Filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) is considered as a powerful supplementary waveform for future wireless communications. However, FBMC systems have the same high peak-to-average power ratio (PAPR) problem as other multi-carrier systems, and the PAPR reduction methods designed for orthogonal frequency division multiplexing (OFDM) systems cannot be directly applied to FBMC systems due to the unique overlapping structure of FBMC signals. Therefore, some PAPR suppression schemes tailored to FBMC systems have been proposed, but their computational complexity is prohibitively high for some practical applications. In this paper, we propose a conversion vector-based low-complexity dispersive selection mapping (DSLM) scheme, called the C-DSLM scheme, to reduce the PAPR of FBMC signals. In the C-DSLM scheme, a series of conversion vectors is first carefully designed for FBMC signals with overlapping structures, and then candidate signals are generated by multiplying the original signal by the cyclic shift of the conversion vectors with only a few nonzero elements. The complexity evaluation and simulation results show that the C-DSLM scheme's PAPR suppression performance is similar to that of the DSLM scheme with computational complexity is only approximately 10% of that of the DSLM scheme. Our proposed C-DSLM scheme is highly efficient and strongly applicable.

Accurate monitoring of hydraulic fracturing fracture morphology is of great significance to the follow-up exploration and development work. Electromagnetic monitoring of fractures can effectively identify the effective propped volume (EPV) of fracturing fractures, making up for the disadvantages of other monitoring methods. This letter introduces a modeling method and a physical model based on very-low-frequency (VLF) electromagnetic scattering theory for monitoring the development of asymmetric fracturing fractures. The 3-D finite-element method (FEM) of equivalent fracturing fracture on transition boundary condition (TBC) surface is used to realize the fast forward modeling of 3-D space receiving response in large formations. A sector-shaped receiver is designed and the relationship between electromagnetic receiving signals and orientation parameters of asymmetric fracturing fractures, such as direction of fracture development and tilt angle, is discussed. By analyzing 3-D signals obtained from the rotating receiver sector, the spatial state of multiple asymmetric fracturing fractures can be determined. The problem of how to identify the 3-D direction of crack growth with electromagnetic monitoring method is solved, which provides a theoretical reference for the development and inversion of detection instruments.

The characterization of hydraulic fractures is crucial for fracturing evaluation and strategy optimization. Low-frequency electromagnetic triaxial induction measurement is a promising candidate in hydraulic fracture characterization. However, it is difficult to accurately monitor fracture shape, orientation, and the multistage fracture network distribution. A novel method that combines triaxial induction measurement with sector-shaped coils axial rotation measurement (TIM-SCARM) is proposed to characterize hydraulic fractures. It is implemented by using the finite element method with transition boundary conditions (FEM-TBCs), which approximates the thin fracture as a surface to enhance the computational efficiency. The study focuses on quantitative analysis of conductivity, cross-sectional shape, half-length, and orientation of hydraulic fractures to assess their effects on specific configurations of the TIM-SCARM. Furthermore, the correlations between multicomponent signals and fracture characteristics are investigated. Numerical results indicate that the coaxial component signal in SCARM can distinguish the cross-sectional shape and orientation. The cross-polarized component signals provide important features of tilted fractures, and the 3-D signal obtained by instrument rotation could determine the spatial distribution of fracture networks. Therefore, measurements that integrate the multicomponent signals and axial information improve fracture geometry evaluation.