International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 04 | Apr -2017
p-ISSN: 2395-0072
www.irjet.net
Analysis of Matched filter based spectrum sensing in cognitive radio Bhadja Akshaykumar Odhavjibhai1, Professor Shilpa Rana2 1 P.G
Student, Department of Electronics and Communication engineering, L.D.C.E Ahmedabad, Gujarat, India 2 Department of Electronics and Communication engineering, L.D.C.E Ahmedabad, Gujarat, India
---------------------------------------------------------------------***--------------------------------------------------------------------Abstract - Cognitive radio is a essential tool for a spectrum utilization. It provides opportunity to use spectrum in strategic manner to both Primary users and secondary users. Primary users have a license to use spectrum. Secondary users doesn’t have license to use spectrum resourses. Secondary users are called cognitive users. Purpose of spectrum sensing is to detect presence of unused channels in spectrum. In spectrum sensing, there are three popular methods. Energy detection method, matched filter method and cyclostationary based detection method. In this paper matched filter method implemented according to various parameters. The performance was assessed by using the MATLAB based on the AWGN channel.
2. GENERAL MODEL FOR SPECTRUM SENSING
Key Words: Cognitive radio, spectrum sensing, Matched Filter detection, AWGN channel.
where, n=1….N, N is the sample number, y (n) is the SU received signal, s (n) is the PU signal, w(n) is the additive white Gaussian noise (AWGN) with zero mean and variance , h is the complex channel gain of the sensing channel, H0 denotes the PU signal is absent, and H1 denotes the PU signal is present.
1. INTRODUCTION Marconni (an inventor of radio)’s first experiment on the radio, radio-communication systems do not cease to multiply to become indispensable to our days. This evolution has been accompanied by an increased demand in radio resources. The resources accessible by the existing technologies do not allow them to meet the demand. In order to overcome the scarcity of frequencies, we have new concepts of sharing and sensing of resources, as the dynamic allocation of a radio channel has a new communication has been developed. In the last twenty years have seen a veritable explosion of telecommunication services. From mobile technology to wireless transmission of data, the quantity of general public services increases and the scarcity of frequencies are more than ever aggravated. According to the Federal Communications Commission (FCC), body of regulation and spectrum management in the US, In more than 70% of cases, the spectrum is under-used next time or space [1]. The problem of the shortage of frequencies is artificial and the current policy of static management of the spectrum is responsible. So, new approaches to dynamic access to the radio spectrum have developed, or access opportunistic is the most widespread because it tackles the cause of the shortage of frequencies. There are four primary objectives of cognitive radio: spectrum sensing, spectrum sharing, spectrum management and spectrum mobility.
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Spectrum sensing allows the cognitive radio users to learn about the radio environment by detecting the presence of an event using one or multiple sensors. It consists in detecting the PU signal transmission in a given time to make decision to transmit in a frequency band. The spectrum sensing model can be formulated as follows: y(n) = w(n)
: PU absent
y(n) = h * s(n) + w(n)
: PU present
The output τ of the detector is compared to a threshold to make the right decision: If τ ≥ threshold then PU signal is present. If τ < threshold then PU signal is absent. 3. MATCHED FILTER BASED DETECTION The matched filter is a system of linear filter used in the digital signal processing. It is used to optimize the SNR in existence of the additive noise stochastic. It provides the coherent detection. Figure 1 shows the block diagram for this in which a signal received from primary use is transmitted through AWGN (Additive White Gaussian Noise) channel and the transmitted signal is given to matched filter. Matched filter correlates the signal with time modified version. Then comparison between the predetermined threshold and the final output of matched filter will determine the presence of the primary user.
Figure 1: Basic block diagram of matched filter based spectrum sensing ISO 9001:2008 Certified Journal
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