Abstract-This paper presents a novel differential energy detection scheme for multi-carrier systems, which can form fast and reliable decision of spectrum availability even in very low signalto-noise ratio (SNR) environment. For example, the proposed scheme can reach 90% in probability of detection (PD) and 10% in probability of false alarm (PFA) for the SNRs as low as −21 dB, while the observation length is equivalent to 2 multi-carrier symbol duration. The underlying initiative of the proposed scheme is applying order statistics on the clustered differential energy-spectral-density (ESD) in order to exploit the channel frequency diversity inherent in high data-rate communications. Specifically, to enjoy a good frequency diversity, the clustering operation is utilized to group uncorrelated subcarriers, while, the differential operation applied onto each cluster can effectively remove the noise floor and consequently overcome the impact of noise uncertainty while exploiting the frequency diversity. More importantly, the proposed scheme is designed to allow robustness in terms of both, time and frequency offsets. In order to analytically evaluate the proposed scheme, PFA and PD for Rayleigh fading channel are derived. The closed-form expressions show a clear relationship between the sensing performance and the cluster size, which is an indicator of the diversity gain. Moreover, we are able to observe up to 10 dB gain in the performance compared to the state-of-the-art spectrum sensing schemes.Index Terms-Differential, energy detection, low signal-tonoise ratio (SNR), multi-carrier, spectrum sensing.

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Abstract-This paper presents a novel frequency-domain energy detection scheme based on extreme statistics for robust sensing of OFDM sources in the low SNR region. The basic idea is to exploit the frequency diversity gain inherited by frequency selective channels with the aid of extreme statistics of the differential energy spectral density (ESD). Thanks to the differential stage the proposed spectrum sensing is robust to noise uncertainty problem. The low computational complexity requirement of the proposed technique makes it suitable for even machine-to-machine sensing. Analytical performance analysis is performed in terms of two classical metrics, i.e. probability of detection and probability of false alarm. The computer simulations carried out further show that the proposed scheme outperforms energy detection and second order cyclostationarity based approach for up to 10 dB gain in the low SNR range.

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In this study, the effect of borage (Borago officinalis) powder on juveniles of common carp (Cyprinus carpio) were investigated. The diets contained control (0), 0.5%, 1.5%, and 2.5% of borage powder. The fish with the initial average weight of 8.40 ± 1.37 were allotted to 12 circular tanks of 300 L capacity at a density of ten fish per each tank and fed to apparent satiety three times a day. The growth performance of the fish showed no significant difference compared to the control group (P > 0.05). By adding 1.5% borage powder to the control diet the mucosal immunity of fish in terms of lysozyme activity (14.26%), total protein (69.64%), immunoglobulin (30.78%), and humoral immunity in term of lysozyme activity (9.7%), complement components C3 (8.27%), C4 (21.64%), and total protein (9.33%) were increased significantly (P < 0.05). A total number of red blood cell (12.39%), mean corpuscular volume (MCV, 8.99%), mean corpuscular hemoglobin (MCH, 10.22%), and hemoglobin (2.69%) showed a significant increase in the fish fed supplemented diet with 1.5% borage powder compared to the control (P < 0.05). The results showed supplemented diet with 1.5% dietary borage powder induced high immunity and survival rate of juvenile common carp.