In multi-carrier wireless OFDM communication systems, a major issue is related to high peaks in transmitted signals, resulting in such problems as power inefficiency. In this regard, a common practice is to transmit t...In multi-carrier wireless OFDM communication systems, a major issue is related to high peaks in transmitted signals, resulting in such problems as power inefficiency. In this regard, a common practice is to transmit the signal that has the lowest Peak to Average Power Ratio (PAPR). Consequently, some efficient and accurate method of estimating the PAPR of a signal is required. Previous literature in this area suggests a strong relationship between PAPR and Power Variance (PV). As such, PV has been advocated as a good measure of PAPR. However, contrary to what is suggested in the literature, our research shows that often low values of PV do not correspond to low values of PAPR. Hence, PV does not provide a sound scientific basis for comparing and estimating PAPR in OFDM signals. In this paper a novel, effective, and efficient measure of high peaks in OFDM signals is proposed, which is less complex than PAPR. The proposed measure, termed as Partial Power Variance (PPV), exploits the relationship among PAPR, Aperiodic Autocorrelation Co-efficient (AAC), and Power Variance (PV) of the transmitted signal. Our results demonstrate that, in comparison to PV, Partial Power Variance is a more efficient as well as a more effective measure of PAPR. In addition, we demonstrate that the computational complexity of PPV is far less than that of PAPR.展开更多
The total biomass of a stand is an indicator of stand productivity and is closely related to the density of plants. According to the self-thinning law, mean individual biomass follows a negative power law with plant d...The total biomass of a stand is an indicator of stand productivity and is closely related to the density of plants. According to the self-thinning law, mean individual biomass follows a negative power law with plant density. If the variance of individual biomass is constant, we can expect increased stand productivity with increasing plant density. However, Taylor's power law(TPL) that relates the variance and the mean of many biological measures(e.g. bilateral areal differences of a leaf, plant biomass atdifferent times, developmental rates at different temperatures, population densities on different spatial or temporal scales), affects the estimate of stand productivity when it is defined as the total biomass of large plants in a stand.Because the variance of individual biomass decreases faster than mean individual biomass, differences in individual biomass decline with increasing density, leading to more homogeneous timbers of greater economic value. We tested whether TPL in plant biomass holds for different species and whether the variance of individual biomass changes faster than the mean with increasing stand density.The height, ground diameter and fresh weight of 50 bamboo species were measured in 50 stands ranging from 1 m by 1 m to 30 m by 30 m to ensure more than 150 bamboos in every stand. We separately examined TPL in height,ground diameter, and weight, and found that TPL holds for all three biological measures, with the relationship strongest for weight. Using analysis of covariance to compare the regression slopes of logarithmic mean and variance against the logarithm of density, we found that the variance in individual biomass declined faster than the mean with increasing density. This suggests that dense planting reduced mean individual biomass but homogenized individual biomass. Thus, there exists a trade-off between effective stand productivity and stand density for optimal forest management. Sparse planting leads to large variation in individual biomass, whereas dense planting reduces mean indiv展开更多
The inter-cycle correlation of fission source distributions(FSDs)in the Monte Carlo power iteration process results in variance underestimation of tallied physical quantities,especially in large local tallies.This stu...The inter-cycle correlation of fission source distributions(FSDs)in the Monte Carlo power iteration process results in variance underestimation of tallied physical quantities,especially in large local tallies.This study provides a mesh-free semiquantitative variance underestimation elimination method to obtain a credible confidence interval for the tallied results.This method comprises two procedures:Estimation and Elimination.The FSD inter-cycle correlation length is estimated in the Estimation procedure using the Sliced Wasserstein distance algorithm.The batch method was then used in the elimination procedure.The FSD inter-cycle correlation length was proved to be the optimum batch length to eliminate the variance underestimation problem.We exemplified this method using the OECD sphere array model and 3D PWR BEAVRS model.The results showed that the average variance underestimation ratios of local tallies declined from 37 to 87%to within±5%in these models.展开更多
文摘In multi-carrier wireless OFDM communication systems, a major issue is related to high peaks in transmitted signals, resulting in such problems as power inefficiency. In this regard, a common practice is to transmit the signal that has the lowest Peak to Average Power Ratio (PAPR). Consequently, some efficient and accurate method of estimating the PAPR of a signal is required. Previous literature in this area suggests a strong relationship between PAPR and Power Variance (PV). As such, PV has been advocated as a good measure of PAPR. However, contrary to what is suggested in the literature, our research shows that often low values of PV do not correspond to low values of PAPR. Hence, PV does not provide a sound scientific basis for comparing and estimating PAPR in OFDM signals. In this paper a novel, effective, and efficient measure of high peaks in OFDM signals is proposed, which is less complex than PAPR. The proposed measure, termed as Partial Power Variance (PPV), exploits the relationship among PAPR, Aperiodic Autocorrelation Co-efficient (AAC), and Power Variance (PV) of the transmitted signal. Our results demonstrate that, in comparison to PV, Partial Power Variance is a more efficient as well as a more effective measure of PAPR. In addition, we demonstrate that the computational complexity of PPV is far less than that of PAPR.
基金supported by the National Natural Science Foundation of China(31870575)the Key Project of National Science&Technology Ministry(No.2015BAD04B02)the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘The total biomass of a stand is an indicator of stand productivity and is closely related to the density of plants. According to the self-thinning law, mean individual biomass follows a negative power law with plant density. If the variance of individual biomass is constant, we can expect increased stand productivity with increasing plant density. However, Taylor's power law(TPL) that relates the variance and the mean of many biological measures(e.g. bilateral areal differences of a leaf, plant biomass atdifferent times, developmental rates at different temperatures, population densities on different spatial or temporal scales), affects the estimate of stand productivity when it is defined as the total biomass of large plants in a stand.Because the variance of individual biomass decreases faster than mean individual biomass, differences in individual biomass decline with increasing density, leading to more homogeneous timbers of greater economic value. We tested whether TPL in plant biomass holds for different species and whether the variance of individual biomass changes faster than the mean with increasing stand density.The height, ground diameter and fresh weight of 50 bamboo species were measured in 50 stands ranging from 1 m by 1 m to 30 m by 30 m to ensure more than 150 bamboos in every stand. We separately examined TPL in height,ground diameter, and weight, and found that TPL holds for all three biological measures, with the relationship strongest for weight. Using analysis of covariance to compare the regression slopes of logarithmic mean and variance against the logarithm of density, we found that the variance in individual biomass declined faster than the mean with increasing density. This suggests that dense planting reduced mean individual biomass but homogenized individual biomass. Thus, there exists a trade-off between effective stand productivity and stand density for optimal forest management. Sparse planting leads to large variation in individual biomass, whereas dense planting reduces mean indiv
基金supported by China Nuclear Power Engineering Co.,Ltd.Scientific Research Project(No.KY22104)the fellowship of China Postdoctoral Science Foundation(No.2022M721793).
文摘The inter-cycle correlation of fission source distributions(FSDs)in the Monte Carlo power iteration process results in variance underestimation of tallied physical quantities,especially in large local tallies.This study provides a mesh-free semiquantitative variance underestimation elimination method to obtain a credible confidence interval for the tallied results.This method comprises two procedures:Estimation and Elimination.The FSD inter-cycle correlation length is estimated in the Estimation procedure using the Sliced Wasserstein distance algorithm.The batch method was then used in the elimination procedure.The FSD inter-cycle correlation length was proved to be the optimum batch length to eliminate the variance underestimation problem.We exemplified this method using the OECD sphere array model and 3D PWR BEAVRS model.The results showed that the average variance underestimation ratios of local tallies declined from 37 to 87%to within±5%in these models.
