A low-complexity orthogonal time frequency space modulation method for underwater acoustic communication

Compared with the orthogonal frequency division multiplexing (OFDM) modulation, the orthogonal time frequency space(OTFS) modulation has a lower peak-to-average power ratio. It can effectively resist the time selective fading caused by the Doppler effect and has significant performance advantages over doubly dispersive channels. However, the conventional OTFS linear minimum mean square error (LMMSE) method has a high complexity and is not easy to process in real time. In order to solve this problem, we propose a low-complexity equalization algorithm with infinite norm constraints based on the optimal coordinate reduction. The equalization algorithm not only obtains the optimal solution through a certain number of iterations and avoids direct matrix inversion but also equalizes infinite norm constraints to improve the symbol detection performance gains. At the same time, the OTFS delay-Doppler channel matrix we utilize is sparse and the two-norm squares of each column vector equally reduces the complexity of optimal coordinate descent. Finally, the simulation in the underwater acoustic communication scenario we designed verify the effectiveness of the proposed equalization algorithm. The simulation results show that the performance of the proposed equalization algorithm is close to that of the LMMSE method, while its low complexity is ensured.

An optimised one-way wave migration method for complex media with arbitrarily varying velocity based on eigen-decomposition

The classical one-way generalised screen propagator (GSP) and Fourier finite-difference (FFD) schemes have limitations in imaging large angles in complex media with substantial lateral variations in wave velocity. Some improvements to the classical one-way wave scheme have been proposed with optimised methods. However, the performance of these methods in imaging complex media remains unsatisfying. To overcome this issue, a new strategy for wavefield extrapolation based on the eigenvalue and eigenvector decomposition of the Helmholtz operator is presented herein. In this method, the square root operator is calculated after the decomposition of the Helmholtz operator at the product of the eigenvalues and eigenvectors. Then, Euler transformation is applied using the best polynomial approximation of the trigonometric function based on the infinite norm, and the propagator for one-way wave migration is calculated. According to this scheme, a one-way operator can be computed more accurately with a lower-order expansion. The imaging performance of this scheme was compared with that of the classical GSP, FFD and the recently developed full-wave-equation depth migration (FWDM) schemes. The impulse responses in media with arbitrary velocity inhomogeneity demonstrate that the proposed migration scheme performs better at large angles than the classical GSP scheme. The wavefronts calculated in the dipping and salt dome models illustrate that this scheme can provide a precise wavefield calculation. The applications of the Marmousi model further demonstrate that the proposed approach can achieve better-migrated results in imaging small-scale and complex structures, especially in media with steep-dipping faults.

Quantum cosmology with dynamical vacuum in a minimal-length scenario

In this work, we consider effects of the dynamical vacuum in quantum cosmology in presence of a minimum length introduced by the GUP (generalized uncertainty principle) related to the modified commutation relation $$[{\hat{X}},{\hat{P}}] := \frac{i\hbar }{ 1 - \beta {\hat{P}}^2 }$$ [ X ^ , P ^ ] : = i ħ 1 - β P ^ 2 . We determine the wave function of the Universe $$ \psi _{qp}(\xi ,t)$$ ψ qp ( ξ , t ) , which is solution of the modified Wheeler–DeWitt equation in the representation of the quasi-position space, in the limit where the scale factor of the Universe is small. Although $$\psi _{qp}(\xi ,t)$$ ψ qp ( ξ , t ) is a physically acceptable state it is not a realizable state of the Universe because $$ \psi _{qp}(\xi ,t)$$ ψ qp ( ξ , t ) has infinite norm, as in the ordinary case with no minimal length.

Novel Transparent Boundary Conditions for the Regularized Long Wave Equation

In this paper, we present a new method to derive transparent boundary conditions for the Regularized Long Wave equation and its linearized equation. These boundary conditions have the advantage of being exact for both linearized and nonlinear equations. The resulting problems supplemented with initial data are approximated numerically using finite difference method in space discretization and Crank–Nicolson scheme in time for the linearized equation, while implicit scheme in time is used for the Regularized Long Wave equation. Numerical experiments are made for solitary initial data and various source terms to illustrate the transparency of the introduced boundary conditions. Results are compared with the use of usual boundary conditions, namely, Dirichlet and Neumann via infinite norm error on the boundary and also by displaying geophones and instantaneous figures.

An Infinite-Norm Algorithm for Joystick Kinematic Control of Two-Wheeled Vehicles

In this paper, we propose an algorithm based on the mathematical p-norm which has been applied to improve both the traction power and the trajectory smoothness of joystick-controlled two-wheeled vehicles. This algorithm can theoretically supply 100% of available power to each of the actuators if the infinity-norm is used, i.e., when the p-norm tends to infinity. Furthermore, a geometrical model using the radius of curvature has been developed to track the effect of the proposed algorithm on the vehicle’s trajectory. Findings in this research work contribute to the kinematic control and path planning algorithms for vehicles actuated by two wheels, such as tanks and electric wheelchairs, both of vital importance for the security and heath industry. Computer simulations and experiments with a real robot are performed to verify the results.

Optimization Algorithm Analysis on Satellite Communication Signal Processing

Aiming at the difference between satellite’s signal frequency spectrum and satellite signals under specific channel condition, larger fluctuation and ineffective threshold searching method by adopting traditional energy, the paper improved singular point’s performance detection of traditional wavelet transform, selected suitable searching threshold by ultimately combining with both advantages and promoted searching performance of satellite signals under specific channel condition. Based on preprocessed order-1 subspace tracing algorithm of space sign function and infinite norm normalization, the paper solved the problem of degenerating performance of regular order-1 subspace tracing algorithm under noise environment of a stationary distribution effectively.