International Journal of Computer Applications (0975 – 8887) Volume 46– No.11, May 2012 10 Efficient Energy Detection Technique in Cognitive Radio Ad-hoc Network Shubhangi Mahamuni Assistant Professor, MAE,Alandi(D), Pune,Maharastra,India Vivekanand Mishra Associate Professor SVNIT, Surat Gujrat, India Vijay M.Wadhai Principal, MITCOE Kothrud,Pune Maharastra,India ABSTRACT Cognitive radio ad-hoc networks (CRAHNs) is used to solve the current problems of inefficiency in the spectrum allocation and used to deploy highly reconfigurable and self organizing wireless networks. Cognitive radio represents an efficient technology since it allows exploiting the unused radio resources. In this context, spectrum sensing plays very important role in cognitive radio communication technology. Here we considered simplified energy detection technique for spectrum sensing. Simulation results show the channel selection along with the signal to noise ratio utilized for message towards destination node by the efficient energy detection method. General Terms Cognitive Radio Communication Keywords Cognitive radio, Spectrum Sensing, Spectrum handoff. 1. INTRODUCTION Cognitive Radio Communication technology used for supporting dynamic spectrum access [1,2,3].During the present scenario, Cognitive radio becomes a popular solution over inefficiency in the spectrum allocation. Sensing of a spectrum and throughput of a cognitive radio network [4,5] plays very important role for the proper and efficient allocation of a spectrum. An end-to-end protocol for cognitive radio ad-hoc networks [6,7] is used for the performance calculation of Cognitive Radio Ad-hoc Network .Ideal energy detection technique used for the detection of idle period of a primary spectrum. Different detection techniques [8,9,10,11] are used for the spectrum sensing .Matched filter detection, feature detection require prior information about the primary signal information .For the energy detection technique no prior information required. Energy detection technique has poor performance in comparison with feature and matched filter detection technique [12,13,14,15].Ideal Energy Detection Technique used for the detection of idle period of a primary spectrum plays very important role. Different detection techniques are used for the detection of idle period of a primary spectrum [16, 17, 18,19,20]. The rest of this paper is organized as follows. In Section 2, we describe Spectrum Sensing Method The proposed spectrum sensing algorithms are examined by numerical examples in Section 3, simulation and results are Section 4,conclusion and future work is in section 5. 2. IDEAL ENERGY DETECTION TECHNIQUE: In cognitive radio scenarios, signal details are unknown, so we have to treat the signal received as a sample function of a random process. When the signal statistics are known, we can design suitable detectors. The schematic diagram of traditional energy detector is shown in Fig 2. Fig.1. Schematic diagram of traditional energy detector The energy detector [4] consists of a squaring device followed by a finite time interval integrator. Pre-filter will make a selection for a certain spectrum band, then y(t) will be a band- pass signal. Suppose signal is transmitted in AWGN (Additive White Gaussian Noise) channel, then y(t) will be a band- limited random process. Calculating the statistics of y(t) from formula (1) under an assumption that n(t) is zero mean Gaussian random process, we can write 1) H0: signal is absent. a. y(t) = n(t) b. E(y (t)) = 0 c. E( 1/T ∫ y(t) dt) =No 2) H1: signal is present. a. y(t) = s(t) + n(t) b. E(y (t)) = s (t) c. E (1/T ∫ y (t) dt) = Ps+Ns are the average power of signal and noise respectively. For a certain time interval, only calculating signal energy in time interval T is much more convenient because it is monotonic