Cooperative Spectrum Sensing Method Using Subband Decomposition with DCT for Cognitive Radio System In this paper a new cooperative spectrum sensing method for cognitive radio systems is presented. The proposed method is based on a new soft decision rule at Fusion Centre (FC) for deciding the primary user (PU) signal presence using the received energy from each Cognitive User (CU) after performing a set of transformations. The sensing process can be summarized as follows: each CU collects the available spectrum and onelevel Discrete Wavelet Transform (DWT) decomposition for the input spectrum is taken. After the decomposition, only the first lower frequencies (LL) and the last high frequencies (HH) bands of twodimensional DWT are truncated. Then Discrete Cosine Transform (DCT) for the truncated subbands is computed. The energy of each subband with Average Ratio (AR) between LL and HH energies is calculated. Finally, only the energy in LL band and AR are sent to FC via reporting channel. At FC the received energies and ARs from all CUs are averaged. The proposed fusion rule is designed such that if the average energy falls below the half of predefined threshold, PU is declared to be absent. From other hand if the average energy equals or greater than threshold value and average AR is greater than 1, PU is declared to be present. Otherwise, it is declared to be absent. The simulation results in both AWGN and Rayleigh fading channels showed that the proposed method has improved detection probability especially at low SNR, reduced sensing time and reduced energy consumption as compared to censoring hard fusion rules available in the literature.

Double Threshold Soft Decision Rule for Improving Performance of Cognitive Radio Networks We propose an efficient soft decision rule to enhance the detection of unused spectra and to improve cognitive radio (CR) throughput. The performance of this rule is evaluated for additive white Gaussian noise and Rayleigh fading channels and compared with the square law and maximal ratio combining rules. For a signal to noise ratio (SNR) of 2dB, the proposed rule enhances the probability of a false alarm by 68% and 95% respectively in case of additive white Gaussian noise and by 53% and 92% in case of Rayleigh fading channels. The simulation results also show that the proposed method enhances throughput compared to the other rules. Over Rayleigh fading channels, throughput is enhanced by 210% compared to square law combining rule and 40% compared to the maximal ratio combining rule.