Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> By using Shannon's sampling formula, the problem of the detection of a deterministic signal in white Gaussian noise, by means of an energy-measuring device, reduces to the consideration of the sum of the squares of statistically independent Gaussian variates. When the signal is absent, the decision statistic has a central chi-square distribution with the number of degrees of freedom equal to twice the time-bandwidth product of the input. When the signal is present, the decision statistic has a noncentral chi-square distribution with the same number of degrees of freedom and a noncentrality parameter λ equal to the ratio of signal energy to two-sided noise spectral density. Since the noncentral chi-square distribution has not been tabulated extensively enough for our purpose, an approximate form was used. This form replaces the noncentral chi-square with a modified chi-square whose degrees of freedom and threshold are determined by the noncentrality parameter and the previous degrees of freedom. Sets of receiver operating characteristic (ROC) curves are drawn for several time-bandwidth products, as well as an extended nomogram of the chi-square cumulative probability which can be used for rapid calculation of false alarm and detection probabilities. Related work in energy detection by J. I. Marcum and E. L Kaplan is discussed. <s> BIB001 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> Software radios are emerging as platforms for multiband multimode personal communications systems. Radio etiquette is the set of RF bands, air interfaces, protocols, and spatial and temporal patterns that moderate the use of the radio spectrum. Cognitive radio extends the software radio with radio-domain model-based reasoning about such etiquettes. Cognitive radio enhances the flexibility of personal services through a radio knowledge representation language. This language represents knowledge of radio etiquette, devices, software modules, propagation, networks, user needs, and application scenarios in a way that supports automated reasoning about the needs of the user. This empowers software radios to conduct expressive negotiations among peers about the use of radio spectrum across fluents of space, time, and user context. With RKRL, cognitive radio agents may actively manipulate the protocol stack to adapt known etiquettes to better satisfy the user's needs. This transforms radio nodes from blind executors of predefined protocols to radio-domain-aware intelligent agents that search out ways to deliver the services the user wants even if that user does not know how to obtain them. Software radio provides an ideal platform for the realization of cognitive radio. <s> BIB002 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> This paper presents another look at the problem of energy detection of unknown signals over different fading channels. We start with the no diversity case and present some alternative closed-form expressions for the probability of detection (P/sub d/) to those recently reported in [V.I. Kostylev, May 2002]. We then investigate the system performance when different diversity schemes are employed. It is shown that there is not much improvement in the probability of detection when either the probability of false alarm (P/sub f/) exceeds 0/1 or the average signal-to-noise ratio (SNR) exceeds 20 dB. In addition, receiver operating characteristic (ROC) curves comparing the performance of equal-gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) are presented. As an example, EGC introduces a gain of two orders of magnitude from the probability of miss perspective compared to the no diversity case while both SC and SSC introduce a gain of about one order of magnitude. <s> BIB003 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> In this paper we present an experimental study that comprehensively evaluates the performance of three different detection methods proposed for sensing of primary user signals in cognitive radios. For pilot and energy detection, our measurement results confirmed the theoretical expectations on sensing time performance. However, a physical implementation of these detectors in the presence of real noise uncertainties, analog impairments and interference allowed us to establish practical bounds on the detectable signal levels. In the case of collaborative detection, our analysis of experimental data collected in indoor environments identified the design parameters that can significantly improve the sensing gain: adaptive threshold, spatial separation and multiple antennas. <s> BIB004 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> Cognitive radio is considered as a promising approach to improve the utilization efficiency of radio spectrum resources. One of the key technologies of cognitive radio is spectrum sensing. A survey of spectrum sensing methodologies for cognitive radio is presented in the paper. The advantages and disadvantages of several spectrum sensing algorithms are analyzed and the challenges of spectrum sensing to be realized are also proposed. <s> BIB005 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> In this paper, detection of the primary user (PU) signal in an orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) system is addressed. According to the prior knowledge of the PU signal known to the detector, three detection algorithms based on the Neyman-Pearson philosophy are proposed. In the first case, a Gaussian PU signal with completely known probability density function (PDF) except for its received power is considered. The frequency band that the PU signal resides is also assumed known. Detection is performed individually at each OFDM sub-carrier possibly interfered by the PU signal, and the results are then combined to form a final decision. In the second case, the sub-carriers that the PU signal resides are known. Observations from all possibly interfered sub-carriers are considered jointly to exploit the fact that the presence of a PU signal interferers all of them simultaneously. In the last case, it is assumed no PU signal prior knowledge is available. The detection is involved with a search of the interfered band. The proposed detector is able to detect an abrupt power change when tracing along the frequency axis. <s> BIB006 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> INTRODUCTION <s> Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented, together with a discussion of the pros and cons of each algorithm and the challenging issues. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing and multichannel sub- Nyquist sampling techniques. <s> BIB007
Spectrum sensing can be said to be the process of performing measurement on a part of the spectrum and making a decision related to spectrum usage based upon measured data  . Spectrum sensing is a fundamental operational block of the cognitive radio (CR) which consists of spectrum sensing, management, sharing and spectrum mobility. The growing demand for wireless application has put a lot of strain on the usage of available spectrum. In order to address this situation and improve spectrum efficiency, Mitola proposed a technique that allows secondary users to utilize radio spectrum band allocated to primary users that is not actively used BIB002 . According to a report from the United States Federal Communication Commission  , there are larger temporal and geographic variations in the utilization of allocated spectrum. It is also known that allocated spectrum is underutilized because of the static allocation of the spectrum. In order to overcome this, there is need to propose a means of improving utilization of spectrum  BIB005  . The scarcity and underutilization of spectrum has led to the development of cognitive radio (CR) technology, which exploit the existing spectrum opportunistically. Cognitive radio technology was defined in BIB002 and  . In this paper, the definition of the FCC is adopted. It states "Cognitive Radio is a system that senses its operational electromagnetic environment and can dynamically and autonomously adjust its radio operating parameters to modify system operation, such as maximization of throughput, mitigation of interference and facilitation of inter-operability accessing the secondary markets''. To achieve this goal of cognitive radio, it is a compulsory requirement that a cognitive user (CU) performs spectrum sensing to detect the presence of primary users' (PU) signal BIB006 . In the context of cognitive radio, the primary users can be defined as the users who have higher priority or right in the usage of a specific part of the spectrum. The secondary users (SU) on the other hand are the users who have lower priority or lower rights; they use the spectrum in such a way that they do not cause harmful interference to the primary users. However, secondary users need to have cognitive radio capabilities, such as sensing spectrum efficiently to ascertain if it is being occupied by a primary user and also change their radio parameters to exploit the unused part of the spectrum. The three popularly used methods for spectrum sensing are: Energy detection, Matched filtering and Cyclostationary detection BIB001  BIB004 BIB003 .The basic idea of cognitive radio is its ability for spectral reusing or spectrum sharing, which allows secondary users to communicate over licensed spectrum. It also involves determining what type of signals that are occupying the spectrum including modulation, waveform, bandwidth, carrier frequency, etc. This however, requires powerful signal analysis method with additional computational complexity. Wideband spectrum sensing for cognitive radio network has not been sufficiently investigated in literature. Earlier approach uses a tunable narrowband filter and the RF front-end to sense one narrow frequency band at a time  , in which the existing narrowband sensing techniques can be applied. In order to operate over multiple frequency bands at a time, the RF front-end needs wideband architecture. Spectrum sensing usually involves the estimation of the power spectral density (PSD) BIB007  . There are so many factors that can cause spectrum sensing to be practically challenging. The rest of the paper is organized as follows. Complexity of spectrum sensing concept is studied in Section II. The challenges associated with spectrum sensing for cognitive radio are discussed in section III. Section IV shows the algorithms for spectrum sensing in cognitive radio. Section V discusses the cooperative spectrum sensing. Section VI discusses the research challenges involved in improving cooperative spectrum sensing and finally section VII concludes this paper.