AWGN BASED SPECTRUM SENSING TECHNIQUES FOR ENERGY DETECTION-DOWNLOAD THE MATLAB P-CODE
DESIGN DETAILS
With the advancement in wireless communication, the demand for various types of mobile services have increased and higher data-rates are required. In order to increase data rates more spectrum is required most of the spectrum is allocated to television and radio broadcasts known as primary users (PU) but it has been observed that 70% of the spectrum is underutilized because the spectrum allocated to PU remains unutilized for certain time in a day. This spectrum can be allocated to unlicensed users called as secondary users (SU). This can be done with the help of cognitive radios. Cognitive radios perform four main operations: spectrum identification, spectrum detection, spectrum tracking and spectrum exploitation. Spectrum identification means determining whether the spectrum hole is wide enough in frequency to accommodate bandwidth of SU. Once a spectrum opportunity has been identified by a secondary user, the SU must detect when such opportunities exist and when they do not. Spectrum tracking is keeping track of the variations in the spectrum availability. Once the SU has gained knowledge about the spectrum it can access spectrum opportunities with a lower probability of interference. There are many techniques for sensing spectrum. In this Matlab design, comparative analysis of four techniques namely Energy detector, Matched filter, Covariance and Eigen value are considered.
DOWNLOAD THE MATLAB(P-CODE) FROM THE BELOW URL,
https://drive.google.com/file/d/1FMkf...
REFERENCES
Reference Paper-1: Comparative Study of Energy Detection and Matched Filter Based Spectrum Sensing Techniques
Author’s Name: A Parvathy and Gayathri Narayanan
Source: IEEE
Year: 2020
Reference Paper-2: Comparative Analysis of the Spectrum Sensing Techniques Energy Detection and Cyclostationary Feature Detection
Author’s Name: R.Gill and, A.Kansal
Source: IJAREEIE
Year: 2014
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