Study on Spectrum Sensing Techniques

Author Name(s): Prof. Vijaylaxmi Jain, Dr.Tanuja Dhope, Prof. Bahubali Shiragapur
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Cognitive radio is a recent emerging technology for effective use of spectrum. To provide newer opportunities in advanced wireless communication system. Spectrum sensing and security are the key issues of Cognitive Radio (CR). The main aim of Cognitive Radio (CR) is to detect unused or idle frequencies of cellular spectrum, not used by Primary User (PU’s). Practically PU’s frequencies can be idle or busy. The goal is to investigate spectrum sensing predictive methods. These methods find idle or busy states of frequencies at discrete interval of time periods. The decision is made to assign these free frequencies to Secondary Users (SU’s). For this we use Machine Learning (ML) techniques to improve its performance, usability and efficiency. A machine learning system includes pre-processing, feature extraction and decision making classifier. This paper lists recent research activities and co-operative spectrum sensing. Identification of CR terminals is done by predictive spectrum sensing methods. Machine learning algorithm are used for classification.


Now a day’s requirement of bandwidth has increased a lot. This forced research community to find new better techniques for radio spectrum utilization. To achieve this goal the dynamic usage of cellular spectrum is required. Spectrum sharing capability results to higher spectral efficiency. Cognitive Radio recognizes spectrum white spaces which are idle & can be reused by secondary users (SU’s). A main role of a CR is to detect white spaces and based on priority allocate to SUs. This increases the spectral efficiency and the channel capacity. The ‘Shannon Channel Capacity’ is given by C = Blog(1 + SNR). Where C is channel capacity, B is Bandwidth and SNR is signal to noise ratio. To fulfill the user requirement spectrum needs to be managed effectively. This adaptive spectral efficiency of 4G network is reaching to Shannon limit. Thus Cognitive radio enables next generation networks to utilize the spectrum more efficiently.


In cognitive radio network spectrum sensing is key process. We have studied different technique and challenge to sense the spectrum and details are discussed in this paper.

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