Novel Semi-Blind Spectrum Sensing in Cognitive Radio Networks with Fourth-Order Statistics (original) (raw)
Related papers
A Performance Study of Energy Detection Based Spectrum Sensing for Cognitive Radio Networks
Spectrum scarcity is considered an impediment to the growth of wireless technologies. However, studies reveal a significant underutilization of the frequency spectrum apportioned to licensed users. An intelligent radio technology platform, termed Cognitive Radio was conceived to solve this imminent challenge by shifting the paradigm of a static spectrum allocation policy to that of dynamic (opportunistic) spectrum access. A foremost part of this technology is spectrum sensing. Among the methods espoused, Energy Detection possesses an advantage of low implementation and low computational complexity; compared to the other methods that require prior information and specific features of the signal to be detected. This study evaluates the performance of the energy detection based spectrum sensing technique in noisy and fading environments. Both single user detection and cooperative detection situations were investigated. Closed form solutions for the probabilities of detection and false alarm were derived. Analytical results were verified by numerical computations using Monte Carlo method in MATLAB. The performance of the energy detection technique was evaluated by use of Receiver Operating Characteristics (ROC) curves over AWGN and fading (Rayleigh & Nakagami-m) channels. Results show that for both single user detection and cooperative detection, the energy detection technique performs better in AWGN than in fading environment. The performance of cooperative detection in fading environment on the other hand, outperforms that of the single user detector.
The rapid growth of bandwidth demanding wireless technologies has led to the problem of spectrum scarcity. However, studies show that licensed spectrum is underutilized. Cognitive radio technology promises a solution to the problem by allowing unlicensed users, access to the licensed bands opportunistically. A prime component of the cognitive radio technology is spectrum sensing. Many spectrum sensing techniques have been developed to sense the presence or not of a licensed user. This paper evaluates the performance of the energy detection based spectrum sensing technique in noisy, fading, jamming, interference environments. Both single user detection and cooperative detection situations were investigated. Closed form solutions for the probabilities of detection and false alarm were derived. The analytical results were varied by numerical computations using Monte Carlo method with MATLAB. The performance of the computationally efficient energy detection (CE-ED) techniques were evaluated by use of Receiver Operating Characteristics (ROC) curves over additive white Gaussian noise (AWGN) and fading (Rayleigh & Nakagami-m) channels. Results show that for single user detection, the energy detection technique performs better in AWGN channel than in the fading channel models. The performance of cooperative detection is better than single user detection in fading environments.
Himalayan Journal of Applied Science and Engineering
Cognitive radio is a ground-breaking software-defined radio paradigm that offers Dynamic spectrum access, allowing secondary users to use the frequency band allotted to the principal user when it is not in use and vacate when the prime application returns. The ability to sense the spectrum is critical to cognitive radio's efficiency. Energy detection sensing is the simplest and most often used spectrum sensing approach, owing to its ease of implementation in cognitive radio applications. The three-energy detection-based algorithms adopted for different scenarios have been compared in this study. The algorithms include the double-threshold energy detection, adaptive single threshold energy detection, and the adaptive double threshold spectrum sensing algorithm. Since the noise prediction in the practical situation is difficult, the necessity is to find the best algorithm in this condition. The other equally important parameters for efficiently sensing the spectrum are spectrum ef...
Spectrum Sensing Algorithms for Cognitive Radio Systems
Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of cognitive systems is spectrum sensing, that consists the analysis of the radio frequency spectrum. In particular, CR has been mainly studied in the context of opportunistic spectrum access, in which secondary devices are allowed to transmit avoiding harmful interference to higher priority systems, called primary users. Thus cognitive nodes must implement signal detection techniques to identify unused bands for transmission. We focused different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. We consider the presence of practical impairments, such as parameter uncertainties, and analyze algorithm design. We aim at providing contributions to the main classes of sensing techniques, from basic energy detection, to cooperative eigen value based algorithms, to wideband approaches, touching also simple localization strategies for CR networks. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the unknown noise power is estimated at the receiver. This analysis allows deepening the phenomenon of the Signal-To-Noise Ratio (SNR) wall, providing the conditions for its existence. This work highlight that the presence of the SNR wall is determined by the accuracy of the noise power estimation process.
A Novel Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks
—The rapid growth in wireless communication technology has led to a scarcity of spectrum. But, studies are saying that licensed spectrum is underutilized. Cognitive Radio Networks (CRNs) seem to be a promising solution to this problem by allowing unlicensed users to access the unused spectrum opportunistically. In this paper we proposed a novel spectrum sensing algorithm to improve the probabilities of detection and false alarm in a CRN, using the traditional techniques of energy and first order correlation detection. Results show a significant improvement in performance in cooperative spectrum sensing. Keywords—cognitive radio networks, energy detection, correlation detection, cooperative spectrum sensing.
A Review on Spectrum Sensing for Cognitive Radio: Challenges and Solutions
Eurasip Journal on Advances in Signal Processing, 2010
Cognitive radio is widely expected to be the next Big Bang in wireless communications. Spectrum sensing, that is, detecting the presence of the primary users in a licensed spectrum, is a fundamental problem for cognitive radio. As a result, spectrum sensing has reborn as a very active research area in recent years despite its long history. In this paper, spectrum sensing techniques from the optimal likelihood ratio test to energy detection, matched filtering detection, cyclostationary detection, eigenvalue-based sensing, joint space-time sensing, and robust sensing methods are reviewed. Cooperative spectrum sensing with multiple receivers is also discussed. Special attention is paid to sensing methods that need little prior information on the source signal and the propagation channel. Practical challenges such as noise power uncertainty are discussed and possible solutions are provided. Theoretical analysis on the test statistic distribution and threshold setting is also investigated.
Energy Detection Based Spectrum Sensing for Cognitive Radio: An Experimental Study
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010
Cognitive radios may operate in practice under various adverse environments. For typical mobile and short-range scenarios, wireless links may tend to be time and frequency selective, i.e., the multipath propagations with time-varying fading coefficients will be inevitable. To cope with the encountered doubly-selective channels, in this paper we present a new spectrum sensing algorithm for distributed applications. Firstly, a dynamic discrete state-space model is established to characterize sensing process, where the occupancy state of primary band and the time-varying multipath channel are treated as two hidden states, while the summed energy is adopted as the observed output. With this new paradigm, spectrum sensing is realized by acquiring primary states and time-dependent multipath channel jointly. For the formulated problem, unfortunately, Bayesian statistical inference may be impractical due to the absence of likelihoods and involved non-stationary distributions. To remedy this problem, an iterative algorithm is further designed by resorting to sequential importance sampling techniques, thus the dynamic non-Gaussian multipath channel and primary states are estimated recursively. Another critical challenge, e.g., the noise uncertainty, is also considered, which may be incorporated conveniently into this sensing diagram and, furthermore, addressed effectively by the designed algorithm. Simulations validate the proposed algorithm. While classical schemes fail to deal with doubly-selective channels, the new sensing scheme can exploit the underlying channel memory and operate well, which provides a great promise to realistic applications.
2015
The ever growing wireless technologies has put a lot of demand on the usage of available spectrum, thus leading to spectrum underutilization and scarcity. To address this issue and improve spectrum utilization gave rise to the concept of the cognitive radio. The cognitive radio is known to enhance the utilization of spectrum of where a secondary user can utilize the spectrum of the primary user without causing harmful interference to the incumbent primary user. In this paper, we evaluated the performance of the energy detection based spectrum sensing in a fading and non-fading environments. Also we presented results on the single user detection and cooperative detection applying the energy detector. The performance of the energy detection technique was assessed by the use of the receiver operating characteristics (ROC) curves over additive white Gaussian noise (AWGN), Rayleigh and Nakagami channels. The cooperative detection shows better performance to the single user in the fading ...
Multi-Stages Co-Operative/Non-Cooperative Schemes of Spectrum Sensing for Cognitive Radio Systems
International Journal of Wireless & Mobile Networks, 2016
Searching for spectrum holes in practical wireless channels where primary users experience multipath fading and shadowing, with noise uncertainty, limits the detection performance significantly. Moreover, the detection challenge will be tougher when different band types have to be sensed, with different signal and spectral characteristics, and probably overlapping spectra. Besides, primary user waveforms can be known (completely or partially) or unknown to allow or forbid cognitive radios to use specific kinds of detection schemes! Hidden primary user's problem, and doubly selective channel oblige the use of cooperative sensing to exploit the spatial diversity in the observations of spatially located cognitive radio users. Incorporated all the aforementioned practical challenges as a whole, this paper developed a new multistage detection scheme that intelligently decides the detection algorithm based on power, noise, bandwidth and knowledge of the signal of interest. The proposed scheme switches between individual and cooperative sensing and among featured based sensing techniques (cyclo-stationary detection and matched filter) and sub-band energy detection according to the characteristics of signal and band of interest.Compared to the existing schemes, performance evaluations show reliable results in terms of probabilities of detection and mean sensing times under the aforementioned conditions.
A Novel Energy Detection Technique for Cooperative Spectrum Sensing in Cognitive Radio
Journal of Green Engineering
Cooperative spectrum sensing is used as a promising solution to detect the primary user effectively in a highly noisy environment, where the multiple secondary users make a global decision in relation to the primary user. The Bayesian Estimation Energy Detection (BEED) technique is one of the elegant spectrum sensing techniques available in a non-cooperative environment. So an attempt was made in this paper by incorporating the BEED in a cooperative environment, which yields the detection of primary user effectively up to a Signal to Noise Ratio (SNR) of-19 dB, when the Rayleigh fading effects are considered.