of cognitive radio networks in the low SNR environment, the stochastic resonance of the single-mode nonlinear optical system is applied to spectrum sensing based on the energy detection method in this paper. The simulation results show that in the low SNR environment, the energy detection based on stochastic resonance of the single-mode nonlinear optical system has better performance than traditional energy detection.
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Spectrum Sensing Based on Monostable Stochastic Resonance in Cognitive Radio Networks

Spectrum Sensing Based on Monostable Stochastic Resonance in Cognitive Radio Networks

The cognitive radio technology can provide dynamic spectrum access and improve the efficiency of spectrum utilization. Spectrum sensing is one of the key technologies of cognitive radio networks. The spectrum sensing performance of cognitive radio networks will be greatly reduced in the low SNR environment, especially when using energy detection. Due to the monostable stochastic resonance system can improve the energy detection system output SNR, a monostable stochastic resonanceis applied to spectrum sensing based on the energy detection method of cognitive radio networks in this paper. The simulation results show that in the low SNR environment, when the false alarm probability is constant, the proposed spectrum sensing based on monostable stochastic resonance has better performance than traditional energy detection.
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Orthogonal Frequency-Division Multiplexing-Based Cooperative Spectrum Sensing for Cognitive Radio Networks

Orthogonal Frequency-Division Multiplexing-Based Cooperative Spectrum Sensing for Cognitive Radio Networks

Nowadays, OFDM techniques are adopted by many existing technology, there have been a variety of spectrum sensing schemes at the physical layer for cognitive radio systems. Recent research on spectrum sensing focuses on more practical sensing techniques utilizing various characteristics in transmitted signals, such as cyclic prefix-based detection for the OFDM signal. [8] presented sensing methods based on both power detector and waveform detector. [9] proposed a method based on exploiting the cyclostationary characteristics of the licensed user signal. However, in conventional spectrum sensing schemes, an unlicensed user is not able to sense the spectrum during data transmission period because both transmitting and receiving signals. As a result, the idle period for sensing is unavoidable. This idle period is system overhead, which causes decrease in the total throughput of the secondary user [3], [5], [6], [7].
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Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Dari Tabel 4.2 terlihat bahwa setiap persentase pembangkitan data masukan mulai dari 10% sampai dengan 100% memiliki kemampuan deteksi yang berbeda-beda. Untuk mendeteksi kehadiran primary user ditentukan berdasarkan perbandingan energi sinyal tehadap nilai threshold yang mana telah ditetapkan bahwa primary user dikatakan hadir (present) jika kanal frekuensi menghasilkan spektrum daya melebihi nilai thresholdnya dan dikatakan tidak hadir (absent) jika kanal frekuensinya menghasilkan spektrum daya di bawah nilai thresholdnya dan kanal frekuensi yang kosong inilah yang nantinya dapat digunakan oleh cognitive radio user. Dari simulasi ini PSD Blackman-Tukey memiliki kemampuan mendeteksi yang cukup akurat, dimana pada saat data masukannya dibangkitkan saat presentasi 10%, 20%, 50%, 60%, 80%, 90% dimana jumlah kanal frekuensi acak yang diperoleh mampu dideteksi secara keseluruhan dimana jumlah primary user yang dideteksi pada PSD ini yaitu 5 PU, 10 PU, 25 PU, 30 PU, 40 PU, dan 45 PU. kehadiran primary user metode Blackman-Tukey ini lebih jelas lagi dapat dilihat pada Lampiran 3.
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Cognitive Radio Oriented Wireless Networks 2015

Cognitive Radio Oriented Wireless Networks 2015

TCP has been extensively studied and analyzed over the past decades. Given its widespread adoption, identifying which of its specific rate control mechanisms are best suited in CR networks will yield useful insights in tuning them for these challenging environments. This is the first step towards determining whether minor changes to existing protocol flavors are sufficient to adapt TCP, or if an entirely new class of window-based approaches are needed to achieve satis- factory operation. We conduct the first comprehensive study of three different TCP flavors with this aim, focusing on high-bandwidth varying situations. Our previous works have explored enhancing TCP NewReno by leveraging extensive cross-layer and intermediate-node information [2] as well as extending equation- based protocol called TFRC [3]. However, both these approaches have limita- tions. First, the transport layer is envisaged to operate end to end from a classical networking viewpoint, and thus, enforcing dependence on the choices made at the lower layers, or mandating feedback from other intermediate nodes, brings about a radical change in the commonly accepted end-to-end paradigm, and results in a loss of generality. Similarly, TFRC is shown to be TCP-friendly in its classical incarnation, while our proposed triggers for the rate control equa- tion in the modified TFRC-CR cause it to lose this important characteristic (though it gives higher network throughput and protection to licensed users). Thus, TFRC-CR can no longer fairly exist with other TCP flows, which lim- its deployment opportunities. As a result, in this study, we examine other well known and unmodified TCP flavors that are compliant with the fairness crite- rion, as well as the end-to-end paradigm of the transport layer, and we determine which of these are best suited for CR networks ‘as is’.
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S FIS 1005397 Bibliography

S FIS 1005397 Bibliography

Turnip, A., Hutagalung, S. S., Pardede, J., Soetraprawata, D. (2013). P300 Detection using multilayer neural networks based adaptive feature extraction method. International Journal of Brain and Cognitive Science, vol.2 hlm.63-75.

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Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Komunikasi radio adalah komunikasi tanpa kabel yang memanfaatkan udara (ruang hampa/ free space ) sebagai media transmisi unuk perambatan gelombang radio ( yang bertindak sebagai gelombang pembawa informasi ). Sistem terdiri atas dua bagian pokok, yaitu pemancar (Tx) dan penerima (Rx). Pemancar terdiri atas modulator dan antena pemancar, sedangkan penerima terdiri atas demodulator dan antena penerima. Modulator berfungsi memodulasi informasi menjadi sinyal yang akan dipancarkan melalui antena pemancar. Antena merupakan suatu sarana atau piranti pengubah sinyal listrik (tegangan/arus) menjadi sinyal elektromagnetik (sebagai pemancar). Sinyal elektromagnetik inilah yang akan dipancarkan melalui udara atau ruang bebas (sehingga sampai ke penerima). Sinyal yang dipancarkan oleh antena pemancar akan ditangkap oleh antena penerima seperti pada Gambar 2.1[1].
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Our core principles in working with ICT and media are built on existing practices. That applies to both media and ICT. For example, Kinerja sees usage of appropriate technologies and already adopted communication channels (BlackBerry messenger, community radio, Facebook and SMS, for example) as a key principle in its media strategy. However, we also recognize that communication technologies are changing rapidly, and so we hope to build into our planning anticipation of their further evolution, spread and adoption in a country known for its early and enthusiastic embrace of advances in communication technologies. For example, Facebook is presently only appropriate in urban areas such as Makassar, but as the project progresses usage is expected to spread to more rural areas, increasing its applicability and creating opportunities to apply lessons learned and resources developed in those areas of early adoption.
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https://drive.google.com/file/d/0B9HTG AMkP1YM1VFZm0yU1h6UG8/view?usp=sharing

https://drive.google.com/file/d/0B9HTG AMkP1YM1VFZm0yU1h6UG8/view?usp=sharing

Electroencephalogram (EEG) records brain activities based on its potential[4]. On the other hand, ERP measured brain response directly from thought or perception; it may be cognitive, sensory, or motoric events[5]. Among many types of signals that constitute ERP signal, P300 is the most important in detecting lies[6].

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Research on Sensor Network Spectrum Detection Technology based on Cognitive Radio Network

Research on Sensor Network Spectrum Detection Technology based on Cognitive Radio Network

The features of the cognitive radio network could be summarized as the following. (1) Sensor nodes are usually distributed in very extensive areas, in order to complete the perception of the real world, high density, sensor node deployment is also very intense. The whole wireless sensor network system reliability and quality of work rely on large-scale, redundancy of embedded devices to work together to implement and improve. In this way, through perceived information in the view of the different space signal-to-noise ratio is bigger. In a large amount of information, distributed processing method can effectively improve the accuracy of the monitoring, and lower precision requirements for a single sensor node. Due to the presence of large amounts of redundant nodes, the system fault tolerance. (2) Each sensor node in the wireless sensor network is random division in monitoring area, the location of the node can't accurate location in advance, the neighbor relationship between nodes are unpredictable, this requires that each sensor node itself has high ability of self-organization which can automatically configure and automatic management, through the network protocol and topology control mechanism automatically form forwarding monitoring data more wireless network. (3) Common cable communication distance of sensor nodes, in a few meters to hundreds of meters. Nodes can communicate with in your communication within the scope of the adjacent nodes. But if you need to communicate with more than its communication range of the other nodes, you must pass by other nodes forwarding routing. The multi-hop routing of wireless sensor network is the common network node collaboration, that is to say, sometimes sensor nodes need to act as the sponsor of the information, forwarding and the recipient the three roles [16]. (4) Sensor network is different from the address centered to the Internet, it is a task-based network and its aim is to obtain the data information. Sensor nodes in a network of all use serial number identification, the network node number is unified depends on the communication protocol of the system. Unable to determine the position of the sensor nodes in advance, the serial number of sensor nodes are depending on the system dynamic allocation, namely node number and the node position is no necessary link between the two. (5) Sensor energy supply in the wireless sensor network is usually carry from its own battery, once the battery runs out, that the sensor node will not be able to continue to work. Extend working hours of all nodes, therefore, that means the whole prolong the working life of the wireless sensor network. The node in the data transmission phase is the consumption of energy, this requests us in the case of complete the task does not affect as far as possible to reduce data transmission, so as to achieve the purpose of save energy and prolong the life of the whole network [17].
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Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Salah satu jenis cognitive radio yang paling banyak digunakan adalah energy detection . Tugas akhir ini menggunakan metode energy detection dengan membandingkan kinerjanya menggunakan PSD (Power Spectral Density) Blackman-Tukey dan Welch . Adapun parameter yang mempengaruhi dalam penelitian ini adalah spektral daya sinyal dan Threshold .

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A Cognitive Radio Spectrum Sensing Algorithm to Improve Energy Detection at Low SNR

A Cognitive Radio Spectrum Sensing Algorithm to Improve Energy Detection at Low SNR

Figure 1 shows the result, the false alarm rate as a function of the number of samples. False alarm rate shows the number of times the detector made wrong decision of vacant channel as occupied. This will miss the opportunity for cognitive radio to maximize spectrum holes ulitization. This will be mainly a function of the threshold. If we set the threshold higher, this will result in lower false alarm, but will also make lower detection rate when later it has to work to detect primary signals. As a general spectrum sensing requirement, false alarm rate should not exceed P f maximum of 10 %, as shown in the figure as a dashed line. By setting the
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PENGARUH WAKTU SENSING TERHADAP KINERJA THROUGHPUT DALAM SISTEM COGNITIVE RADIO NETWORK YANG BERBASIS MATRIKS KOVARIANSI THE IMPACT OF SENSING TIME TO THROUGHPUT PERFORMANCE IN COGNITIVE RADIO NETWORK BASED ON COVARIANCE MATRIX

PENGARUH WAKTU SENSING TERHADAP KINERJA THROUGHPUT DALAM SISTEM COGNITIVE RADIO NETWORK YANG BERBASIS MATRIKS KOVARIANSI THE IMPACT OF SENSING TIME TO THROUGHPUT PERFORMANCE IN COGNITIVE RADIO NETWORK BASED ON COVARIANCE MATRIX

In this paper, cognitive radio system will be designed to detect signals in the form of modulated signal PU Orthogonal Frequency Division Multiplexing (OFDM) with two different types of noise. The process will start with randomly generate OFDM signal with the sensing time is different. then it will be added to the noise power remains (Certain noise) and changing (uncertain noise) and each output will be used as input or input to a process of spectrum sensing to be performed by the method of covariance matrix to determine the detection performance with a second input the form -an distribution Keyword :Cognitive Radio, OFDM, Energy Detector, Covariance Matrix, Sensing time nitive Radio, OFDM, Energy Detector, Covariance Matrix, Sensing time
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UNTUK APLIKASI KOGNITIF RADIO DESIGN AND REALIZATION ULTRA-WIDEBAND ANTENNA 800-2400 MHZ FOR RADIO COGNITIVE APPLICATION

UNTUK APLIKASI KOGNITIF RADIO DESIGN AND REALIZATION ULTRA-WIDEBAND ANTENNA 800-2400 MHZ FOR RADIO COGNITIVE APPLICATION

Radio kognitif sendiri adalah suatu bentuk komunikasi nirkabel dimana transceiver mampu mendeteksi saluran komunikasi yang digunakan dan yang tidak, dan langsung berpindah ke saluran yang tidak terpakai sambil menghindari saluran yang sedang diduduki. Hal ini mengoptimalkan penggunaan ketersediaan frekuensi radio spektrum, sementara gangguan diminimalkan untuk pengguna lain. Teknologi CR adalah paradigma untuk komunikasi nirkabel dimana pengiriman atau penerimaan parameter jaringan atau node nirkabel berubah untuk menghindari gangguan komunikasi dengan pengguna berlisensi atau yang tidak berlisensi[3].
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Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Analisis Kinerja Energy Detection Blackman-Tukey dan Welch Pada Kanal AWGN Aplikasi Cognitive Radio

Energy Detection Blackman-Tukey dan Welch pada Kanal AWGN aplikasi Cognitive Radio ” . Penulisan Tugas Akhir ini merupakan salah satu persyaratan untuk menyelesaikan studi dan memperoleh gelar Sarjana Teknik di Departemen Teknik Elektro, Fakultas Teknik, Universitas Sumatera Utara.

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PENGARUH WAKTU SENSING TERHADAP KINERJA THROUGHPUT DALAM SISTEM COGNITIVE RADIO NETWORK THE IMPACT OF SENSING TIME TO THROUGHPUT PERFORMANCE IN COGNITIVE RADIO NETWORK

PENGARUH WAKTU SENSING TERHADAP KINERJA THROUGHPUT DALAM SISTEM COGNITIVE RADIO NETWORK THE IMPACT OF SENSING TIME TO THROUGHPUT PERFORMANCE IN COGNITIVE RADIO NETWORK

Cognitive Radio is a new technology that allows the secondary user (unlicense) to using primary spectrum (license) whenever available. Spectrum sensing is affected by the time of detection of the primary frequency spectrum, in order to avoid any error detection or false alarm. In this research, an analysis of the performance of detection in cognitive radio system with Orthogonal Frequency Division Multiplexing (OFDM) technology. Performance Analysis of detection consists of Receiver Operating Characteristic (ROC) analysis, sensing time and throughput. Energy detector techniques applied in this research. Increasingly value of the sensing time, resulting greater shifts in the distribution of E. Due to the shift of the distribution of E can simplify the task of energy detector to detect more accurately. This causes increasing probability of detection. Usage of energy detector in practice is going poorly because of the uncertain noise. By using sensing time duration of 24 ms obtained received throughput for the condition (iii) is 0.4387 bits
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DETEKSI SINYAL SPECTRUM SENSING MENGGUNAKAN NILAI EIGEN PADA COGNITIVE RADIO SPECTRUM SENSING SIGNAL DETECTION USING EIGEN VALUE FOR COGNITIVE RADIO

DETEKSI SINYAL SPECTRUM SENSING MENGGUNAKAN NILAI EIGEN PADA COGNITIVE RADIO SPECTRUM SENSING SIGNAL DETECTION USING EIGEN VALUE FOR COGNITIVE RADIO

Cognitive Radio adalah sebuah sistem nirkabel cerdas yang dapat memahami lingkungan komunikasi dan dapat mendeteksi lingkugan spektral pada frekuensi yang luas dan dapat mengeksploitasi spektrum frekuensi yang sedang tidak dipakai agar bisa digunakan dalam waktu tertentu [4]. Cognitive Radio(CR) dapat mendeteksi lingkungan spektrum dari berbagai variansi bands frequency dan dapat menduduki kanal kosong yang tidak terpakai oleh Primary User (PU) [5]. Primary User didefinisikan sebagai pengguna yang memiliki hak dalam penggunaan spektrum frekuensi tertentu atau pengguna yang memiliki prioritas paling tinggi dalam penggunaan spektrum frekuensi [6]. Sedangkan Secondary User (SU) adalah pengguna yang tidak mempunyai hak untuk kepemilikan spektrum frekuensi atau pengguna yang memiliki tingkat prioritas lebih rendah daripada PU [6]. Maka dari itu Cognitive Radio harus dapat mendeteksi apakah spektrum frekuensi dari PU bisa digunakan atau tidak secara dinamis. Tujuan utama dari Cognitive Radio ini adalah mengoptimalkan pemakaian spektrum frekuensi [7].
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Cognitive Networks  Applications and Deployments pdf  pdf

Cognitive Networks Applications and Deployments pdf pdf

creating a new RF spectrum band. For SUs with software-defined radios along with some intelligence to work automatically accord- ing to their operating environment, the radio components are imple- mented in software rather than in hardware; therefore, it is possible to adapt system configurations to any frequency to transmit and receive the data. It is important to note that the primary users (PUs) are the authorized users of the licensed frequency band, and SUs, who are not the PUs but want to use the licensed frequency band, are the cognitive users in CWNs. It is also worth mentioning that allowing an SU to access the licensed spectrum (imposing some constraints on SUs) improves the spectrum utilization. In CWNs, devices detect each other’s presence as interference and try to avoid the interference autonomously by changing their behavior accordingly. In dynamic spectrum sharing, SUs are not allowed to cause harmful interference to the incumbent PUs. It is worth noting that the SUs are essen- tially invisible to the PUs in CWNs; hence, possibly no changes are needed for licensed users/devices. In such a scenario, SUs can either be allowed to transmit at low power as in the ultra wideband (UWB) system or be allowed to use spectrum opportunities dynamically to transmit without causing the harmful interference to PUs. In the lat- ter case, the CWN autonomously detects and exploits the idle spec- trum where and when the PUs are not active. This helps to increase the system capacity and efficiency, and the dynamic spectral access implies that the SU be able to work in multiband, different wireless channels, and support multimedia services and/or applications.
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Cognitive Radio Oriented Wireless Networks pdf  pdf

Cognitive Radio Oriented Wireless Networks pdf pdf

In wireless networks, MAC protocols are classified into two main groups: contention-based and contention-free MAC protocols. The contention-based MAC protocols are distributed in nature and suffer from packet collisions. Nodes whose packets collide, perform a random backoff before attempting to access the channel again for retransmission of the lost frames. Such protocols include ALOHA [1], slotted ALOHA [2] and CSMA/CA family of protocols [3]. On the other hand, the contention free MAC protocols are mainly coordinated in nature involving a centralised master entity which develops and allocates orthogonal or non-orthogonal radio resources according to some policies defined by the schedul- ing algorithms. Schedules assigned to users can either be in time, frequency, space, code or combination of more than one resource dimension. The conven- tional scheduling algorithms include: Round-Robin (RR), Earliest Deadline First (EDF) [4], Maximum Throughput (MT), and Proportional Fair (PF) [5]. Each scheduling algorithm aims at maximizing/minimizing some network performance metrics such as fairness measure, sum throughput, power consumption, latency, etc., subject to some constraints.
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Energy Detection Method In Cognitive Radio.

Energy Detection Method In Cognitive Radio.

Therefore, cognitive radios have to be extra sensitive to discriminate a faded or shadowed main primary signal from a white space. Each uncertainty in the received power of the primary signal translates into a higher detection sensitivity requirement. Moreover, the possibility of a single cognitive radio that depends on the local sensing where the increased sensitivity is not possible to achieve. Therefore, cooperative sensing are required to handle these issues where needed to allocate locale measurements and select the occupancy state on a licensed band.
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