Volume-based spectrum sensing for OFDM based cognitive radio

Abstract

Due to the exponential increment of spectrum requirement in multimedia application, leads to spectrum scarcity. Traditionally licensed spectrum is used only by licensees over relatively long time period with the help of FSA (fixed spectrum allocation) which guarantees the licensed authorized party without interference. According to FCC records, utilization efficiency varies between 15% to 85%, for spectrum allocated in the bands below 3GHz. Due to shortage of frequencies the BW becomes expensive. Cognitive radio (CR) play an important role between scarcity of spectrum and underutilization of the available spectrum. In CR one of the most important technique is spectrum sensing. Spectrum sensing helps to detect the spectrum holes. Energy detection method is one of the simplest spectrum sensing method. But it is particularly challenging for small sample size, low SNR (due to noise uncertainty) and fixing the threshold in conventional energy detection. OFDM-FFT and DWT are the multi carrier modulations used in CR to encounter with high data rates and give high spectral efficiency. In this paper we proposed a volume detection algorithm which using random matrix theory (RMT), provide an efficient spectrum sensing algorithm for OFDM modulated signals implement in CR. It is applied when the PU uses OFDM modulation. With the help of SMT (sample covariance matrix) the theoretical decision threshold accurately produce under the Gaussian noise assumption.