Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> E. Decision Fusion in Cooperative Sensing <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> BIB001 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> E. Decision Fusion in Cooperative Sensing <s> In this paper a distributed approach to mode identification and spectrum monitoring is studied. A Wireless Network composed by Cognitive Terminals is used to classify air interfaces present in the radio scene. The use of cooperative strategies and an advanced signal processing tool, Time Frequency analysis, allows to improve the radio awareness of device. Results in the terms of error probability, modeling the probability density function of considered features as Asymmetric Generalized and Generalized Gaussian functions, are compared to error rate showing good performance and coherence of theoretical model with experimental results. <s> BIB002 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> E. Decision Fusion in Cooperative Sensing <s> Cognitive radios is emerging in research laboratories as a promising wireless paradigm, which will integrate benefits of software defined radio with a complete aware communication behavior. To reach this goal many issues remain still open, such as powerful algorithms for sensing the external environment. This paper presents a further step in the direction of allowing cooperative spectrum sensing in peer-to-peer cognitive networks by using distributed detection theory. The approach aims at improving the radio awareness with respect to stand alone scenario as it is shown with theoretical and experimental results <s> BIB003 </s> Spectrum Sensing Methodologies for Cognitive Radio Systems: A Review <s> E. Decision Fusion in Cooperative Sensing <s> The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given. <s> BIB004
Sharing information among cognitive radios and combining results from various measurements is a challenging task BIB004 . This shared information can either be soft or hard decisions made by each cognitive device  . The results presented in   shows that soft information combining method performs better than hard information combining method in terms of the probability of missed opportunity. Hard decision is found to perform as good as soft decision when the numbers of cooperating users are high. The optimum fusion rule for combining sensing information is the ChairVarshney rule with log-likelihood ratio test  . Likelihood ratio tests (LRT) are used for making classification using decision from secondary users in   BIB002  BIB003 . Different techniques for combining sensing result are employed in BIB001 . The credibility of cognitive radios depends on the channel conditions and their distance from a licensed user. The required number of nodes for satisfying a probability of false alarm rate is investigated in  .