Design of WaveletEncoded Symbol Constellations for Cyclostationary Spectrum Sensing In mobile communication systems, the signals propagate through multipath over timevarying channels, which are subject to distortion caused by fading and Doppler shifts. In order to minimize such distortions, coding techniques and transmission diversity can be employed, e.g., wavelet coding. In this work, the wavelet coding is investigated in scenarios of cognitive radio systems with dynamic spectrum access. Cognitive radio systems with dynamic spectrum access should be able to sense unoccupied frequency bands for opportunistic transmissions, as well as detect the presence of primary users when they occupy their licensed spectrum. Therefore, an essential element for the accurate operation of cognitive radio systems encoded by wavelet coding is the ability to sense the signals encoded by this technique. It is effectively demonstrated that the possibility of sensing such signals is associated with a suitable design of the signal constellation used in the modulation of the coded symbols. The constellation design of these is performed via genetic algorithms using a multiobjective optimization approach. The developed system is evaluated according to the robustness to timevarying flat fading through a bit error probability (BER) versus EbN0 analysis. The spectral sensing ability is also addressed employing the cyclostationary analysis. The results denote the feasibility of using wavelet coding in radio scenarios with dynamic spectrum access, with good performance in terms of BER and signal detection rates.

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.